2020-09-15 20:39:22,497 ----------------------------------------------------------------------------------------------------
2020-09-15 20:39:22,498 Model: "SequenceTagger(
  (embeddings): TransformerWordEmbeddings(
    (model): BertModel(
      (embeddings): BertEmbeddings(
        (word_embeddings): Embedding(30000, 768, padding_idx=3)
        (position_embeddings): Embedding(512, 768)
        (token_type_embeddings): Embedding(2, 768)
        (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
        (dropout): Dropout(p=0.1, inplace=False)
      )
      (encoder): BertEncoder(
        (layer): ModuleList(
          (0): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (1): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (2): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (3): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (4): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (5): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (6): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (7): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (8): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (9): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (10): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
          (11): BertLayer(
            (attention): BertAttention(
              (self): BertSelfAttention(
                (query): Linear(in_features=768, out_features=768, bias=True)
                (key): Linear(in_features=768, out_features=768, bias=True)
                (value): Linear(in_features=768, out_features=768, bias=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
              (output): BertSelfOutput(
                (dense): Linear(in_features=768, out_features=768, bias=True)
                (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
                (dropout): Dropout(p=0.1, inplace=False)
              )
            )
            (intermediate): BertIntermediate(
              (dense): Linear(in_features=768, out_features=3072, bias=True)
            )
            (output): BertOutput(
              (dense): Linear(in_features=3072, out_features=768, bias=True)
              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
              (dropout): Dropout(p=0.1, inplace=False)
            )
          )
        )
      )
      (pooler): BertPooler(
        (dense): Linear(in_features=768, out_features=768, bias=True)
        (activation): Tanh()
      )
    )
  )
  (word_dropout): WordDropout(p=0.05)
  (locked_dropout): LockedDropout(p=0.5)
  (embedding2nn): Linear(in_features=3072, out_features=3072, bias=True)
  (rnn): LSTM(3072, 256, batch_first=True, bidirectional=True)
  (linear): Linear(in_features=512, out_features=20, bias=True)
  (beta): 1.0
  (weights): None
  (weight_tensor) None
)"
2020-09-15 20:39:22,499 ----------------------------------------------------------------------------------------------------
2020-09-15 20:39:22,499 Corpus: "Corpus: 15806 train + 2895 dev + 5195 test sentences"
2020-09-15 20:39:22,499 ----------------------------------------------------------------------------------------------------
2020-09-15 20:39:22,499 Parameters:
2020-09-15 20:39:22,499  - learning_rate: "0.1"
2020-09-15 20:39:22,499  - mini_batch_size: "32"
2020-09-15 20:39:22,499  - patience: "3"
2020-09-15 20:39:22,499  - anneal_factor: "0.5"
2020-09-15 20:39:22,499  - max_epochs: "150"
2020-09-15 20:39:22,499  - shuffle: "True"
2020-09-15 20:39:22,499  - train_with_dev: "True"
2020-09-15 20:39:22,499  - batch_growth_annealing: "False"
2020-09-15 20:39:22,499 ----------------------------------------------------------------------------------------------------
2020-09-15 20:39:22,499 Model training base path: "resources/taggers/dutch-bert-ner"
2020-09-15 20:39:22,499 ----------------------------------------------------------------------------------------------------
2020-09-15 20:39:22,499 Device: cuda:0
2020-09-15 20:39:22,499 ----------------------------------------------------------------------------------------------------
2020-09-15 20:39:22,499 Embeddings storage mode: cpu
2020-09-15 20:39:22,503 ----------------------------------------------------------------------------------------------------
2020-09-15 20:40:25,982 epoch 1 - iter 58/585 - loss 9.02671925 - samples/sec: 29.24 - lr: 0.100000
2020-09-15 20:41:26,830 epoch 1 - iter 116/585 - loss 6.57227961 - samples/sec: 30.51 - lr: 0.100000
2020-09-15 20:42:26,639 epoch 1 - iter 174/585 - loss 5.50421115 - samples/sec: 31.04 - lr: 0.100000
2020-09-15 20:43:28,614 epoch 1 - iter 232/585 - loss 4.91990340 - samples/sec: 29.95 - lr: 0.100000
2020-09-15 20:44:28,462 epoch 1 - iter 290/585 - loss 4.45448867 - samples/sec: 31.01 - lr: 0.100000
2020-09-15 20:45:30,799 epoch 1 - iter 348/585 - loss 4.05986988 - samples/sec: 29.78 - lr: 0.100000
2020-09-15 20:46:28,634 epoch 1 - iter 406/585 - loss 3.75590321 - samples/sec: 32.09 - lr: 0.100000
2020-09-15 20:47:44,774 epoch 1 - iter 464/585 - loss 3.59221266 - samples/sec: 24.38 - lr: 0.100000
2020-09-15 20:49:01,075 epoch 1 - iter 522/585 - loss 3.36389842 - samples/sec: 24.33 - lr: 0.100000
2020-09-15 20:50:21,129 epoch 1 - iter 580/585 - loss 3.17420696 - samples/sec: 23.19 - lr: 0.100000
2020-09-15 20:50:28,023 ----------------------------------------------------------------------------------------------------
2020-09-15 20:50:28,024 EPOCH 1 done: loss 3.1551 - lr 0.1000000
2020-09-15 20:50:28,024 BAD EPOCHS (no improvement): 0
2020-09-15 20:50:28,027 ----------------------------------------------------------------------------------------------------
2020-09-15 20:51:00,615 epoch 2 - iter 58/585 - loss 1.70375227 - samples/sec: 56.97 - lr: 0.100000
2020-09-15 20:51:21,413 epoch 2 - iter 116/585 - loss 1.54357578 - samples/sec: 89.28 - lr: 0.100000
2020-09-15 20:51:35,286 epoch 2 - iter 174/585 - loss 1.57853562 - samples/sec: 133.87 - lr: 0.100000
2020-09-15 20:52:02,398 epoch 2 - iter 232/585 - loss 1.49992598 - samples/sec: 68.48 - lr: 0.100000
2020-09-15 20:52:33,736 epoch 2 - iter 290/585 - loss 1.45015041 - samples/sec: 59.24 - lr: 0.100000
2020-09-15 20:53:05,554 epoch 2 - iter 348/585 - loss 1.40867149 - samples/sec: 58.35 - lr: 0.100000
2020-09-15 20:53:37,077 epoch 2 - iter 406/585 - loss 1.38271532 - samples/sec: 58.89 - lr: 0.100000
2020-09-15 20:53:52,611 epoch 2 - iter 464/585 - loss 1.37491975 - samples/sec: 119.56 - lr: 0.100000
2020-09-15 20:54:05,493 epoch 2 - iter 522/585 - loss 1.42288860 - samples/sec: 144.17 - lr: 0.100000
2020-09-15 20:54:38,701 epoch 2 - iter 580/585 - loss 1.45792048 - samples/sec: 55.91 - lr: 0.100000
2020-09-15 20:54:41,269 ----------------------------------------------------------------------------------------------------
2020-09-15 20:54:41,269 EPOCH 2 done: loss 1.4533 - lr 0.1000000
2020-09-15 20:54:41,269 BAD EPOCHS (no improvement): 0
2020-09-15 20:54:41,273 ----------------------------------------------------------------------------------------------------
2020-09-15 20:55:12,977 epoch 3 - iter 58/585 - loss 1.07933304 - samples/sec: 58.56 - lr: 0.100000
2020-09-15 20:55:45,048 epoch 3 - iter 116/585 - loss 1.06587742 - samples/sec: 57.89 - lr: 0.100000
2020-09-15 20:56:14,239 epoch 3 - iter 174/585 - loss 1.08684647 - samples/sec: 63.60 - lr: 0.100000
2020-09-15 20:56:26,975 epoch 3 - iter 232/585 - loss 1.07807006 - samples/sec: 145.82 - lr: 0.100000
2020-09-15 20:56:42,827 epoch 3 - iter 290/585 - loss 1.11569723 - samples/sec: 117.16 - lr: 0.100000
2020-09-15 20:57:14,394 epoch 3 - iter 348/585 - loss 1.09693921 - samples/sec: 58.81 - lr: 0.100000
2020-09-15 20:57:45,890 epoch 3 - iter 406/585 - loss 1.07660729 - samples/sec: 58.94 - lr: 0.100000
2020-09-15 20:58:20,311 epoch 3 - iter 464/585 - loss 1.16957949 - samples/sec: 53.93 - lr: 0.100000
2020-09-15 20:58:44,811 epoch 3 - iter 522/585 - loss 1.19612699 - samples/sec: 75.78 - lr: 0.100000
2020-09-15 20:58:58,206 epoch 3 - iter 580/585 - loss 1.18278006 - samples/sec: 138.65 - lr: 0.100000
2020-09-15 20:58:58,770 ----------------------------------------------------------------------------------------------------
2020-09-15 20:58:58,770 EPOCH 3 done: loss 1.1825 - lr 0.1000000
2020-09-15 20:58:58,770 BAD EPOCHS (no improvement): 0
2020-09-15 20:58:58,829 ----------------------------------------------------------------------------------------------------
2020-09-15 20:59:20,357 epoch 4 - iter 58/585 - loss 0.97199818 - samples/sec: 86.26 - lr: 0.100000
2020-09-15 20:59:52,052 epoch 4 - iter 116/585 - loss 1.01320457 - samples/sec: 58.58 - lr: 0.100000
2020-09-15 21:00:23,547 epoch 4 - iter 174/585 - loss 0.93724664 - samples/sec: 58.95 - lr: 0.100000
2020-09-15 21:00:55,287 epoch 4 - iter 232/585 - loss 0.96507941 - samples/sec: 58.49 - lr: 0.100000
2020-09-15 21:01:14,058 epoch 4 - iter 290/585 - loss 0.95275335 - samples/sec: 98.93 - lr: 0.100000
2020-09-15 21:01:28,753 epoch 4 - iter 348/585 - loss 1.04891414 - samples/sec: 126.37 - lr: 0.100000
2020-09-15 21:01:54,590 epoch 4 - iter 406/585 - loss 1.06654501 - samples/sec: 71.86 - lr: 0.100000
2020-09-15 21:02:25,431 epoch 4 - iter 464/585 - loss 1.04015188 - samples/sec: 60.20 - lr: 0.100000
2020-09-15 21:02:55,522 epoch 4 - iter 522/585 - loss 1.02982810 - samples/sec: 61.70 - lr: 0.100000
2020-09-15 21:03:28,348 epoch 4 - iter 580/585 - loss 1.05496220 - samples/sec: 56.55 - lr: 0.100000
2020-09-15 21:03:30,909 ----------------------------------------------------------------------------------------------------
2020-09-15 21:03:30,909 EPOCH 4 done: loss 1.0544 - lr 0.1000000
2020-09-15 21:03:30,909 BAD EPOCHS (no improvement): 0
2020-09-15 21:03:30,913 ----------------------------------------------------------------------------------------------------
2020-09-15 21:03:47,055 epoch 5 - iter 58/585 - loss 0.84403375 - samples/sec: 115.05 - lr: 0.100000
2020-09-15 21:03:58,725 epoch 5 - iter 116/585 - loss 0.82691555 - samples/sec: 159.16 - lr: 0.100000
2020-09-15 21:04:29,875 epoch 5 - iter 174/585 - loss 0.94467663 - samples/sec: 59.60 - lr: 0.100000
2020-09-15 21:05:01,469 epoch 5 - iter 232/585 - loss 0.92686379 - samples/sec: 58.76 - lr: 0.100000
2020-09-15 21:05:34,466 epoch 5 - iter 290/585 - loss 0.93802412 - samples/sec: 56.26 - lr: 0.100000
2020-09-15 21:06:05,940 epoch 5 - iter 348/585 - loss 0.92046789 - samples/sec: 58.99 - lr: 0.100000
2020-09-15 21:06:19,082 epoch 5 - iter 406/585 - loss 0.91219689 - samples/sec: 141.34 - lr: 0.100000
2020-09-15 21:06:29,126 epoch 5 - iter 464/585 - loss 0.90746013 - samples/sec: 184.96 - lr: 0.100000
2020-09-15 21:07:02,010 epoch 5 - iter 522/585 - loss 0.95461371 - samples/sec: 56.46 - lr: 0.100000
2020-09-15 21:07:35,293 epoch 5 - iter 580/585 - loss 0.95385694 - samples/sec: 55.78 - lr: 0.100000
2020-09-15 21:07:37,895 ----------------------------------------------------------------------------------------------------
2020-09-15 21:07:37,895 EPOCH 5 done: loss 0.9525 - lr 0.1000000
2020-09-15 21:07:37,895 BAD EPOCHS (no improvement): 0
2020-09-15 21:07:37,899 ----------------------------------------------------------------------------------------------------
2020-09-15 21:08:09,546 epoch 6 - iter 58/585 - loss 0.75493402 - samples/sec: 58.67 - lr: 0.100000
2020-09-15 21:08:38,699 epoch 6 - iter 116/585 - loss 0.95209563 - samples/sec: 63.68 - lr: 0.100000
2020-09-15 21:08:52,632 epoch 6 - iter 174/585 - loss 1.02129598 - samples/sec: 133.30 - lr: 0.100000
2020-09-15 21:09:10,203 epoch 6 - iter 232/585 - loss 0.94976660 - samples/sec: 105.69 - lr: 0.100000
2020-09-15 21:09:42,479 epoch 6 - iter 290/585 - loss 0.94922707 - samples/sec: 57.52 - lr: 0.100000
2020-09-15 21:10:13,975 epoch 6 - iter 348/585 - loss 0.91314650 - samples/sec: 58.94 - lr: 0.100000
2020-09-15 21:10:45,498 epoch 6 - iter 406/585 - loss 0.88912685 - samples/sec: 58.89 - lr: 0.100000
2020-09-15 21:11:08,136 epoch 6 - iter 464/585 - loss 0.87824843 - samples/sec: 82.02 - lr: 0.100000
2020-09-15 21:11:22,481 epoch 6 - iter 522/585 - loss 0.89361478 - samples/sec: 129.47 - lr: 0.100000
2020-09-15 21:11:46,238 epoch 6 - iter 580/585 - loss 0.88050943 - samples/sec: 78.15 - lr: 0.100000
2020-09-15 21:11:48,717 ----------------------------------------------------------------------------------------------------
2020-09-15 21:11:48,717 EPOCH 6 done: loss 0.8837 - lr 0.1000000
2020-09-15 21:11:48,718 BAD EPOCHS (no improvement): 0
2020-09-15 21:11:48,722 ----------------------------------------------------------------------------------------------------
2020-09-15 21:12:20,555 epoch 7 - iter 58/585 - loss 0.73645943 - samples/sec: 58.32 - lr: 0.100000
2020-09-15 21:12:52,078 epoch 7 - iter 116/585 - loss 0.70882830 - samples/sec: 58.89 - lr: 0.100000
2020-09-15 21:13:24,249 epoch 7 - iter 174/585 - loss 0.74434740 - samples/sec: 57.71 - lr: 0.100000
2020-09-15 21:13:42,602 epoch 7 - iter 232/585 - loss 0.79621464 - samples/sec: 101.18 - lr: 0.100000
2020-09-15 21:13:53,011 epoch 7 - iter 290/585 - loss 0.77921367 - samples/sec: 178.46 - lr: 0.100000
2020-09-15 21:14:24,759 epoch 7 - iter 348/585 - loss 0.76553712 - samples/sec: 58.48 - lr: 0.100000
2020-09-15 21:14:57,666 epoch 7 - iter 406/585 - loss 0.79439826 - samples/sec: 56.42 - lr: 0.100000
2020-09-15 21:15:29,219 epoch 7 - iter 464/585 - loss 0.78544418 - samples/sec: 58.84 - lr: 0.100000
2020-09-15 21:16:00,667 epoch 7 - iter 522/585 - loss 0.77216768 - samples/sec: 59.04 - lr: 0.100000
2020-09-15 21:16:14,948 epoch 7 - iter 580/585 - loss 0.81523151 - samples/sec: 130.04 - lr: 0.100000
2020-09-15 21:16:16,233 ----------------------------------------------------------------------------------------------------
2020-09-15 21:16:16,233 EPOCH 7 done: loss 0.8123 - lr 0.1000000
2020-09-15 21:16:16,233 BAD EPOCHS (no improvement): 0
2020-09-15 21:16:16,236 ----------------------------------------------------------------------------------------------------
2020-09-15 21:16:36,931 epoch 8 - iter 58/585 - loss 0.95978505 - samples/sec: 89.73 - lr: 0.100000
2020-09-15 21:17:08,429 epoch 8 - iter 116/585 - loss 0.78491071 - samples/sec: 58.94 - lr: 0.100000
2020-09-15 21:17:39,995 epoch 8 - iter 174/585 - loss 0.74181226 - samples/sec: 58.81 - lr: 0.100000
2020-09-15 21:18:11,568 epoch 8 - iter 232/585 - loss 0.69305805 - samples/sec: 58.80 - lr: 0.100000
2020-09-15 21:18:32,111 epoch 8 - iter 290/585 - loss 0.69823679 - samples/sec: 90.39 - lr: 0.100000
2020-09-15 21:18:45,282 epoch 8 - iter 348/585 - loss 0.69447731 - samples/sec: 141.02 - lr: 0.100000
2020-09-15 21:19:06,466 epoch 8 - iter 406/585 - loss 0.69608810 - samples/sec: 87.65 - lr: 0.100000
2020-09-15 21:19:40,930 epoch 8 - iter 464/585 - loss 0.76718875 - samples/sec: 53.87 - lr: 0.100000
2020-09-15 21:20:12,490 epoch 8 - iter 522/585 - loss 0.76069690 - samples/sec: 58.83 - lr: 0.100000
2020-09-15 21:20:44,734 epoch 8 - iter 580/585 - loss 0.76063763 - samples/sec: 57.58 - lr: 0.100000
2020-09-15 21:20:47,326 ----------------------------------------------------------------------------------------------------
2020-09-15 21:20:47,327 EPOCH 8 done: loss 0.7603 - lr 0.1000000
2020-09-15 21:20:47,327 BAD EPOCHS (no improvement): 0
2020-09-15 21:20:47,349 ----------------------------------------------------------------------------------------------------
2020-09-15 21:21:03,689 epoch 9 - iter 58/585 - loss 0.61209200 - samples/sec: 113.67 - lr: 0.100000
2020-09-15 21:21:15,739 epoch 9 - iter 116/585 - loss 0.63037965 - samples/sec: 154.14 - lr: 0.100000
2020-09-15 21:21:42,833 epoch 9 - iter 174/585 - loss 0.62904081 - samples/sec: 68.53 - lr: 0.100000
2020-09-15 21:22:14,208 epoch 9 - iter 232/585 - loss 0.62278452 - samples/sec: 59.17 - lr: 0.100000
2020-09-15 21:22:45,769 epoch 9 - iter 290/585 - loss 0.63902286 - samples/sec: 58.82 - lr: 0.100000
2020-09-15 21:23:14,476 epoch 9 - iter 348/585 - loss 0.65304121 - samples/sec: 64.67 - lr: 0.100000
2020-09-15 21:23:32,434 epoch 9 - iter 406/585 - loss 0.66012702 - samples/sec: 103.41 - lr: 0.100000
2020-09-15 21:23:44,620 epoch 9 - iter 464/585 - loss 0.66068279 - samples/sec: 152.42 - lr: 0.100000
2020-09-15 21:24:14,185 epoch 9 - iter 522/585 - loss 0.70688683 - samples/sec: 62.80 - lr: 0.100000
2020-09-15 21:24:46,778 epoch 9 - iter 580/585 - loss 0.72331310 - samples/sec: 56.96 - lr: 0.100000
2020-09-15 21:24:49,201 ----------------------------------------------------------------------------------------------------
2020-09-15 21:24:49,201 EPOCH 9 done: loss 0.7205 - lr 0.1000000
2020-09-15 21:24:49,202 BAD EPOCHS (no improvement): 0
2020-09-15 21:24:49,206 ----------------------------------------------------------------------------------------------------
2020-09-15 21:25:21,764 epoch 10 - iter 58/585 - loss 0.85222130 - samples/sec: 57.02 - lr: 0.100000
2020-09-15 21:25:53,150 epoch 10 - iter 116/585 - loss 0.74850868 - samples/sec: 59.15 - lr: 0.100000
2020-09-15 21:26:05,714 epoch 10 - iter 174/585 - loss 0.71128669 - samples/sec: 147.82 - lr: 0.100000
2020-09-15 21:26:21,025 epoch 10 - iter 232/585 - loss 0.74463793 - samples/sec: 121.29 - lr: 0.100000
2020-09-15 21:26:53,307 epoch 10 - iter 290/585 - loss 0.78792858 - samples/sec: 57.51 - lr: 0.100000
2020-09-15 21:27:24,781 epoch 10 - iter 348/585 - loss 0.76123840 - samples/sec: 58.99 - lr: 0.100000
2020-09-15 21:27:56,405 epoch 10 - iter 406/585 - loss 0.73781124 - samples/sec: 58.71 - lr: 0.100000
2020-09-15 21:28:25,011 epoch 10 - iter 464/585 - loss 0.72195070 - samples/sec: 64.90 - lr: 0.100000
2020-09-15 21:28:37,241 epoch 10 - iter 522/585 - loss 0.71207287 - samples/sec: 151.87 - lr: 0.100000
2020-09-15 21:28:54,656 epoch 10 - iter 580/585 - loss 0.72591342 - samples/sec: 106.63 - lr: 0.100000
2020-09-15 21:28:57,242 ----------------------------------------------------------------------------------------------------
2020-09-15 21:28:57,242 EPOCH 10 done: loss 0.7225 - lr 0.1000000
2020-09-15 21:28:57,242 BAD EPOCHS (no improvement): 1
2020-09-15 21:28:57,245 ----------------------------------------------------------------------------------------------------
2020-09-15 21:29:30,186 epoch 11 - iter 58/585 - loss 0.61330870 - samples/sec: 56.36 - lr: 0.100000
2020-09-15 21:30:01,720 epoch 11 - iter 116/585 - loss 0.61642685 - samples/sec: 58.87 - lr: 0.100000
2020-09-15 21:30:33,282 epoch 11 - iter 174/585 - loss 0.59864615 - samples/sec: 58.82 - lr: 0.100000
2020-09-15 21:30:55,310 epoch 11 - iter 232/585 - loss 0.58746948 - samples/sec: 84.30 - lr: 0.100000
2020-09-15 21:31:08,925 epoch 11 - iter 290/585 - loss 0.57093563 - samples/sec: 136.41 - lr: 0.100000
2020-09-15 21:31:33,884 epoch 11 - iter 348/585 - loss 0.63680548 - samples/sec: 74.39 - lr: 0.100000
2020-09-15 21:32:06,121 epoch 11 - iter 406/585 - loss 0.64910112 - samples/sec: 57.59 - lr: 0.100000
2020-09-15 21:32:38,925 epoch 11 - iter 464/585 - loss 0.66617902 - samples/sec: 56.59 - lr: 0.100000
2020-09-15 21:33:11,613 epoch 11 - iter 522/585 - loss 0.68014512 - samples/sec: 56.79 - lr: 0.100000
2020-09-15 21:33:27,579 epoch 11 - iter 580/585 - loss 0.67756139 - samples/sec: 116.32 - lr: 0.100000
2020-09-15 21:33:28,811 ----------------------------------------------------------------------------------------------------
2020-09-15 21:33:28,811 EPOCH 11 done: loss 0.6747 - lr 0.1000000
2020-09-15 21:33:28,811 BAD EPOCHS (no improvement): 0
2020-09-15 21:33:28,824 ----------------------------------------------------------------------------------------------------
2020-09-15 21:33:40,031 epoch 12 - iter 58/585 - loss 0.89566245 - samples/sec: 165.78 - lr: 0.100000
2020-09-15 21:34:11,739 epoch 12 - iter 116/585 - loss 0.75823753 - samples/sec: 58.55 - lr: 0.100000
2020-09-15 21:34:43,157 epoch 12 - iter 174/585 - loss 0.69831899 - samples/sec: 59.09 - lr: 0.100000
2020-09-15 21:35:14,516 epoch 12 - iter 232/585 - loss 0.69214703 - samples/sec: 59.20 - lr: 0.100000
2020-09-15 21:35:45,816 epoch 12 - iter 290/585 - loss 0.66720429 - samples/sec: 59.31 - lr: 0.100000
2020-09-15 21:36:00,497 epoch 12 - iter 348/585 - loss 0.70374858 - samples/sec: 126.51 - lr: 0.100000
2020-09-15 21:36:17,272 epoch 12 - iter 406/585 - loss 0.68644595 - samples/sec: 110.71 - lr: 0.100000
2020-09-15 21:36:50,131 epoch 12 - iter 464/585 - loss 0.69675008 - samples/sec: 56.50 - lr: 0.100000
2020-09-15 21:37:21,635 epoch 12 - iter 522/585 - loss 0.67908250 - samples/sec: 58.93 - lr: 0.100000
2020-09-15 21:37:53,402 epoch 12 - iter 580/585 - loss 0.67141771 - samples/sec: 58.44 - lr: 0.100000
2020-09-15 21:37:55,875 ----------------------------------------------------------------------------------------------------
2020-09-15 21:37:55,875 EPOCH 12 done: loss 0.6684 - lr 0.1000000
2020-09-15 21:37:55,875 BAD EPOCHS (no improvement): 0
2020-09-15 21:37:55,879 ----------------------------------------------------------------------------------------------------
2020-09-15 21:38:19,661 epoch 13 - iter 58/585 - loss 0.58205660 - samples/sec: 78.08 - lr: 0.100000
2020-09-15 21:38:34,868 epoch 13 - iter 116/585 - loss 0.66643957 - samples/sec: 122.14 - lr: 0.100000
2020-09-15 21:39:03,415 epoch 13 - iter 174/585 - loss 0.62364415 - samples/sec: 65.04 - lr: 0.100000
2020-09-15 21:39:35,020 epoch 13 - iter 232/585 - loss 0.60238930 - samples/sec: 58.74 - lr: 0.100000
2020-09-15 21:40:06,651 epoch 13 - iter 290/585 - loss 0.59394921 - samples/sec: 58.69 - lr: 0.100000
2020-09-15 21:40:39,541 epoch 13 - iter 348/585 - loss 0.63326906 - samples/sec: 56.45 - lr: 0.100000
2020-09-15 21:40:55,686 epoch 13 - iter 406/585 - loss 0.64121954 - samples/sec: 115.02 - lr: 0.100000
2020-09-15 21:41:14,508 epoch 13 - iter 464/585 - loss 0.66773917 - samples/sec: 98.66 - lr: 0.100000
2020-09-15 21:41:46,096 epoch 13 - iter 522/585 - loss 0.65050017 - samples/sec: 58.77 - lr: 0.100000
2020-09-15 21:42:17,563 epoch 13 - iter 580/585 - loss 0.64553918 - samples/sec: 59.00 - lr: 0.100000
2020-09-15 21:42:20,024 ----------------------------------------------------------------------------------------------------
2020-09-15 21:42:20,024 EPOCH 13 done: loss 0.6438 - lr 0.1000000
2020-09-15 21:42:20,024 BAD EPOCHS (no improvement): 0
2020-09-15 21:42:20,029 ----------------------------------------------------------------------------------------------------
2020-09-15 21:42:51,788 epoch 14 - iter 58/585 - loss 0.48504858 - samples/sec: 58.46 - lr: 0.100000
2020-09-15 21:43:15,571 epoch 14 - iter 116/585 - loss 0.64031193 - samples/sec: 78.07 - lr: 0.100000
2020-09-15 21:43:28,851 epoch 14 - iter 174/585 - loss 0.61398125 - samples/sec: 139.85 - lr: 0.100000
2020-09-15 21:43:49,534 epoch 14 - iter 232/585 - loss 0.59582424 - samples/sec: 89.77 - lr: 0.100000
2020-09-15 21:44:23,990 epoch 14 - iter 290/585 - loss 0.66326206 - samples/sec: 53.88 - lr: 0.100000
2020-09-15 21:44:56,246 epoch 14 - iter 348/585 - loss 0.66484946 - samples/sec: 57.56 - lr: 0.100000
2020-09-15 21:45:27,762 epoch 14 - iter 406/585 - loss 0.64426975 - samples/sec: 58.91 - lr: 0.100000
2020-09-15 21:45:46,137 epoch 14 - iter 464/585 - loss 0.63448707 - samples/sec: 101.06 - lr: 0.100000
2020-09-15 21:45:58,724 epoch 14 - iter 522/585 - loss 0.63079730 - samples/sec: 147.55 - lr: 0.100000
2020-09-15 21:46:24,156 epoch 14 - iter 580/585 - loss 0.62357242 - samples/sec: 73.01 - lr: 0.100000
2020-09-15 21:46:26,614 ----------------------------------------------------------------------------------------------------
2020-09-15 21:46:26,614 EPOCH 14 done: loss 0.6215 - lr 0.1000000
2020-09-15 21:46:26,614 BAD EPOCHS (no improvement): 0
2020-09-15 21:46:26,617 ----------------------------------------------------------------------------------------------------
2020-09-15 21:46:58,519 epoch 15 - iter 58/585 - loss 0.50423465 - samples/sec: 58.20 - lr: 0.100000
2020-09-15 21:47:31,492 epoch 15 - iter 116/585 - loss 0.62962373 - samples/sec: 56.30 - lr: 0.100000
2020-09-15 21:48:02,993 epoch 15 - iter 174/585 - loss 0.57837085 - samples/sec: 58.93 - lr: 0.100000
2020-09-15 21:48:17,629 epoch 15 - iter 232/585 - loss 0.57381051 - samples/sec: 126.89 - lr: 0.100000
2020-09-15 21:48:28,319 epoch 15 - iter 290/585 - loss 0.56621148 - samples/sec: 173.80 - lr: 0.100000
2020-09-15 21:48:59,716 epoch 15 - iter 348/585 - loss 0.57691567 - samples/sec: 59.13 - lr: 0.100000
2020-09-15 21:49:32,055 epoch 15 - iter 406/585 - loss 0.59319052 - samples/sec: 57.41 - lr: 0.100000
2020-09-15 21:50:03,652 epoch 15 - iter 464/585 - loss 0.59376572 - samples/sec: 58.76 - lr: 0.100000
2020-09-15 21:50:35,208 epoch 15 - iter 522/585 - loss 0.58492945 - samples/sec: 58.83 - lr: 0.100000
2020-09-15 21:50:49,305 epoch 15 - iter 580/585 - loss 0.60177120 - samples/sec: 131.75 - lr: 0.100000
2020-09-15 21:50:50,504 ----------------------------------------------------------------------------------------------------
2020-09-15 21:50:50,504 EPOCH 15 done: loss 0.6004 - lr 0.1000000
2020-09-15 21:50:50,504 BAD EPOCHS (no improvement): 0
2020-09-15 21:50:50,507 ----------------------------------------------------------------------------------------------------
2020-09-15 21:51:04,143 epoch 16 - iter 58/585 - loss 0.50385409 - samples/sec: 136.21 - lr: 0.100000
2020-09-15 21:51:37,151 epoch 16 - iter 116/585 - loss 0.68599604 - samples/sec: 56.24 - lr: 0.100000
2020-09-15 21:52:10,036 epoch 16 - iter 174/585 - loss 0.66147200 - samples/sec: 56.45 - lr: 0.100000
2020-09-15 21:52:41,545 epoch 16 - iter 232/585 - loss 0.62528151 - samples/sec: 58.92 - lr: 0.100000
2020-09-15 21:53:08,201 epoch 16 - iter 290/585 - loss 0.59991103 - samples/sec: 69.65 - lr: 0.100000
2020-09-15 21:53:21,692 epoch 16 - iter 348/585 - loss 0.57740658 - samples/sec: 137.67 - lr: 0.100000
2020-09-15 21:53:42,798 epoch 16 - iter 406/585 - loss 0.61577702 - samples/sec: 87.97 - lr: 0.100000
2020-09-15 21:54:15,724 epoch 16 - iter 464/585 - loss 0.62277007 - samples/sec: 56.38 - lr: 0.100000
2020-09-15 21:54:47,373 epoch 16 - iter 522/585 - loss 0.60660917 - samples/sec: 58.66 - lr: 0.100000
2020-09-15 21:55:18,900 epoch 16 - iter 580/585 - loss 0.59541716 - samples/sec: 58.89 - lr: 0.100000
2020-09-15 21:55:21,379 ----------------------------------------------------------------------------------------------------
2020-09-15 21:55:21,379 EPOCH 16 done: loss 0.5958 - lr 0.1000000
2020-09-15 21:55:21,380 BAD EPOCHS (no improvement): 0
2020-09-15 21:55:21,383 ----------------------------------------------------------------------------------------------------
2020-09-15 21:55:40,266 epoch 17 - iter 58/585 - loss 0.74254123 - samples/sec: 98.34 - lr: 0.100000
2020-09-15 21:55:52,627 epoch 17 - iter 116/585 - loss 0.62284605 - samples/sec: 150.25 - lr: 0.100000
2020-09-15 21:56:19,006 epoch 17 - iter 174/585 - loss 0.60375935 - samples/sec: 70.39 - lr: 0.100000
2020-09-15 21:56:49,894 epoch 17 - iter 232/585 - loss 0.56779350 - samples/sec: 60.10 - lr: 0.100000
2020-09-15 21:57:22,632 epoch 17 - iter 290/585 - loss 0.59219112 - samples/sec: 56.71 - lr: 0.100000
2020-09-15 21:57:54,150 epoch 17 - iter 348/585 - loss 0.57785174 - samples/sec: 58.90 - lr: 0.100000
2020-09-15 21:58:10,032 epoch 17 - iter 406/585 - loss 0.56525757 - samples/sec: 116.94 - lr: 0.100000
2020-09-15 21:58:21,783 epoch 17 - iter 464/585 - loss 0.57377647 - samples/sec: 158.07 - lr: 0.100000
2020-09-15 21:58:52,057 epoch 17 - iter 522/585 - loss 0.58547860 - samples/sec: 61.32 - lr: 0.100000
2020-09-15 21:59:24,253 epoch 17 - iter 580/585 - loss 0.58979234 - samples/sec: 57.66 - lr: 0.100000
2020-09-15 21:59:26,843 ----------------------------------------------------------------------------------------------------
2020-09-15 21:59:26,844 EPOCH 17 done: loss 0.5896 - lr 0.1000000
2020-09-15 21:59:26,844 BAD EPOCHS (no improvement): 0
2020-09-15 21:59:26,849 ----------------------------------------------------------------------------------------------------
2020-09-15 21:59:57,583 epoch 18 - iter 58/585 - loss 0.52440896 - samples/sec: 60.41 - lr: 0.100000
2020-09-15 22:00:31,122 epoch 18 - iter 116/585 - loss 0.64459421 - samples/sec: 55.35 - lr: 0.100000
2020-09-15 22:00:43,701 epoch 18 - iter 174/585 - loss 0.64931560 - samples/sec: 147.66 - lr: 0.100000
2020-09-15 22:00:57,513 epoch 18 - iter 232/585 - loss 0.60005475 - samples/sec: 134.47 - lr: 0.100000
2020-09-15 22:01:29,119 epoch 18 - iter 290/585 - loss 0.57648625 - samples/sec: 58.74 - lr: 0.100000
2020-09-15 22:02:02,089 epoch 18 - iter 348/585 - loss 0.59672918 - samples/sec: 56.31 - lr: 0.100000
2020-09-15 22:02:33,862 epoch 18 - iter 406/585 - loss 0.57878899 - samples/sec: 58.43 - lr: 0.100000
2020-09-15 22:03:01,577 epoch 18 - iter 464/585 - loss 0.57073843 - samples/sec: 66.99 - lr: 0.100000
2020-09-15 22:03:14,900 epoch 18 - iter 522/585 - loss 0.59056539 - samples/sec: 139.41 - lr: 0.100000
2020-09-15 22:03:32,630 epoch 18 - iter 580/585 - loss 0.58165231 - samples/sec: 104.73 - lr: 0.100000
2020-09-15 22:03:35,135 ----------------------------------------------------------------------------------------------------
2020-09-15 22:03:35,135 EPOCH 18 done: loss 0.5814 - lr 0.1000000
2020-09-15 22:03:35,136 BAD EPOCHS (no improvement): 0
2020-09-15 22:03:35,142 ----------------------------------------------------------------------------------------------------
2020-09-15 22:04:06,980 epoch 19 - iter 58/585 - loss 0.52369872 - samples/sec: 58.31 - lr: 0.100000
2020-09-15 22:04:38,493 epoch 19 - iter 116/585 - loss 0.48490787 - samples/sec: 58.91 - lr: 0.100000
2020-09-15 22:05:10,862 epoch 19 - iter 174/585 - loss 0.57840532 - samples/sec: 57.36 - lr: 0.100000
2020-09-15 22:05:31,783 epoch 19 - iter 232/585 - loss 0.55862052 - samples/sec: 88.76 - lr: 0.100000
2020-09-15 22:05:45,375 epoch 19 - iter 290/585 - loss 0.54058501 - samples/sec: 136.65 - lr: 0.100000
2020-09-15 22:06:08,864 epoch 19 - iter 348/585 - loss 0.55123559 - samples/sec: 79.04 - lr: 0.100000
2020-09-15 22:06:43,074 epoch 19 - iter 406/585 - loss 0.59185125 - samples/sec: 54.27 - lr: 0.100000
2020-09-15 22:07:14,634 epoch 19 - iter 464/585 - loss 0.57585561 - samples/sec: 58.82 - lr: 0.100000
2020-09-15 22:07:46,104 epoch 19 - iter 522/585 - loss 0.56236330 - samples/sec: 58.99 - lr: 0.100000
2020-09-15 22:08:03,830 epoch 19 - iter 580/585 - loss 0.55659833 - samples/sec: 104.76 - lr: 0.100000
2020-09-15 22:08:05,123 ----------------------------------------------------------------------------------------------------
2020-09-15 22:08:05,123 EPOCH 19 done: loss 0.5547 - lr 0.1000000
2020-09-15 22:08:05,124 BAD EPOCHS (no improvement): 0
2020-09-15 22:08:05,129 ----------------------------------------------------------------------------------------------------
2020-09-15 22:08:15,926 epoch 20 - iter 58/585 - loss 0.46654771 - samples/sec: 172.07 - lr: 0.100000
2020-09-15 22:08:45,357 epoch 20 - iter 116/585 - loss 0.48345978 - samples/sec: 63.08 - lr: 0.100000
2020-09-15 22:09:18,152 epoch 20 - iter 174/585 - loss 0.51444969 - samples/sec: 56.61 - lr: 0.100000
2020-09-15 22:09:49,689 epoch 20 - iter 232/585 - loss 0.51273402 - samples/sec: 58.87 - lr: 0.100000
2020-09-15 22:10:21,170 epoch 20 - iter 290/585 - loss 0.50626923 - samples/sec: 58.97 - lr: 0.100000
2020-09-15 22:10:35,141 epoch 20 - iter 348/585 - loss 0.50303703 - samples/sec: 132.94 - lr: 0.100000
2020-09-15 22:10:46,971 epoch 20 - iter 406/585 - loss 0.50256912 - samples/sec: 157.00 - lr: 0.100000
2020-09-15 22:11:19,417 epoch 20 - iter 464/585 - loss 0.51837716 - samples/sec: 57.22 - lr: 0.100000
2020-09-15 22:11:52,520 epoch 20 - iter 522/585 - loss 0.54947001 - samples/sec: 56.08 - lr: 0.100000
2020-09-15 22:12:25,481 epoch 20 - iter 580/585 - loss 0.56973051 - samples/sec: 56.32 - lr: 0.100000
2020-09-15 22:12:27,956 ----------------------------------------------------------------------------------------------------
2020-09-15 22:12:27,956 EPOCH 20 done: loss 0.5683 - lr 0.1000000
2020-09-15 22:12:27,957 BAD EPOCHS (no improvement): 1
2020-09-15 22:12:27,974 ----------------------------------------------------------------------------------------------------
2020-09-15 22:12:55,603 epoch 21 - iter 58/585 - loss 0.45074064 - samples/sec: 67.20 - lr: 0.100000
2020-09-15 22:13:09,680 epoch 21 - iter 116/585 - loss 0.47648401 - samples/sec: 131.93 - lr: 0.100000
2020-09-15 22:13:28,351 epoch 21 - iter 174/585 - loss 0.45923720 - samples/sec: 99.46 - lr: 0.100000
2020-09-15 22:14:01,030 epoch 21 - iter 232/585 - loss 0.51575737 - samples/sec: 56.81 - lr: 0.100000
2020-09-15 22:14:32,875 epoch 21 - iter 290/585 - loss 0.50249695 - samples/sec: 58.30 - lr: 0.100000
2020-09-15 22:15:04,389 epoch 21 - iter 348/585 - loss 0.49407067 - samples/sec: 58.91 - lr: 0.100000
2020-09-15 22:15:25,438 epoch 21 - iter 406/585 - loss 0.50119494 - samples/sec: 88.21 - lr: 0.100000
2020-09-15 22:15:39,406 epoch 21 - iter 464/585 - loss 0.52624064 - samples/sec: 132.96 - lr: 0.100000
2020-09-15 22:16:01,758 epoch 21 - iter 522/585 - loss 0.52641706 - samples/sec: 83.07 - lr: 0.100000
2020-09-15 22:16:34,759 epoch 21 - iter 580/585 - loss 0.54432054 - samples/sec: 56.25 - lr: 0.100000
2020-09-15 22:16:37,113 ----------------------------------------------------------------------------------------------------
2020-09-15 22:16:37,113 EPOCH 21 done: loss 0.5439 - lr 0.1000000
2020-09-15 22:16:37,114 BAD EPOCHS (no improvement): 0
2020-09-15 22:16:37,118 ----------------------------------------------------------------------------------------------------
2020-09-15 22:17:08,536 epoch 22 - iter 58/585 - loss 0.45786948 - samples/sec: 59.09 - lr: 0.100000
2020-09-15 22:17:40,091 epoch 22 - iter 116/585 - loss 0.45287637 - samples/sec: 58.83 - lr: 0.100000
2020-09-15 22:17:57,817 epoch 22 - iter 174/585 - loss 0.50145901 - samples/sec: 104.76 - lr: 0.100000
2020-09-15 22:18:09,307 epoch 22 - iter 232/585 - loss 0.48452023 - samples/sec: 161.65 - lr: 0.100000
2020-09-15 22:18:38,720 epoch 22 - iter 290/585 - loss 0.47464224 - samples/sec: 63.12 - lr: 0.100000
2020-09-15 22:19:10,200 epoch 22 - iter 348/585 - loss 0.47572084 - samples/sec: 58.98 - lr: 0.100000
2020-09-15 22:19:43,690 epoch 22 - iter 406/585 - loss 0.51836053 - samples/sec: 55.44 - lr: 0.100000
2020-09-15 22:20:15,100 epoch 22 - iter 464/585 - loss 0.51142313 - samples/sec: 59.10 - lr: 0.100000
2020-09-15 22:20:28,363 epoch 22 - iter 522/585 - loss 0.51099227 - samples/sec: 140.05 - lr: 0.100000
2020-09-15 22:20:44,794 epoch 22 - iter 580/585 - loss 0.54289293 - samples/sec: 113.01 - lr: 0.100000
2020-09-15 22:20:47,410 ----------------------------------------------------------------------------------------------------
2020-09-15 22:20:47,411 EPOCH 22 done: loss 0.5436 - lr 0.1000000
2020-09-15 22:20:47,411 BAD EPOCHS (no improvement): 0
2020-09-15 22:20:47,416 ----------------------------------------------------------------------------------------------------
2020-09-15 22:21:18,762 epoch 23 - iter 58/585 - loss 0.39452579 - samples/sec: 59.23 - lr: 0.100000
2020-09-15 22:21:51,747 epoch 23 - iter 116/585 - loss 0.50506601 - samples/sec: 56.28 - lr: 0.100000
2020-09-15 22:22:23,385 epoch 23 - iter 174/585 - loss 0.48790370 - samples/sec: 58.68 - lr: 0.100000
2020-09-15 22:22:49,738 epoch 23 - iter 232/585 - loss 0.52454119 - samples/sec: 70.45 - lr: 0.100000
2020-09-15 22:23:02,960 epoch 23 - iter 290/585 - loss 0.50805791 - samples/sec: 140.46 - lr: 0.100000
2020-09-15 22:23:22,416 epoch 23 - iter 348/585 - loss 0.50670284 - samples/sec: 95.44 - lr: 0.100000
2020-09-15 22:23:55,357 epoch 23 - iter 406/585 - loss 0.53454250 - samples/sec: 56.36 - lr: 0.100000
2020-09-15 22:24:27,577 epoch 23 - iter 464/585 - loss 0.54240504 - samples/sec: 57.62 - lr: 0.100000
2020-09-15 22:24:59,065 epoch 23 - iter 522/585 - loss 0.53016211 - samples/sec: 58.96 - lr: 0.100000
2020-09-15 22:25:18,754 epoch 23 - iter 580/585 - loss 0.52461703 - samples/sec: 94.31 - lr: 0.100000
2020-09-15 22:25:19,957 ----------------------------------------------------------------------------------------------------
2020-09-15 22:25:19,957 EPOCH 23 done: loss 0.5244 - lr 0.1000000
2020-09-15 22:25:19,958 BAD EPOCHS (no improvement): 0
2020-09-15 22:25:19,962 ----------------------------------------------------------------------------------------------------
2020-09-15 22:25:33,027 epoch 24 - iter 58/585 - loss 0.45993511 - samples/sec: 142.19 - lr: 0.100000
2020-09-15 22:26:01,113 epoch 24 - iter 116/585 - loss 0.46038062 - samples/sec: 66.11 - lr: 0.100000
2020-09-15 22:26:32,963 epoch 24 - iter 174/585 - loss 0.46196454 - samples/sec: 58.29 - lr: 0.100000
2020-09-15 22:27:05,793 epoch 24 - iter 232/585 - loss 0.48762515 - samples/sec: 56.55 - lr: 0.100000
2020-09-15 22:27:38,424 epoch 24 - iter 290/585 - loss 0.47802300 - samples/sec: 56.89 - lr: 0.100000
2020-09-15 22:27:52,371 epoch 24 - iter 348/585 - loss 0.47366612 - samples/sec: 133.17 - lr: 0.100000
2020-09-15 22:28:06,962 epoch 24 - iter 406/585 - loss 0.49703034 - samples/sec: 127.28 - lr: 0.100000
2020-09-15 22:28:41,579 epoch 24 - iter 464/585 - loss 0.53744789 - samples/sec: 53.63 - lr: 0.100000
2020-09-15 22:29:13,027 epoch 24 - iter 522/585 - loss 0.52084663 - samples/sec: 59.03 - lr: 0.100000
2020-09-15 22:29:44,509 epoch 24 - iter 580/585 - loss 0.51220347 - samples/sec: 58.97 - lr: 0.100000
2020-09-15 22:29:47,089 ----------------------------------------------------------------------------------------------------
2020-09-15 22:29:47,089 EPOCH 24 done: loss 0.5113 - lr 0.1000000
2020-09-15 22:29:47,089 BAD EPOCHS (no improvement): 0
2020-09-15 22:29:47,093 ----------------------------------------------------------------------------------------------------
2020-09-15 22:30:13,650 epoch 25 - iter 58/585 - loss 0.63903937 - samples/sec: 69.92 - lr: 0.100000
2020-09-15 22:30:27,090 epoch 25 - iter 116/585 - loss 0.53657016 - samples/sec: 138.19 - lr: 0.100000
2020-09-15 22:30:48,973 epoch 25 - iter 174/585 - loss 0.59208941 - samples/sec: 84.85 - lr: 0.100000
2020-09-15 22:31:20,550 epoch 25 - iter 232/585 - loss 0.55319928 - samples/sec: 58.79 - lr: 0.100000
2020-09-15 22:31:52,185 epoch 25 - iter 290/585 - loss 0.52956202 - samples/sec: 58.69 - lr: 0.100000
2020-09-15 22:32:23,875 epoch 25 - iter 348/585 - loss 0.51267406 - samples/sec: 58.58 - lr: 0.100000
2020-09-15 22:32:43,389 epoch 25 - iter 406/585 - loss 0.50548741 - samples/sec: 95.16 - lr: 0.100000
2020-09-15 22:32:56,609 epoch 25 - iter 464/585 - loss 0.49587337 - samples/sec: 140.49 - lr: 0.100000
2020-09-15 22:33:18,504 epoch 25 - iter 522/585 - loss 0.49212417 - samples/sec: 84.80 - lr: 0.100000
2020-09-15 22:33:51,469 epoch 25 - iter 580/585 - loss 0.51027373 - samples/sec: 56.32 - lr: 0.100000
2020-09-15 22:33:53,955 ----------------------------------------------------------------------------------------------------
2020-09-15 22:33:53,955 EPOCH 25 done: loss 0.5097 - lr 0.1000000
2020-09-15 22:33:53,955 BAD EPOCHS (no improvement): 0
2020-09-15 22:33:53,960 ----------------------------------------------------------------------------------------------------
2020-09-15 22:34:26,655 epoch 26 - iter 58/585 - loss 0.50839270 - samples/sec: 56.78 - lr: 0.100000
2020-09-15 22:34:59,922 epoch 26 - iter 116/585 - loss 0.54024736 - samples/sec: 55.81 - lr: 0.100000
2020-09-15 22:35:15,458 epoch 26 - iter 174/585 - loss 0.48795531 - samples/sec: 119.54 - lr: 0.100000
2020-09-15 22:35:26,913 epoch 26 - iter 232/585 - loss 0.47364083 - samples/sec: 162.15 - lr: 0.100000
2020-09-15 22:35:55,189 epoch 26 - iter 290/585 - loss 0.46144404 - samples/sec: 65.66 - lr: 0.100000
2020-09-15 22:36:26,698 epoch 26 - iter 348/585 - loss 0.46342716 - samples/sec: 58.92 - lr: 0.100000
2020-09-15 22:36:58,322 epoch 26 - iter 406/585 - loss 0.46449751 - samples/sec: 58.70 - lr: 0.100000
2020-09-15 22:37:31,291 epoch 26 - iter 464/585 - loss 0.48776087 - samples/sec: 56.31 - lr: 0.100000
2020-09-15 22:37:45,508 epoch 26 - iter 522/585 - loss 0.48968672 - samples/sec: 130.64 - lr: 0.100000
2020-09-15 22:37:56,971 epoch 26 - iter 580/585 - loss 0.50513158 - samples/sec: 162.05 - lr: 0.100000
2020-09-15 22:37:59,573 ----------------------------------------------------------------------------------------------------
2020-09-15 22:37:59,573 EPOCH 26 done: loss 0.5050 - lr 0.1000000
2020-09-15 22:37:59,573 BAD EPOCHS (no improvement): 0
2020-09-15 22:37:59,578 ----------------------------------------------------------------------------------------------------
2020-09-15 22:38:31,385 epoch 27 - iter 58/585 - loss 0.41967044 - samples/sec: 58.38 - lr: 0.100000
2020-09-15 22:39:03,417 epoch 27 - iter 116/585 - loss 0.43442010 - samples/sec: 57.96 - lr: 0.100000
2020-09-15 22:39:37,106 epoch 27 - iter 174/585 - loss 0.51582262 - samples/sec: 55.11 - lr: 0.100000
2020-09-15 22:40:06,746 epoch 27 - iter 232/585 - loss 0.52844617 - samples/sec: 62.64 - lr: 0.100000
2020-09-15 22:40:19,963 epoch 27 - iter 290/585 - loss 0.50875199 - samples/sec: 140.53 - lr: 0.100000
2020-09-15 22:40:39,274 epoch 27 - iter 348/585 - loss 0.51040041 - samples/sec: 96.16 - lr: 0.100000
2020-09-15 22:41:10,878 epoch 27 - iter 406/585 - loss 0.49510471 - samples/sec: 58.74 - lr: 0.100000
2020-09-15 22:41:43,139 epoch 27 - iter 464/585 - loss 0.50303415 - samples/sec: 57.55 - lr: 0.100000
2020-09-15 22:42:14,737 epoch 27 - iter 522/585 - loss 0.49613414 - samples/sec: 58.75 - lr: 0.100000
2020-09-15 22:42:36,831 epoch 27 - iter 580/585 - loss 0.48951363 - samples/sec: 84.04 - lr: 0.100000
2020-09-15 22:42:37,495 ----------------------------------------------------------------------------------------------------
2020-09-15 22:42:37,495 EPOCH 27 done: loss 0.4895 - lr 0.1000000
2020-09-15 22:42:37,495 BAD EPOCHS (no improvement): 0
2020-09-15 22:42:37,498 ----------------------------------------------------------------------------------------------------
2020-09-15 22:42:51,364 epoch 28 - iter 58/585 - loss 0.42863249 - samples/sec: 133.96 - lr: 0.100000
2020-09-15 22:43:18,628 epoch 28 - iter 116/585 - loss 0.41738520 - samples/sec: 68.10 - lr: 0.100000
2020-09-15 22:43:50,097 epoch 28 - iter 174/585 - loss 0.40873860 - samples/sec: 59.00 - lr: 0.100000
2020-09-15 22:44:21,672 epoch 28 - iter 232/585 - loss 0.41477225 - samples/sec: 58.80 - lr: 0.100000
2020-09-15 22:44:53,308 epoch 28 - iter 290/585 - loss 0.42763725 - samples/sec: 58.68 - lr: 0.100000
2020-09-15 22:45:11,774 epoch 28 - iter 348/585 - loss 0.48906164 - samples/sec: 100.56 - lr: 0.100000
2020-09-15 22:45:23,838 epoch 28 - iter 406/585 - loss 0.47988769 - samples/sec: 153.96 - lr: 0.100000
2020-09-15 22:45:55,415 epoch 28 - iter 464/585 - loss 0.47614820 - samples/sec: 58.79 - lr: 0.100000
2020-09-15 22:46:29,096 epoch 28 - iter 522/585 - loss 0.50398492 - samples/sec: 55.12 - lr: 0.100000
2020-09-15 22:47:00,665 epoch 28 - iter 580/585 - loss 0.49418469 - samples/sec: 58.81 - lr: 0.100000
2020-09-15 22:47:03,252 ----------------------------------------------------------------------------------------------------
2020-09-15 22:47:03,252 EPOCH 28 done: loss 0.4928 - lr 0.1000000
2020-09-15 22:47:03,252 BAD EPOCHS (no improvement): 1
2020-09-15 22:47:03,260 ----------------------------------------------------------------------------------------------------
2020-09-15 22:47:31,443 epoch 29 - iter 58/585 - loss 0.39889928 - samples/sec: 65.89 - lr: 0.100000
2020-09-15 22:47:44,772 epoch 29 - iter 116/585 - loss 0.41153606 - samples/sec: 139.34 - lr: 0.100000
2020-09-15 22:48:01,421 epoch 29 - iter 174/585 - loss 0.40447009 - samples/sec: 111.55 - lr: 0.100000
2020-09-15 22:48:35,106 epoch 29 - iter 232/585 - loss 0.45036368 - samples/sec: 55.11 - lr: 0.100000
2020-09-15 22:49:06,535 epoch 29 - iter 290/585 - loss 0.44205445 - samples/sec: 59.07 - lr: 0.100000
2020-09-15 22:49:38,091 epoch 29 - iter 348/585 - loss 0.43578058 - samples/sec: 58.83 - lr: 0.100000
2020-09-15 22:50:01,307 epoch 29 - iter 406/585 - loss 0.45029898 - samples/sec: 79.98 - lr: 0.100000
2020-09-15 22:50:14,686 epoch 29 - iter 464/585 - loss 0.44512289 - samples/sec: 138.81 - lr: 0.100000
2020-09-15 22:50:21,921 epoch 29 - iter 522/585 - loss 0.46890655 - samples/sec: 256.92 - lr: 0.100000
2020-09-15 22:50:29,054 epoch 29 - iter 580/585 - loss 0.47740721 - samples/sec: 260.55 - lr: 0.100000
2020-09-15 22:50:29,578 ----------------------------------------------------------------------------------------------------
2020-09-15 22:50:29,579 EPOCH 29 done: loss 0.4782 - lr 0.1000000
2020-09-15 22:50:29,579 BAD EPOCHS (no improvement): 0
2020-09-15 22:50:29,583 ----------------------------------------------------------------------------------------------------
2020-09-15 22:50:36,953 epoch 30 - iter 58/585 - loss 0.35469078 - samples/sec: 252.24 - lr: 0.100000
2020-09-15 22:50:44,927 epoch 30 - iter 116/585 - loss 0.44184479 - samples/sec: 233.09 - lr: 0.100000
2020-09-15 22:50:51,973 epoch 30 - iter 174/585 - loss 0.43712438 - samples/sec: 263.81 - lr: 0.100000
2020-09-15 22:50:59,136 epoch 30 - iter 232/585 - loss 0.43574265 - samples/sec: 259.49 - lr: 0.100000
2020-09-15 22:51:07,219 epoch 30 - iter 290/585 - loss 0.47355421 - samples/sec: 229.93 - lr: 0.100000
2020-09-15 22:51:14,425 epoch 30 - iter 348/585 - loss 0.46536354 - samples/sec: 257.95 - lr: 0.100000
2020-09-15 22:51:22,294 epoch 30 - iter 406/585 - loss 0.47752973 - samples/sec: 236.15 - lr: 0.100000
2020-09-15 22:51:33,169 epoch 30 - iter 464/585 - loss 0.47354859 - samples/sec: 170.80 - lr: 0.100000
2020-09-15 22:51:54,381 epoch 30 - iter 522/585 - loss 0.47607791 - samples/sec: 87.53 - lr: 0.100000
2020-09-15 22:52:15,856 epoch 30 - iter 580/585 - loss 0.47029812 - samples/sec: 86.46 - lr: 0.100000
2020-09-15 22:52:17,360 ----------------------------------------------------------------------------------------------------
2020-09-15 22:52:17,361 EPOCH 30 done: loss 0.4696 - lr 0.1000000
2020-09-15 22:52:17,361 BAD EPOCHS (no improvement): 0
2020-09-15 22:52:17,368 ----------------------------------------------------------------------------------------------------
2020-09-15 22:52:38,805 epoch 31 - iter 58/585 - loss 0.54375496 - samples/sec: 86.62 - lr: 0.100000
2020-09-15 22:52:59,296 epoch 31 - iter 116/585 - loss 0.46184476 - samples/sec: 90.61 - lr: 0.100000
2020-09-15 22:53:16,926 epoch 31 - iter 174/585 - loss 0.43354908 - samples/sec: 105.33 - lr: 0.100000
2020-09-15 22:53:24,347 epoch 31 - iter 232/585 - loss 0.42760602 - samples/sec: 250.38 - lr: 0.100000
2020-09-15 22:53:38,370 epoch 31 - iter 290/585 - loss 0.43601602 - samples/sec: 132.39 - lr: 0.100000
2020-09-15 22:54:00,448 epoch 31 - iter 348/585 - loss 0.45790263 - samples/sec: 84.08 - lr: 0.100000
2020-09-15 22:54:20,407 epoch 31 - iter 406/585 - loss 0.45281033 - samples/sec: 93.01 - lr: 0.100000
2020-09-15 22:54:40,755 epoch 31 - iter 464/585 - loss 0.44911641 - samples/sec: 91.24 - lr: 0.100000
2020-09-15 22:55:01,091 epoch 31 - iter 522/585 - loss 0.44446238 - samples/sec: 91.29 - lr: 0.100000
2020-09-15 22:55:17,893 epoch 31 - iter 580/585 - loss 0.46607868 - samples/sec: 110.50 - lr: 0.100000
2020-09-15 22:55:18,282 ----------------------------------------------------------------------------------------------------
2020-09-15 22:55:18,282 EPOCH 31 done: loss 0.4650 - lr 0.1000000
2020-09-15 22:55:18,282 BAD EPOCHS (no improvement): 0
2020-09-15 22:55:18,285 ----------------------------------------------------------------------------------------------------
2020-09-15 22:55:24,846 epoch 32 - iter 58/585 - loss 0.42701056 - samples/sec: 283.14 - lr: 0.100000
2020-09-15 22:55:37,136 epoch 32 - iter 116/585 - loss 0.42418850 - samples/sec: 151.07 - lr: 0.100000
2020-09-15 22:55:57,087 epoch 32 - iter 174/585 - loss 0.43853766 - samples/sec: 93.05 - lr: 0.100000
2020-09-15 22:56:17,534 epoch 32 - iter 232/585 - loss 0.43843944 - samples/sec: 90.79 - lr: 0.100000
2020-09-15 22:56:39,902 epoch 32 - iter 290/585 - loss 0.52009508 - samples/sec: 82.99 - lr: 0.100000
2020-09-15 22:56:59,356 epoch 32 - iter 348/585 - loss 0.50352956 - samples/sec: 95.43 - lr: 0.100000
2020-09-15 22:57:17,375 epoch 32 - iter 406/585 - loss 0.49237383 - samples/sec: 103.04 - lr: 0.100000
2020-09-15 22:57:23,917 epoch 32 - iter 464/585 - loss 0.48113615 - samples/sec: 283.87 - lr: 0.100000
2020-09-15 22:57:32,203 epoch 32 - iter 522/585 - loss 0.48704936 - samples/sec: 224.11 - lr: 0.100000
2020-09-15 22:57:52,348 epoch 32 - iter 580/585 - loss 0.48018946 - samples/sec: 92.15 - lr: 0.100000
2020-09-15 22:57:53,987 ----------------------------------------------------------------------------------------------------
2020-09-15 22:57:53,987 EPOCH 32 done: loss 0.4794 - lr 0.1000000
2020-09-15 22:57:53,987 BAD EPOCHS (no improvement): 1
2020-09-15 22:57:53,990 ----------------------------------------------------------------------------------------------------
2020-09-15 22:58:14,000 epoch 33 - iter 58/585 - loss 0.39580041 - samples/sec: 92.78 - lr: 0.100000
2020-09-15 22:58:34,182 epoch 33 - iter 116/585 - loss 0.40376635 - samples/sec: 91.98 - lr: 0.100000
2020-09-15 22:58:55,997 epoch 33 - iter 174/585 - loss 0.48203747 - samples/sec: 85.10 - lr: 0.100000
2020-09-15 22:59:15,970 epoch 33 - iter 232/585 - loss 0.45036311 - samples/sec: 92.95 - lr: 0.100000
2020-09-15 22:59:23,361 epoch 33 - iter 290/585 - loss 0.43523380 - samples/sec: 251.27 - lr: 0.100000
2020-09-15 22:59:29,060 epoch 33 - iter 348/585 - loss 0.42967785 - samples/sec: 325.90 - lr: 0.100000
2020-09-15 22:59:47,704 epoch 33 - iter 406/585 - loss 0.42551288 - samples/sec: 99.57 - lr: 0.100000
2020-09-15 23:00:07,229 epoch 33 - iter 464/585 - loss 0.42713046 - samples/sec: 95.08 - lr: 0.100000
2020-09-15 23:00:27,476 epoch 33 - iter 522/585 - loss 0.42209239 - samples/sec: 91.69 - lr: 0.100000
2020-09-15 23:00:50,363 epoch 33 - iter 580/585 - loss 0.46292849 - samples/sec: 81.11 - lr: 0.100000
2020-09-15 23:00:51,978 ----------------------------------------------------------------------------------------------------
2020-09-15 23:00:51,978 EPOCH 33 done: loss 0.4615 - lr 0.1000000
2020-09-15 23:00:51,978 BAD EPOCHS (no improvement): 0
2020-09-15 23:00:51,993 ----------------------------------------------------------------------------------------------------
2020-09-15 23:01:11,587 epoch 34 - iter 58/585 - loss 0.40034909 - samples/sec: 94.75 - lr: 0.100000
2020-09-15 23:01:22,724 epoch 34 - iter 116/585 - loss 0.46558189 - samples/sec: 166.71 - lr: 0.100000
2020-09-15 23:01:29,398 epoch 34 - iter 174/585 - loss 0.44583996 - samples/sec: 278.29 - lr: 0.100000
2020-09-15 23:01:48,274 epoch 34 - iter 232/585 - loss 0.43479791 - samples/sec: 98.35 - lr: 0.100000
2020-09-15 23:02:06,679 epoch 34 - iter 290/585 - loss 0.43566151 - samples/sec: 100.87 - lr: 0.100000
2020-09-15 23:02:20,584 epoch 34 - iter 348/585 - loss 0.43151453 - samples/sec: 133.51 - lr: 0.100000
2020-09-15 23:02:40,772 epoch 34 - iter 406/585 - loss 0.42335862 - samples/sec: 91.96 - lr: 0.100000
2020-09-15 23:03:01,413 epoch 34 - iter 464/585 - loss 0.41758118 - samples/sec: 89.94 - lr: 0.100000
2020-09-15 23:03:20,743 epoch 34 - iter 522/585 - loss 0.43442053 - samples/sec: 96.04 - lr: 0.100000
2020-09-15 23:03:29,127 epoch 34 - iter 580/585 - loss 0.45577895 - samples/sec: 221.50 - lr: 0.100000
2020-09-15 23:03:29,502 ----------------------------------------------------------------------------------------------------
2020-09-15 23:03:29,502 EPOCH 34 done: loss 0.4567 - lr 0.1000000
2020-09-15 23:03:29,502 BAD EPOCHS (no improvement): 0
2020-09-15 23:03:29,505 ----------------------------------------------------------------------------------------------------
2020-09-15 23:03:40,849 epoch 35 - iter 58/585 - loss 0.39018683 - samples/sec: 163.69 - lr: 0.100000
2020-09-15 23:04:01,794 epoch 35 - iter 116/585 - loss 0.46021428 - samples/sec: 88.63 - lr: 0.100000
2020-09-15 23:04:21,547 epoch 35 - iter 174/585 - loss 0.44596164 - samples/sec: 93.98 - lr: 0.100000
2020-09-15 23:04:41,925 epoch 35 - iter 232/585 - loss 0.45568175 - samples/sec: 91.10 - lr: 0.100000
2020-09-15 23:05:01,478 epoch 35 - iter 290/585 - loss 0.44288276 - samples/sec: 94.94 - lr: 0.100000
2020-09-15 23:05:22,161 epoch 35 - iter 348/585 - loss 0.47375508 - samples/sec: 89.75 - lr: 0.100000
2020-09-15 23:05:28,756 epoch 35 - iter 406/585 - loss 0.45879265 - samples/sec: 281.64 - lr: 0.100000
2020-09-15 23:05:37,028 epoch 35 - iter 464/585 - loss 0.46678093 - samples/sec: 224.48 - lr: 0.100000
2020-09-15 23:05:57,693 epoch 35 - iter 522/585 - loss 0.45594774 - samples/sec: 89.83 - lr: 0.100000
2020-09-15 23:06:17,965 epoch 35 - iter 580/585 - loss 0.45132401 - samples/sec: 91.58 - lr: 0.100000
2020-09-15 23:06:19,508 ----------------------------------------------------------------------------------------------------
2020-09-15 23:06:19,508 EPOCH 35 done: loss 0.4520 - lr 0.1000000
2020-09-15 23:06:19,508 BAD EPOCHS (no improvement): 0
2020-09-15 23:06:19,511 ----------------------------------------------------------------------------------------------------
2020-09-15 23:06:39,729 epoch 36 - iter 58/585 - loss 0.35052240 - samples/sec: 91.83 - lr: 0.100000
2020-09-15 23:07:01,398 epoch 36 - iter 116/585 - loss 0.51395455 - samples/sec: 85.67 - lr: 0.100000
2020-09-15 23:07:21,738 epoch 36 - iter 174/585 - loss 0.48053762 - samples/sec: 91.27 - lr: 0.100000
2020-09-15 23:07:27,641 epoch 36 - iter 232/585 - loss 0.45333263 - samples/sec: 314.65 - lr: 0.100000
2020-09-15 23:07:36,401 epoch 36 - iter 290/585 - loss 0.48405630 - samples/sec: 211.95 - lr: 0.100000
2020-09-15 23:07:56,914 epoch 36 - iter 348/585 - loss 0.48489888 - samples/sec: 90.50 - lr: 0.100000
2020-09-15 23:08:17,160 epoch 36 - iter 406/585 - loss 0.47005592 - samples/sec: 91.69 - lr: 0.100000
2020-09-15 23:08:37,750 epoch 36 - iter 464/585 - loss 0.46195544 - samples/sec: 90.16 - lr: 0.100000
2020-09-15 23:08:57,904 epoch 36 - iter 522/585 - loss 0.45489023 - samples/sec: 92.12 - lr: 0.100000
2020-09-15 23:09:18,518 epoch 36 - iter 580/585 - loss 0.44458329 - samples/sec: 90.05 - lr: 0.100000
2020-09-15 23:09:20,026 ----------------------------------------------------------------------------------------------------
2020-09-15 23:09:20,026 EPOCH 36 done: loss 0.4438 - lr 0.1000000
2020-09-15 23:09:20,026 BAD EPOCHS (no improvement): 0
2020-09-15 23:09:20,029 ----------------------------------------------------------------------------------------------------
2020-09-15 23:09:26,870 epoch 37 - iter 58/585 - loss 0.32273317 - samples/sec: 271.51 - lr: 0.100000
2020-09-15 23:09:33,247 epoch 37 - iter 116/585 - loss 0.32767517 - samples/sec: 291.23 - lr: 0.100000
2020-09-15 23:09:56,055 epoch 37 - iter 174/585 - loss 0.45862579 - samples/sec: 81.39 - lr: 0.100000
2020-09-15 23:10:16,192 epoch 37 - iter 232/585 - loss 0.44713983 - samples/sec: 92.19 - lr: 0.100000
2020-09-15 23:10:36,830 epoch 37 - iter 290/585 - loss 0.42620973 - samples/sec: 89.95 - lr: 0.100000
2020-09-15 23:10:56,418 epoch 37 - iter 348/585 - loss 0.42182861 - samples/sec: 94.77 - lr: 0.100000
2020-09-15 23:11:16,775 epoch 37 - iter 406/585 - loss 0.41016055 - samples/sec: 91.20 - lr: 0.100000
2020-09-15 23:11:25,806 epoch 37 - iter 464/585 - loss 0.42317445 - samples/sec: 205.59 - lr: 0.100000
2020-09-15 23:11:33,319 epoch 37 - iter 522/585 - loss 0.43448545 - samples/sec: 247.20 - lr: 0.100000
2020-09-15 23:11:53,413 epoch 37 - iter 580/585 - loss 0.43086908 - samples/sec: 92.39 - lr: 0.100000
2020-09-15 23:11:54,958 ----------------------------------------------------------------------------------------------------
2020-09-15 23:11:54,958 EPOCH 37 done: loss 0.4291 - lr 0.1000000
2020-09-15 23:11:54,958 BAD EPOCHS (no improvement): 0
2020-09-15 23:11:54,961 ----------------------------------------------------------------------------------------------------
2020-09-15 23:12:17,569 epoch 38 - iter 58/585 - loss 0.74049321 - samples/sec: 82.12 - lr: 0.100000
2020-09-15 23:12:38,047 epoch 38 - iter 116/585 - loss 0.55590626 - samples/sec: 90.65 - lr: 0.100000
2020-09-15 23:12:58,695 epoch 38 - iter 174/585 - loss 0.52336379 - samples/sec: 89.91 - lr: 0.100000
2020-09-15 23:13:20,139 epoch 38 - iter 232/585 - loss 0.53013110 - samples/sec: 86.57 - lr: 0.100000
2020-09-15 23:13:26,980 epoch 38 - iter 290/585 - loss 0.49223766 - samples/sec: 271.48 - lr: 0.100000
2020-09-15 23:13:32,859 epoch 38 - iter 348/585 - loss 0.47510026 - samples/sec: 315.93 - lr: 0.100000
2020-09-15 23:13:51,388 epoch 38 - iter 406/585 - loss 0.46202741 - samples/sec: 100.19 - lr: 0.100000
2020-09-15 23:14:10,695 epoch 38 - iter 464/585 - loss 0.45142682 - samples/sec: 96.16 - lr: 0.100000
2020-09-15 23:14:30,563 epoch 38 - iter 522/585 - loss 0.43916612 - samples/sec: 93.44 - lr: 0.100000
2020-09-15 23:14:50,914 epoch 38 - iter 580/585 - loss 0.43878313 - samples/sec: 91.22 - lr: 0.100000
2020-09-15 23:14:52,493 ----------------------------------------------------------------------------------------------------
2020-09-15 23:14:52,494 EPOCH 38 done: loss 0.4388 - lr 0.1000000
2020-09-15 23:14:52,494 BAD EPOCHS (no improvement): 1
2020-09-15 23:14:52,497 ----------------------------------------------------------------------------------------------------
2020-09-15 23:15:12,888 epoch 39 - iter 58/585 - loss 0.52710337 - samples/sec: 91.04 - lr: 0.100000
2020-09-15 23:15:24,829 epoch 39 - iter 116/585 - loss 0.45580352 - samples/sec: 155.50 - lr: 0.100000
2020-09-15 23:15:31,724 epoch 39 - iter 174/585 - loss 0.43601412 - samples/sec: 269.32 - lr: 0.100000
2020-09-15 23:15:46,181 epoch 39 - iter 232/585 - loss 0.47970859 - samples/sec: 128.42 - lr: 0.100000
2020-09-15 23:16:06,498 epoch 39 - iter 290/585 - loss 0.45476909 - samples/sec: 91.37 - lr: 0.100000
2020-09-15 23:16:26,141 epoch 39 - iter 348/585 - loss 0.44208202 - samples/sec: 94.51 - lr: 0.100000
2020-09-15 23:16:45,745 epoch 39 - iter 406/585 - loss 0.42745432 - samples/sec: 94.70 - lr: 0.100000
2020-09-15 23:17:07,527 epoch 39 - iter 464/585 - loss 0.45190877 - samples/sec: 85.22 - lr: 0.100000
2020-09-15 23:17:24,072 epoch 39 - iter 522/585 - loss 0.44223277 - samples/sec: 112.22 - lr: 0.100000
2020-09-15 23:17:30,706 epoch 39 - iter 580/585 - loss 0.43190614 - samples/sec: 279.93 - lr: 0.100000
2020-09-15 23:17:31,151 ----------------------------------------------------------------------------------------------------
2020-09-15 23:17:31,151 EPOCH 39 done: loss 0.4312 - lr 0.1000000
2020-09-15 23:17:31,151 BAD EPOCHS (no improvement): 2
2020-09-15 23:17:31,154 ----------------------------------------------------------------------------------------------------
2020-09-15 23:17:40,199 epoch 40 - iter 58/585 - loss 0.37689168 - samples/sec: 205.34 - lr: 0.100000
2020-09-15 23:18:00,364 epoch 40 - iter 116/585 - loss 0.36353662 - samples/sec: 92.06 - lr: 0.100000
2020-09-15 23:18:21,303 epoch 40 - iter 174/585 - loss 0.43904933 - samples/sec: 88.66 - lr: 0.100000
2020-09-15 23:18:42,639 epoch 40 - iter 232/585 - loss 0.46551462 - samples/sec: 87.01 - lr: 0.100000
2020-09-15 23:19:02,546 epoch 40 - iter 290/585 - loss 0.43682852 - samples/sec: 93.25 - lr: 0.100000
2020-09-15 23:19:22,657 epoch 40 - iter 348/585 - loss 0.42184692 - samples/sec: 92.31 - lr: 0.100000
2020-09-15 23:19:30,017 epoch 40 - iter 406/585 - loss 0.41258215 - samples/sec: 252.36 - lr: 0.100000
2020-09-15 23:19:43,287 epoch 40 - iter 464/585 - loss 0.41542257 - samples/sec: 139.96 - lr: 0.100000
2020-09-15 23:20:04,315 epoch 40 - iter 522/585 - loss 0.42310341 - samples/sec: 88.30 - lr: 0.100000
2020-09-15 23:20:24,480 epoch 40 - iter 580/585 - loss 0.41569860 - samples/sec: 92.08 - lr: 0.100000
2020-09-15 23:20:26,132 ----------------------------------------------------------------------------------------------------
2020-09-15 23:20:26,132 EPOCH 40 done: loss 0.4145 - lr 0.1000000
2020-09-15 23:20:26,132 BAD EPOCHS (no improvement): 0
2020-09-15 23:20:26,136 ----------------------------------------------------------------------------------------------------
2020-09-15 23:20:47,355 epoch 41 - iter 58/585 - loss 0.41051254 - samples/sec: 87.51 - lr: 0.100000
2020-09-15 23:21:07,599 epoch 41 - iter 116/585 - loss 0.39175524 - samples/sec: 91.71 - lr: 0.100000
2020-09-15 23:21:25,521 epoch 41 - iter 174/585 - loss 0.38645109 - samples/sec: 103.61 - lr: 0.100000
2020-09-15 23:21:33,592 epoch 41 - iter 232/585 - loss 0.38047679 - samples/sec: 230.26 - lr: 0.100000
2020-09-15 23:21:50,364 epoch 41 - iter 290/585 - loss 0.47453107 - samples/sec: 110.72 - lr: 0.100000
2020-09-15 23:22:10,353 epoch 41 - iter 348/585 - loss 0.46008038 - samples/sec: 92.88 - lr: 0.100000
2020-09-15 23:22:31,649 epoch 41 - iter 406/585 - loss 0.46240738 - samples/sec: 87.19 - lr: 0.100000
2020-09-15 23:22:52,235 epoch 41 - iter 464/585 - loss 0.44681566 - samples/sec: 90.19 - lr: 0.100000
2020-09-15 23:23:12,251 epoch 41 - iter 522/585 - loss 0.43410248 - samples/sec: 92.76 - lr: 0.100000
2020-09-15 23:23:28,192 epoch 41 - iter 580/585 - loss 0.42753247 - samples/sec: 116.50 - lr: 0.100000
2020-09-15 23:23:28,783 ----------------------------------------------------------------------------------------------------
2020-09-15 23:23:28,783 EPOCH 41 done: loss 0.4272 - lr 0.1000000
2020-09-15 23:23:28,783 BAD EPOCHS (no improvement): 1
2020-09-15 23:23:28,787 ----------------------------------------------------------------------------------------------------
2020-09-15 23:23:37,066 epoch 42 - iter 58/585 - loss 0.38380862 - samples/sec: 224.49 - lr: 0.100000
2020-09-15 23:23:56,793 epoch 42 - iter 116/585 - loss 0.49382837 - samples/sec: 94.12 - lr: 0.100000
2020-09-15 23:24:17,830 epoch 42 - iter 174/585 - loss 0.47390567 - samples/sec: 88.26 - lr: 0.100000
2020-09-15 23:24:38,126 epoch 42 - iter 232/585 - loss 0.44883482 - samples/sec: 91.47 - lr: 0.100000
2020-09-15 23:24:59,293 epoch 42 - iter 290/585 - loss 0.45981757 - samples/sec: 87.72 - lr: 0.100000
2020-09-15 23:25:19,687 epoch 42 - iter 348/585 - loss 0.43658136 - samples/sec: 91.04 - lr: 0.100000
2020-09-15 23:25:31,371 epoch 42 - iter 406/585 - loss 0.42845734 - samples/sec: 158.97 - lr: 0.100000
2020-09-15 23:25:41,565 epoch 42 - iter 464/585 - loss 0.42426771 - samples/sec: 182.26 - lr: 0.100000
2020-09-15 23:26:01,960 epoch 42 - iter 522/585 - loss 0.41903285 - samples/sec: 91.04 - lr: 0.100000
2020-09-15 23:26:23,119 epoch 42 - iter 580/585 - loss 0.42387448 - samples/sec: 87.75 - lr: 0.100000
2020-09-15 23:26:24,881 ----------------------------------------------------------------------------------------------------
2020-09-15 23:26:24,881 EPOCH 42 done: loss 0.4235 - lr 0.1000000
2020-09-15 23:26:24,881 BAD EPOCHS (no improvement): 2
2020-09-15 23:26:24,884 ----------------------------------------------------------------------------------------------------
2020-09-15 23:26:45,996 epoch 43 - iter 58/585 - loss 0.47316877 - samples/sec: 87.95 - lr: 0.100000
2020-09-15 23:27:06,289 epoch 43 - iter 116/585 - loss 0.39846222 - samples/sec: 91.50 - lr: 0.100000
2020-09-15 23:27:26,674 epoch 43 - iter 174/585 - loss 0.38509805 - samples/sec: 91.08 - lr: 0.100000
2020-09-15 23:27:35,324 epoch 43 - iter 232/585 - loss 0.38564660 - samples/sec: 214.83 - lr: 0.100000
2020-09-15 23:27:47,868 epoch 43 - iter 290/585 - loss 0.37588637 - samples/sec: 148.06 - lr: 0.100000
2020-09-15 23:28:08,944 epoch 43 - iter 348/585 - loss 0.40528545 - samples/sec: 88.10 - lr: 0.100000
2020-09-15 23:28:28,945 epoch 43 - iter 406/585 - loss 0.38921094 - samples/sec: 92.83 - lr: 0.100000
2020-09-15 23:28:49,764 epoch 43 - iter 464/585 - loss 0.39353122 - samples/sec: 89.18 - lr: 0.100000
2020-09-15 23:29:10,444 epoch 43 - iter 522/585 - loss 0.38871662 - samples/sec: 89.78 - lr: 0.100000
2020-09-15 23:29:29,332 epoch 43 - iter 580/585 - loss 0.38566465 - samples/sec: 98.31 - lr: 0.100000
2020-09-15 23:29:30,605 ----------------------------------------------------------------------------------------------------
2020-09-15 23:29:30,605 EPOCH 43 done: loss 0.4055 - lr 0.1000000
2020-09-15 23:29:30,606 BAD EPOCHS (no improvement): 0
2020-09-15 23:29:30,609 ----------------------------------------------------------------------------------------------------
2020-09-15 23:29:39,048 epoch 44 - iter 58/585 - loss 0.31176363 - samples/sec: 220.36 - lr: 0.100000
2020-09-15 23:29:56,711 epoch 44 - iter 116/585 - loss 0.33578401 - samples/sec: 105.13 - lr: 0.100000
2020-09-15 23:30:17,519 epoch 44 - iter 174/585 - loss 0.37004887 - samples/sec: 89.23 - lr: 0.100000
2020-09-15 23:30:36,452 epoch 44 - iter 232/585 - loss 0.37630659 - samples/sec: 98.08 - lr: 0.100000
2020-09-15 23:30:57,253 epoch 44 - iter 290/585 - loss 0.39185993 - samples/sec: 89.26 - lr: 0.100000
2020-09-15 23:31:18,379 epoch 44 - iter 348/585 - loss 0.42455288 - samples/sec: 87.89 - lr: 0.100000
2020-09-15 23:31:33,335 epoch 44 - iter 406/585 - loss 0.40909212 - samples/sec: 124.18 - lr: 0.100000
2020-09-15 23:31:41,512 epoch 44 - iter 464/585 - loss 0.39846369 - samples/sec: 227.24 - lr: 0.100000
2020-09-15 23:32:02,087 epoch 44 - iter 522/585 - loss 0.42237304 - samples/sec: 90.24 - lr: 0.100000
2020-09-15 23:32:22,681 epoch 44 - iter 580/585 - loss 0.41642339 - samples/sec: 90.16 - lr: 0.100000
2020-09-15 23:32:24,153 ----------------------------------------------------------------------------------------------------
2020-09-15 23:32:24,153 EPOCH 44 done: loss 0.4154 - lr 0.1000000
2020-09-15 23:32:24,153 BAD EPOCHS (no improvement): 1
2020-09-15 23:32:24,159 ----------------------------------------------------------------------------------------------------
2020-09-15 23:32:46,985 epoch 45 - iter 58/585 - loss 0.32365879 - samples/sec: 81.35 - lr: 0.100000
2020-09-15 23:33:08,723 epoch 45 - iter 116/585 - loss 0.43562228 - samples/sec: 85.41 - lr: 0.100000
2020-09-15 23:33:30,540 epoch 45 - iter 174/585 - loss 0.50212709 - samples/sec: 85.10 - lr: 0.100000
2020-09-15 23:33:38,922 epoch 45 - iter 232/585 - loss 0.45697858 - samples/sec: 221.72 - lr: 0.100000
2020-09-15 23:33:53,203 epoch 45 - iter 290/585 - loss 0.43364836 - samples/sec: 130.03 - lr: 0.100000
2020-09-15 23:34:13,474 epoch 45 - iter 348/585 - loss 0.41509541 - samples/sec: 91.60 - lr: 0.100000
2020-09-15 23:34:34,351 epoch 45 - iter 406/585 - loss 0.41366256 - samples/sec: 88.94 - lr: 0.100000
2020-09-15 23:34:55,036 epoch 45 - iter 464/585 - loss 0.40740617 - samples/sec: 89.76 - lr: 0.100000
2020-09-15 23:35:16,873 epoch 45 - iter 522/585 - loss 0.41140157 - samples/sec: 85.02 - lr: 0.100000
2020-09-15 23:35:32,876 epoch 45 - iter 580/585 - loss 0.40418490 - samples/sec: 116.04 - lr: 0.100000
2020-09-15 23:35:33,537 ----------------------------------------------------------------------------------------------------
2020-09-15 23:35:33,537 EPOCH 45 done: loss 0.4048 - lr 0.1000000
2020-09-15 23:35:33,537 BAD EPOCHS (no improvement): 0
2020-09-15 23:35:33,541 ----------------------------------------------------------------------------------------------------
2020-09-15 23:35:41,710 epoch 46 - iter 58/585 - loss 0.35249818 - samples/sec: 227.55 - lr: 0.100000
2020-09-15 23:36:00,932 epoch 46 - iter 116/585 - loss 0.33706160 - samples/sec: 96.60 - lr: 0.100000
2020-09-15 23:36:21,394 epoch 46 - iter 174/585 - loss 0.33933817 - samples/sec: 90.74 - lr: 0.100000
2020-09-15 23:36:43,410 epoch 46 - iter 232/585 - loss 0.40172608 - samples/sec: 84.34 - lr: 0.100000
2020-09-15 23:37:04,128 epoch 46 - iter 290/585 - loss 0.39202913 - samples/sec: 89.62 - lr: 0.100000
2020-09-15 23:37:25,880 epoch 46 - iter 348/585 - loss 0.40890763 - samples/sec: 85.36 - lr: 0.100000
2020-09-15 23:37:36,678 epoch 46 - iter 406/585 - loss 0.40004694 - samples/sec: 172.03 - lr: 0.100000
2020-09-15 23:37:48,845 epoch 46 - iter 464/585 - loss 0.42236449 - samples/sec: 152.66 - lr: 0.100000
2020-09-15 23:38:09,877 epoch 46 - iter 522/585 - loss 0.41482313 - samples/sec: 88.28 - lr: 0.100000
2020-09-15 23:38:30,560 epoch 46 - iter 580/585 - loss 0.40460538 - samples/sec: 89.77 - lr: 0.100000
2020-09-15 23:38:32,281 ----------------------------------------------------------------------------------------------------
2020-09-15 23:38:32,281 EPOCH 46 done: loss 0.4048 - lr 0.1000000
2020-09-15 23:38:32,282 BAD EPOCHS (no improvement): 1
2020-09-15 23:38:32,285 ----------------------------------------------------------------------------------------------------
2020-09-15 23:38:52,612 epoch 47 - iter 58/585 - loss 0.32486529 - samples/sec: 91.35 - lr: 0.100000
2020-09-15 23:39:13,544 epoch 47 - iter 116/585 - loss 0.32534004 - samples/sec: 88.70 - lr: 0.100000
2020-09-15 23:39:32,292 epoch 47 - iter 174/585 - loss 0.32782917 - samples/sec: 99.04 - lr: 0.100000
2020-09-15 23:39:40,390 epoch 47 - iter 232/585 - loss 0.33946494 - samples/sec: 229.47 - lr: 0.100000
2020-09-15 23:39:55,124 epoch 47 - iter 290/585 - loss 0.35679570 - samples/sec: 126.04 - lr: 0.100000
2020-09-15 23:40:15,406 epoch 47 - iter 348/585 - loss 0.34490090 - samples/sec: 91.55 - lr: 0.100000
2020-09-15 23:40:36,309 epoch 47 - iter 406/585 - loss 0.35893918 - samples/sec: 88.82 - lr: 0.100000
2020-09-15 23:40:57,728 epoch 47 - iter 464/585 - loss 0.38225452 - samples/sec: 86.68 - lr: 0.100000
2020-09-15 23:41:19,579 epoch 47 - iter 522/585 - loss 0.40220773 - samples/sec: 84.97 - lr: 0.100000
2020-09-15 23:41:35,104 epoch 47 - iter 580/585 - loss 0.39783890 - samples/sec: 119.62 - lr: 0.100000
2020-09-15 23:41:35,613 ----------------------------------------------------------------------------------------------------
2020-09-15 23:41:35,613 EPOCH 47 done: loss 0.3990 - lr 0.1000000
2020-09-15 23:41:35,613 BAD EPOCHS (no improvement): 0
2020-09-15 23:41:35,617 ----------------------------------------------------------------------------------------------------
2020-09-15 23:41:44,450 epoch 48 - iter 58/585 - loss 0.50747638 - samples/sec: 210.45 - lr: 0.100000
2020-09-15 23:42:05,210 epoch 48 - iter 116/585 - loss 0.41240927 - samples/sec: 89.44 - lr: 0.100000
2020-09-15 23:42:26,573 epoch 48 - iter 174/585 - loss 0.40206232 - samples/sec: 86.91 - lr: 0.100000
2020-09-15 23:42:46,860 epoch 48 - iter 232/585 - loss 0.38032877 - samples/sec: 91.53 - lr: 0.100000
2020-09-15 23:43:07,452 epoch 48 - iter 290/585 - loss 0.36896846 - samples/sec: 90.17 - lr: 0.100000
2020-09-15 23:43:27,428 epoch 48 - iter 348/585 - loss 0.35979240 - samples/sec: 92.95 - lr: 0.100000
2020-09-15 23:43:38,619 epoch 48 - iter 406/585 - loss 0.35676714 - samples/sec: 165.99 - lr: 0.100000
2020-09-15 23:43:48,432 epoch 48 - iter 464/585 - loss 0.35439465 - samples/sec: 189.33 - lr: 0.100000
2020-09-15 23:44:10,317 epoch 48 - iter 522/585 - loss 0.35470987 - samples/sec: 84.84 - lr: 0.100000
2020-09-15 23:44:36,158 epoch 48 - iter 580/585 - loss 0.39525071 - samples/sec: 71.85 - lr: 0.100000
2020-09-15 23:44:38,011 ----------------------------------------------------------------------------------------------------
2020-09-15 23:44:38,011 EPOCH 48 done: loss 0.3950 - lr 0.1000000
2020-09-15 23:44:38,011 BAD EPOCHS (no improvement): 0
2020-09-15 23:44:38,014 ----------------------------------------------------------------------------------------------------
2020-09-15 23:45:00,819 epoch 49 - iter 58/585 - loss 0.29939853 - samples/sec: 81.42 - lr: 0.100000
2020-09-15 23:45:22,710 epoch 49 - iter 116/585 - loss 0.31680993 - samples/sec: 84.82 - lr: 0.100000
2020-09-15 23:45:36,654 epoch 49 - iter 174/585 - loss 0.32660100 - samples/sec: 133.18 - lr: 0.100000
2020-09-15 23:45:47,542 epoch 49 - iter 232/585 - loss 0.37941802 - samples/sec: 170.63 - lr: 0.100000
2020-09-15 23:46:08,556 epoch 49 - iter 290/585 - loss 0.36812387 - samples/sec: 88.36 - lr: 0.100000
2020-09-15 23:46:28,538 epoch 49 - iter 348/585 - loss 0.36784066 - samples/sec: 92.92 - lr: 0.100000
2020-09-15 23:46:50,169 epoch 49 - iter 406/585 - loss 0.39933226 - samples/sec: 85.84 - lr: 0.100000
2020-09-15 23:47:12,246 epoch 49 - iter 464/585 - loss 0.41184130 - samples/sec: 84.10 - lr: 0.100000
2020-09-15 23:47:32,351 epoch 49 - iter 522/585 - loss 0.39935783 - samples/sec: 92.35 - lr: 0.100000
2020-09-15 23:47:41,440 epoch 49 - iter 580/585 - loss 0.39615619 - samples/sec: 204.42 - lr: 0.100000
2020-09-15 23:47:42,003 ----------------------------------------------------------------------------------------------------
2020-09-15 23:47:42,003 EPOCH 49 done: loss 0.3955 - lr 0.1000000
2020-09-15 23:47:42,003 BAD EPOCHS (no improvement): 1
2020-09-15 23:47:42,006 ----------------------------------------------------------------------------------------------------
2020-09-15 23:47:55,267 epoch 50 - iter 58/585 - loss 0.33672425 - samples/sec: 140.09 - lr: 0.100000
2020-09-15 23:48:15,868 epoch 50 - iter 116/585 - loss 0.36067475 - samples/sec: 90.13 - lr: 0.100000
2020-09-15 23:48:38,649 epoch 50 - iter 174/585 - loss 0.47269251 - samples/sec: 81.50 - lr: 0.100000
2020-09-15 23:48:58,855 epoch 50 - iter 232/585 - loss 0.44930480 - samples/sec: 91.89 - lr: 0.100000
2020-09-15 23:49:19,450 epoch 50 - iter 290/585 - loss 0.42379827 - samples/sec: 90.15 - lr: 0.100000
2020-09-15 23:49:36,991 epoch 50 - iter 348/585 - loss 0.40598176 - samples/sec: 105.86 - lr: 0.100000
2020-09-15 23:49:45,212 epoch 50 - iter 406/585 - loss 0.39892767 - samples/sec: 226.03 - lr: 0.100000
2020-09-15 23:50:00,606 epoch 50 - iter 464/585 - loss 0.39124944 - samples/sec: 120.63 - lr: 0.100000
2020-09-15 23:50:20,187 epoch 50 - iter 522/585 - loss 0.38100102 - samples/sec: 94.83 - lr: 0.100000
2020-09-15 23:50:42,118 epoch 50 - iter 580/585 - loss 0.39445594 - samples/sec: 84.66 - lr: 0.100000
2020-09-15 23:50:43,512 ----------------------------------------------------------------------------------------------------
2020-09-15 23:50:43,512 EPOCH 50 done: loss 0.3932 - lr 0.1000000
2020-09-15 23:50:43,512 BAD EPOCHS (no improvement): 0
2020-09-15 23:50:43,516 ----------------------------------------------------------------------------------------------------
2020-09-15 23:51:05,288 epoch 51 - iter 58/585 - loss 0.56249951 - samples/sec: 85.28 - lr: 0.100000
2020-09-15 23:51:25,288 epoch 51 - iter 116/585 - loss 0.45410402 - samples/sec: 92.84 - lr: 0.100000
2020-09-15 23:51:39,712 epoch 51 - iter 174/585 - loss 0.42248903 - samples/sec: 128.76 - lr: 0.100000
2020-09-15 23:51:47,974 epoch 51 - iter 232/585 - loss 0.40096232 - samples/sec: 224.94 - lr: 0.100000
2020-09-15 23:52:04,411 epoch 51 - iter 290/585 - loss 0.38155695 - samples/sec: 112.99 - lr: 0.100000
2020-09-15 23:52:36,047 epoch 51 - iter 348/585 - loss 0.37272031 - samples/sec: 58.68 - lr: 0.100000
2020-09-15 23:53:07,673 epoch 51 - iter 406/585 - loss 0.36596488 - samples/sec: 58.70 - lr: 0.100000
2020-09-15 23:53:39,317 epoch 51 - iter 464/585 - loss 0.36583507 - samples/sec: 58.67 - lr: 0.100000
2020-09-15 23:54:03,260 epoch 51 - iter 522/585 - loss 0.36084689 - samples/sec: 77.55 - lr: 0.100000
2020-09-15 23:54:18,356 epoch 51 - iter 580/585 - loss 0.40397013 - samples/sec: 123.02 - lr: 0.100000
2020-09-15 23:54:18,902 ----------------------------------------------------------------------------------------------------
2020-09-15 23:54:18,903 EPOCH 51 done: loss 0.4040 - lr 0.1000000
2020-09-15 23:54:18,903 BAD EPOCHS (no improvement): 1
2020-09-15 23:54:18,909 ----------------------------------------------------------------------------------------------------
2020-09-15 23:54:38,085 epoch 52 - iter 58/585 - loss 0.32159423 - samples/sec: 96.84 - lr: 0.100000
2020-09-15 23:55:09,602 epoch 52 - iter 116/585 - loss 0.31590481 - samples/sec: 58.90 - lr: 0.100000
2020-09-15 23:55:42,648 epoch 52 - iter 174/585 - loss 0.37722309 - samples/sec: 56.18 - lr: 0.100000
2020-09-15 23:56:14,309 epoch 52 - iter 232/585 - loss 0.35790589 - samples/sec: 58.64 - lr: 0.100000
2020-09-15 23:56:34,294 epoch 52 - iter 290/585 - loss 0.34894708 - samples/sec: 92.91 - lr: 0.100000
2020-09-15 23:56:48,740 epoch 52 - iter 348/585 - loss 0.40130339 - samples/sec: 128.56 - lr: 0.100000
2020-09-15 23:57:09,009 epoch 52 - iter 406/585 - loss 0.38672045 - samples/sec: 91.61 - lr: 0.100000
2020-09-15 23:57:41,309 epoch 52 - iter 464/585 - loss 0.39248061 - samples/sec: 57.48 - lr: 0.100000
2020-09-15 23:58:12,907 epoch 52 - iter 522/585 - loss 0.38575682 - samples/sec: 58.75 - lr: 0.100000
2020-09-15 23:58:44,373 epoch 52 - iter 580/585 - loss 0.37793011 - samples/sec: 59.00 - lr: 0.100000
2020-09-15 23:58:46,888 ----------------------------------------------------------------------------------------------------
2020-09-15 23:58:46,889 EPOCH 52 done: loss 0.3768 - lr 0.1000000
2020-09-15 23:58:46,889 BAD EPOCHS (no improvement): 0
2020-09-15 23:58:46,892 ----------------------------------------------------------------------------------------------------
2020-09-15 23:59:05,905 epoch 53 - iter 58/585 - loss 0.37627815 - samples/sec: 97.69 - lr: 0.100000
2020-09-15 23:59:18,986 epoch 53 - iter 116/585 - loss 0.38271056 - samples/sec: 141.99 - lr: 0.100000
2020-09-15 23:59:44,101 epoch 53 - iter 174/585 - loss 0.34890301 - samples/sec: 73.93 - lr: 0.100000
2020-09-16 00:00:15,614 epoch 53 - iter 232/585 - loss 0.33507652 - samples/sec: 58.91 - lr: 0.100000
2020-09-16 00:00:48,181 epoch 53 - iter 290/585 - loss 0.37048742 - samples/sec: 57.01 - lr: 0.100000
2020-09-16 00:01:19,821 epoch 53 - iter 348/585 - loss 0.36266765 - samples/sec: 58.68 - lr: 0.100000
2020-09-16 00:01:36,383 epoch 53 - iter 406/585 - loss 0.38334463 - samples/sec: 112.13 - lr: 0.100000
2020-09-16 00:01:49,113 epoch 53 - iter 464/585 - loss 0.39342409 - samples/sec: 145.90 - lr: 0.100000
2020-09-16 00:02:13,953 epoch 53 - iter 522/585 - loss 0.38565300 - samples/sec: 74.74 - lr: 0.100000
2020-09-16 00:02:45,582 epoch 53 - iter 580/585 - loss 0.37889693 - samples/sec: 58.70 - lr: 0.100000
2020-09-16 00:02:46,330 ----------------------------------------------------------------------------------------------------
2020-09-16 00:02:46,330 EPOCH 53 done: loss 0.3784 - lr 0.1000000
2020-09-16 00:02:46,330 BAD EPOCHS (no improvement): 1
2020-09-16 00:02:46,333 ----------------------------------------------------------------------------------------------------
2020-09-16 00:03:15,754 epoch 54 - iter 58/585 - loss 0.35931614 - samples/sec: 63.11 - lr: 0.100000
2020-09-16 00:03:48,025 epoch 54 - iter 116/585 - loss 0.38131457 - samples/sec: 57.53 - lr: 0.100000
2020-09-16 00:04:08,128 epoch 54 - iter 174/585 - loss 0.42481030 - samples/sec: 92.37 - lr: 0.100000
2020-09-16 00:04:19,402 epoch 54 - iter 232/585 - loss 0.38631324 - samples/sec: 164.76 - lr: 0.100000
2020-09-16 00:04:47,757 epoch 54 - iter 290/585 - loss 0.40547847 - samples/sec: 65.48 - lr: 0.100000
2020-09-16 00:05:20,730 epoch 54 - iter 348/585 - loss 0.43165950 - samples/sec: 56.30 - lr: 0.100000
2020-09-16 00:05:52,146 epoch 54 - iter 406/585 - loss 0.41415749 - samples/sec: 59.09 - lr: 0.100000
2020-09-16 00:06:23,526 epoch 54 - iter 464/585 - loss 0.40213354 - samples/sec: 59.16 - lr: 0.100000
2020-09-16 00:06:37,165 epoch 54 - iter 522/585 - loss 0.39201283 - samples/sec: 136.18 - lr: 0.100000
2020-09-16 00:06:48,121 epoch 54 - iter 580/585 - loss 0.38930127 - samples/sec: 169.56 - lr: 0.100000
2020-09-16 00:06:48,681 ----------------------------------------------------------------------------------------------------
2020-09-16 00:06:48,681 EPOCH 54 done: loss 0.3891 - lr 0.1000000
2020-09-16 00:06:48,681 BAD EPOCHS (no improvement): 2
2020-09-16 00:06:48,684 ----------------------------------------------------------------------------------------------------
2020-09-16 00:07:19,625 epoch 55 - iter 58/585 - loss 0.30928791 - samples/sec: 60.01 - lr: 0.100000
2020-09-16 00:07:51,122 epoch 55 - iter 116/585 - loss 0.31364597 - samples/sec: 58.94 - lr: 0.100000
2020-09-16 00:08:22,780 epoch 55 - iter 174/585 - loss 0.32225102 - samples/sec: 58.64 - lr: 0.100000
2020-09-16 00:08:54,269 epoch 55 - iter 232/585 - loss 0.31359396 - samples/sec: 58.96 - lr: 0.100000
2020-09-16 00:09:08,107 epoch 55 - iter 290/585 - loss 0.35677964 - samples/sec: 134.22 - lr: 0.100000
2020-09-16 00:09:21,739 epoch 55 - iter 348/585 - loss 0.38652155 - samples/sec: 136.25 - lr: 0.100000
2020-09-16 00:09:53,924 epoch 55 - iter 406/585 - loss 0.39113911 - samples/sec: 57.68 - lr: 0.100000
2020-09-16 00:10:27,018 epoch 55 - iter 464/585 - loss 0.39524809 - samples/sec: 56.10 - lr: 0.100000
2020-09-16 00:10:58,551 epoch 55 - iter 522/585 - loss 0.38615729 - samples/sec: 58.87 - lr: 0.100000
2020-09-16 00:11:27,645 epoch 55 - iter 580/585 - loss 0.38029845 - samples/sec: 63.81 - lr: 0.100000
2020-09-16 00:11:28,159 ----------------------------------------------------------------------------------------------------
2020-09-16 00:11:28,159 EPOCH 55 done: loss 0.3790 - lr 0.1000000
2020-09-16 00:11:28,160 BAD EPOCHS (no improvement): 3
2020-09-16 00:11:28,165 ----------------------------------------------------------------------------------------------------
2020-09-16 00:11:40,283 epoch 56 - iter 58/585 - loss 0.27950299 - samples/sec: 153.31 - lr: 0.100000
2020-09-16 00:11:49,681 epoch 56 - iter 116/585 - loss 0.29432777 - samples/sec: 197.71 - lr: 0.100000
2020-09-16 00:12:21,297 epoch 56 - iter 174/585 - loss 0.30542840 - samples/sec: 58.72 - lr: 0.100000
2020-09-16 00:12:54,579 epoch 56 - iter 232/585 - loss 0.35289772 - samples/sec: 55.78 - lr: 0.100000
2020-09-16 00:13:27,943 epoch 56 - iter 290/585 - loss 0.39961265 - samples/sec: 55.64 - lr: 0.100000
2020-09-16 00:13:58,403 epoch 56 - iter 348/585 - loss 0.39510418 - samples/sec: 60.95 - lr: 0.100000
2020-09-16 00:14:10,278 epoch 56 - iter 406/585 - loss 0.39264722 - samples/sec: 156.43 - lr: 0.100000
2020-09-16 00:14:23,330 epoch 56 - iter 464/585 - loss 0.38565542 - samples/sec: 142.30 - lr: 0.100000
2020-09-16 00:14:56,368 epoch 56 - iter 522/585 - loss 0.39537761 - samples/sec: 56.19 - lr: 0.100000
2020-09-16 00:15:27,854 epoch 56 - iter 580/585 - loss 0.38745132 - samples/sec: 58.96 - lr: 0.100000
2020-09-16 00:15:30,484 ----------------------------------------------------------------------------------------------------
2020-09-16 00:15:30,484 EPOCH 56 done: loss 0.3870 - lr 0.1000000
2020-09-16 00:15:30,485 BAD EPOCHS (no improvement): 4
2020-09-16 00:15:30,488 ----------------------------------------------------------------------------------------------------
2020-09-16 00:16:03,832 epoch 57 - iter 58/585 - loss 0.45362846 - samples/sec: 55.68 - lr: 0.050000
2020-09-16 00:16:28,686 epoch 57 - iter 116/585 - loss 0.37648024 - samples/sec: 74.70 - lr: 0.050000
2020-09-16 00:16:42,066 epoch 57 - iter 174/585 - loss 0.35189904 - samples/sec: 138.81 - lr: 0.050000
2020-09-16 00:16:57,175 epoch 57 - iter 232/585 - loss 0.33666925 - samples/sec: 122.92 - lr: 0.050000
2020-09-16 00:17:29,329 epoch 57 - iter 290/585 - loss 0.33606120 - samples/sec: 57.74 - lr: 0.050000
2020-09-16 00:18:00,916 epoch 57 - iter 348/585 - loss 0.32828389 - samples/sec: 58.77 - lr: 0.050000
2020-09-16 00:18:32,586 epoch 57 - iter 406/585 - loss 0.32141226 - samples/sec: 58.62 - lr: 0.050000
2020-09-16 00:18:57,940 epoch 57 - iter 464/585 - loss 0.33091970 - samples/sec: 73.23 - lr: 0.050000
2020-09-16 00:19:11,462 epoch 57 - iter 522/585 - loss 0.32701059 - samples/sec: 137.34 - lr: 0.050000
2020-09-16 00:19:31,458 epoch 57 - iter 580/585 - loss 0.34047581 - samples/sec: 92.86 - lr: 0.050000
2020-09-16 00:19:33,979 ----------------------------------------------------------------------------------------------------
2020-09-16 00:19:33,979 EPOCH 57 done: loss 0.3403 - lr 0.0500000
2020-09-16 00:19:33,980 BAD EPOCHS (no improvement): 0
2020-09-16 00:19:33,983 ----------------------------------------------------------------------------------------------------
2020-09-16 00:20:05,756 epoch 58 - iter 58/585 - loss 0.25295881 - samples/sec: 58.44 - lr: 0.050000
2020-09-16 00:20:38,273 epoch 58 - iter 116/585 - loss 0.25792029 - samples/sec: 57.09 - lr: 0.050000
2020-09-16 00:21:09,968 epoch 58 - iter 174/585 - loss 0.25707557 - samples/sec: 58.57 - lr: 0.050000
2020-09-16 00:21:28,495 epoch 58 - iter 232/585 - loss 0.26175185 - samples/sec: 100.23 - lr: 0.050000
2020-09-16 00:21:41,870 epoch 58 - iter 290/585 - loss 0.28326338 - samples/sec: 138.86 - lr: 0.050000
2020-09-16 00:22:08,518 epoch 58 - iter 348/585 - loss 0.31182913 - samples/sec: 69.67 - lr: 0.050000
2020-09-16 00:22:38,793 epoch 58 - iter 406/585 - loss 0.30224789 - samples/sec: 61.32 - lr: 0.050000
2020-09-16 00:23:10,267 epoch 58 - iter 464/585 - loss 0.29769254 - samples/sec: 58.98 - lr: 0.050000
2020-09-16 00:23:44,633 epoch 58 - iter 522/585 - loss 0.33062860 - samples/sec: 54.02 - lr: 0.050000
2020-09-16 00:24:00,454 epoch 58 - iter 580/585 - loss 0.32584408 - samples/sec: 117.38 - lr: 0.050000
2020-09-16 00:24:01,727 ----------------------------------------------------------------------------------------------------
2020-09-16 00:24:01,727 EPOCH 58 done: loss 0.3259 - lr 0.0500000
2020-09-16 00:24:01,727 BAD EPOCHS (no improvement): 0
2020-09-16 00:24:01,731 ----------------------------------------------------------------------------------------------------
2020-09-16 00:24:12,900 epoch 59 - iter 58/585 - loss 0.28088551 - samples/sec: 166.34 - lr: 0.050000
2020-09-16 00:24:43,006 epoch 59 - iter 116/585 - loss 0.27122378 - samples/sec: 61.66 - lr: 0.050000
2020-09-16 00:25:14,550 epoch 59 - iter 174/585 - loss 0.27879875 - samples/sec: 58.85 - lr: 0.050000
2020-09-16 00:25:46,761 epoch 59 - iter 232/585 - loss 0.29431049 - samples/sec: 57.64 - lr: 0.050000
2020-09-16 00:26:18,256 epoch 59 - iter 290/585 - loss 0.28684465 - samples/sec: 58.95 - lr: 0.050000
2020-09-16 00:26:32,834 epoch 59 - iter 348/585 - loss 0.30201414 - samples/sec: 127.40 - lr: 0.050000
2020-09-16 00:26:52,091 epoch 59 - iter 406/585 - loss 0.34816355 - samples/sec: 96.42 - lr: 0.050000
2020-09-16 00:27:23,781 epoch 59 - iter 464/585 - loss 0.33775850 - samples/sec: 58.58 - lr: 0.050000
2020-09-16 00:27:55,247 epoch 59 - iter 522/585 - loss 0.33021538 - samples/sec: 59.00 - lr: 0.050000
2020-09-16 00:28:26,776 epoch 59 - iter 580/585 - loss 0.32568572 - samples/sec: 58.88 - lr: 0.050000
2020-09-16 00:28:29,349 ----------------------------------------------------------------------------------------------------
2020-09-16 00:28:29,349 EPOCH 59 done: loss 0.3253 - lr 0.0500000
2020-09-16 00:28:29,349 BAD EPOCHS (no improvement): 0
2020-09-16 00:28:29,363 ----------------------------------------------------------------------------------------------------
2020-09-16 00:28:53,033 epoch 60 - iter 58/585 - loss 0.27682828 - samples/sec: 78.45 - lr: 0.050000
2020-09-16 00:29:06,618 epoch 60 - iter 116/585 - loss 0.27625417 - samples/sec: 136.71 - lr: 0.050000
2020-09-16 00:29:23,084 epoch 60 - iter 174/585 - loss 0.27063375 - samples/sec: 112.78 - lr: 0.050000
2020-09-16 00:29:54,689 epoch 60 - iter 232/585 - loss 0.26271549 - samples/sec: 58.74 - lr: 0.050000
2020-09-16 00:30:27,606 epoch 60 - iter 290/585 - loss 0.28516128 - samples/sec: 56.40 - lr: 0.050000
2020-09-16 00:30:59,223 epoch 60 - iter 348/585 - loss 0.28427214 - samples/sec: 58.72 - lr: 0.050000
2020-09-16 00:31:22,178 epoch 60 - iter 406/585 - loss 0.27656812 - samples/sec: 80.88 - lr: 0.050000
2020-09-16 00:31:36,479 epoch 60 - iter 464/585 - loss 0.30472505 - samples/sec: 129.86 - lr: 0.050000
2020-09-16 00:31:55,176 epoch 60 - iter 522/585 - loss 0.31985213 - samples/sec: 99.32 - lr: 0.050000
2020-09-16 00:32:26,725 epoch 60 - iter 580/585 - loss 0.31526677 - samples/sec: 58.84 - lr: 0.050000
2020-09-16 00:32:29,328 ----------------------------------------------------------------------------------------------------
2020-09-16 00:32:29,328 EPOCH 60 done: loss 0.3144 - lr 0.0500000
2020-09-16 00:32:29,328 BAD EPOCHS (no improvement): 0
2020-09-16 00:32:29,331 ----------------------------------------------------------------------------------------------------
2020-09-16 00:33:00,973 epoch 61 - iter 58/585 - loss 0.25600156 - samples/sec: 58.68 - lr: 0.050000
2020-09-16 00:33:33,199 epoch 61 - iter 116/585 - loss 0.27460958 - samples/sec: 57.61 - lr: 0.050000
2020-09-16 00:33:54,339 epoch 61 - iter 174/585 - loss 0.32939620 - samples/sec: 87.84 - lr: 0.050000
2020-09-16 00:34:07,878 epoch 61 - iter 232/585 - loss 0.33161660 - samples/sec: 137.17 - lr: 0.050000
2020-09-16 00:34:38,837 epoch 61 - iter 290/585 - loss 0.36950197 - samples/sec: 59.97 - lr: 0.050000
2020-09-16 00:35:10,424 epoch 61 - iter 348/585 - loss 0.35193329 - samples/sec: 58.77 - lr: 0.050000
2020-09-16 00:35:41,897 epoch 61 - iter 406/585 - loss 0.33377884 - samples/sec: 58.99 - lr: 0.050000
2020-09-16 00:36:13,540 epoch 61 - iter 464/585 - loss 0.32581412 - samples/sec: 58.67 - lr: 0.050000
2020-09-16 00:36:26,765 epoch 61 - iter 522/585 - loss 0.32157073 - samples/sec: 140.44 - lr: 0.050000
2020-09-16 00:36:37,596 epoch 61 - iter 580/585 - loss 0.32102612 - samples/sec: 171.51 - lr: 0.050000
2020-09-16 00:36:38,141 ----------------------------------------------------------------------------------------------------
2020-09-16 00:36:38,141 EPOCH 61 done: loss 0.3198 - lr 0.0500000
2020-09-16 00:36:38,141 BAD EPOCHS (no improvement): 1
2020-09-16 00:36:38,145 ----------------------------------------------------------------------------------------------------
2020-09-16 00:37:09,942 epoch 62 - iter 58/585 - loss 0.34693233 - samples/sec: 58.39 - lr: 0.050000
2020-09-16 00:37:42,181 epoch 62 - iter 116/585 - loss 0.30952811 - samples/sec: 57.59 - lr: 0.050000
2020-09-16 00:38:13,707 epoch 62 - iter 174/585 - loss 0.27960681 - samples/sec: 58.89 - lr: 0.050000
2020-09-16 00:38:45,257 epoch 62 - iter 232/585 - loss 0.27379067 - samples/sec: 58.84 - lr: 0.050000
2020-09-16 00:38:57,419 epoch 62 - iter 290/585 - loss 0.26615992 - samples/sec: 152.73 - lr: 0.050000
2020-09-16 00:39:11,942 epoch 62 - iter 348/585 - loss 0.32666027 - samples/sec: 127.88 - lr: 0.050000
2020-09-16 00:39:43,514 epoch 62 - iter 406/585 - loss 0.31593003 - samples/sec: 58.80 - lr: 0.050000
2020-09-16 00:40:15,080 epoch 62 - iter 464/585 - loss 0.30947401 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 00:40:47,462 epoch 62 - iter 522/585 - loss 0.31834699 - samples/sec: 57.33 - lr: 0.050000
2020-09-16 00:41:17,474 epoch 62 - iter 580/585 - loss 0.31310092 - samples/sec: 61.86 - lr: 0.050000
2020-09-16 00:41:18,004 ----------------------------------------------------------------------------------------------------
2020-09-16 00:41:18,004 EPOCH 62 done: loss 0.3120 - lr 0.0500000
2020-09-16 00:41:18,004 BAD EPOCHS (no improvement): 0
2020-09-16 00:41:18,007 ----------------------------------------------------------------------------------------------------
2020-09-16 00:41:29,755 epoch 63 - iter 58/585 - loss 0.24234294 - samples/sec: 158.13 - lr: 0.050000
2020-09-16 00:41:43,347 epoch 63 - iter 116/585 - loss 0.35261727 - samples/sec: 136.64 - lr: 0.050000
2020-09-16 00:42:14,898 epoch 63 - iter 174/585 - loss 0.31611900 - samples/sec: 58.84 - lr: 0.050000
2020-09-16 00:42:47,856 epoch 63 - iter 232/585 - loss 0.33981075 - samples/sec: 56.33 - lr: 0.050000
2020-09-16 00:43:19,335 epoch 63 - iter 290/585 - loss 0.32549847 - samples/sec: 58.98 - lr: 0.050000
2020-09-16 00:43:48,185 epoch 63 - iter 348/585 - loss 0.33147365 - samples/sec: 64.35 - lr: 0.050000
2020-09-16 00:44:00,867 epoch 63 - iter 406/585 - loss 0.31891600 - samples/sec: 146.45 - lr: 0.050000
2020-09-16 00:44:15,916 epoch 63 - iter 464/585 - loss 0.31255096 - samples/sec: 123.40 - lr: 0.050000
2020-09-16 00:44:47,536 epoch 63 - iter 522/585 - loss 0.30656091 - samples/sec: 58.71 - lr: 0.050000
2020-09-16 00:45:19,071 epoch 63 - iter 580/585 - loss 0.29978839 - samples/sec: 58.87 - lr: 0.050000
2020-09-16 00:45:21,658 ----------------------------------------------------------------------------------------------------
2020-09-16 00:45:21,659 EPOCH 63 done: loss 0.2998 - lr 0.0500000
2020-09-16 00:45:21,659 BAD EPOCHS (no improvement): 0
2020-09-16 00:45:21,662 ----------------------------------------------------------------------------------------------------
2020-09-16 00:45:53,165 epoch 64 - iter 58/585 - loss 0.21786700 - samples/sec: 58.93 - lr: 0.050000
2020-09-16 00:46:17,714 epoch 64 - iter 116/585 - loss 0.30685031 - samples/sec: 75.63 - lr: 0.050000
2020-09-16 00:46:31,208 epoch 64 - iter 174/585 - loss 0.27411358 - samples/sec: 137.64 - lr: 0.050000
2020-09-16 00:46:48,252 epoch 64 - iter 232/585 - loss 0.30305297 - samples/sec: 108.95 - lr: 0.050000
2020-09-16 00:47:19,766 epoch 64 - iter 290/585 - loss 0.29147326 - samples/sec: 58.91 - lr: 0.050000
2020-09-16 00:47:52,564 epoch 64 - iter 348/585 - loss 0.29696665 - samples/sec: 56.60 - lr: 0.050000
2020-09-16 00:48:25,514 epoch 64 - iter 406/585 - loss 0.30220232 - samples/sec: 56.34 - lr: 0.050000
2020-09-16 00:48:47,849 epoch 64 - iter 464/585 - loss 0.30051186 - samples/sec: 83.13 - lr: 0.050000
2020-09-16 00:49:01,232 epoch 64 - iter 522/585 - loss 0.29483114 - samples/sec: 138.76 - lr: 0.050000
2020-09-16 00:49:20,020 epoch 64 - iter 580/585 - loss 0.29161744 - samples/sec: 98.84 - lr: 0.050000
2020-09-16 00:49:22,602 ----------------------------------------------------------------------------------------------------
2020-09-16 00:49:22,602 EPOCH 64 done: loss 0.2918 - lr 0.0500000
2020-09-16 00:49:22,602 BAD EPOCHS (no improvement): 0
2020-09-16 00:49:22,607 ----------------------------------------------------------------------------------------------------
2020-09-16 00:49:54,153 epoch 65 - iter 58/585 - loss 0.25830818 - samples/sec: 58.85 - lr: 0.050000
2020-09-16 00:50:25,129 epoch 65 - iter 116/585 - loss 0.23647449 - samples/sec: 59.93 - lr: 0.050000
2020-09-16 00:50:56,407 epoch 65 - iter 174/585 - loss 0.28426691 - samples/sec: 59.35 - lr: 0.050000
2020-09-16 00:51:17,372 epoch 65 - iter 232/585 - loss 0.31887655 - samples/sec: 88.57 - lr: 0.050000
2020-09-16 00:51:30,821 epoch 65 - iter 290/585 - loss 0.31072698 - samples/sec: 138.08 - lr: 0.050000
2020-09-16 00:51:55,620 epoch 65 - iter 348/585 - loss 0.30688493 - samples/sec: 74.87 - lr: 0.050000
2020-09-16 00:52:27,222 epoch 65 - iter 406/585 - loss 0.29767576 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 00:52:59,030 epoch 65 - iter 464/585 - loss 0.30219970 - samples/sec: 58.37 - lr: 0.050000
2020-09-16 00:53:30,337 epoch 65 - iter 522/585 - loss 0.29505146 - samples/sec: 59.30 - lr: 0.050000
2020-09-16 00:53:48,069 epoch 65 - iter 580/585 - loss 0.28917963 - samples/sec: 104.72 - lr: 0.050000
2020-09-16 00:53:49,281 ----------------------------------------------------------------------------------------------------
2020-09-16 00:53:49,281 EPOCH 65 done: loss 0.2883 - lr 0.0500000
2020-09-16 00:53:49,281 BAD EPOCHS (no improvement): 0
2020-09-16 00:53:49,308 ----------------------------------------------------------------------------------------------------
2020-09-16 00:54:01,370 epoch 66 - iter 58/585 - loss 0.22634717 - samples/sec: 154.02 - lr: 0.050000
2020-09-16 00:54:31,749 epoch 66 - iter 116/585 - loss 0.32252304 - samples/sec: 61.11 - lr: 0.050000
2020-09-16 00:55:03,334 epoch 66 - iter 174/585 - loss 0.29322061 - samples/sec: 58.78 - lr: 0.050000
2020-09-16 00:55:35,970 epoch 66 - iter 232/585 - loss 0.32605286 - samples/sec: 56.89 - lr: 0.050000
2020-09-16 00:56:07,756 epoch 66 - iter 290/585 - loss 0.30850625 - samples/sec: 58.41 - lr: 0.050000
2020-09-16 00:56:20,459 epoch 66 - iter 348/585 - loss 0.30036241 - samples/sec: 146.25 - lr: 0.050000
2020-09-16 00:56:32,041 epoch 66 - iter 406/585 - loss 0.29862133 - samples/sec: 160.38 - lr: 0.050000
2020-09-16 00:57:04,150 epoch 66 - iter 464/585 - loss 0.31278463 - samples/sec: 57.82 - lr: 0.050000
2020-09-16 00:57:35,455 epoch 66 - iter 522/585 - loss 0.30636473 - samples/sec: 59.30 - lr: 0.050000
2020-09-16 00:58:05,797 epoch 66 - iter 580/585 - loss 0.29623530 - samples/sec: 61.19 - lr: 0.050000
2020-09-16 00:58:08,409 ----------------------------------------------------------------------------------------------------
2020-09-16 00:58:08,409 EPOCH 66 done: loss 0.2963 - lr 0.0500000
2020-09-16 00:58:08,409 BAD EPOCHS (no improvement): 1
2020-09-16 00:58:08,432 ----------------------------------------------------------------------------------------------------
2020-09-16 00:58:38,203 epoch 67 - iter 58/585 - loss 0.24376380 - samples/sec: 62.36 - lr: 0.050000
2020-09-16 00:58:50,621 epoch 67 - iter 116/585 - loss 0.23935733 - samples/sec: 149.57 - lr: 0.050000
2020-09-16 00:59:03,253 epoch 67 - iter 174/585 - loss 0.24979340 - samples/sec: 147.04 - lr: 0.050000
2020-09-16 00:59:36,131 epoch 67 - iter 232/585 - loss 0.27416286 - samples/sec: 56.46 - lr: 0.050000
2020-09-16 01:00:07,427 epoch 67 - iter 290/585 - loss 0.26131546 - samples/sec: 59.32 - lr: 0.050000
2020-09-16 01:00:38,988 epoch 67 - iter 348/585 - loss 0.25346993 - samples/sec: 58.82 - lr: 0.050000
2020-09-16 01:01:09,863 epoch 67 - iter 406/585 - loss 0.24832884 - samples/sec: 60.13 - lr: 0.050000
2020-09-16 01:01:21,748 epoch 67 - iter 464/585 - loss 0.27088209 - samples/sec: 156.29 - lr: 0.050000
2020-09-16 01:01:33,223 epoch 67 - iter 522/585 - loss 0.26752741 - samples/sec: 161.88 - lr: 0.050000
2020-09-16 01:02:02,398 epoch 67 - iter 580/585 - loss 0.27708116 - samples/sec: 63.63 - lr: 0.050000
2020-09-16 01:02:05,006 ----------------------------------------------------------------------------------------------------
2020-09-16 01:02:05,006 EPOCH 67 done: loss 0.2770 - lr 0.0500000
2020-09-16 01:02:05,006 BAD EPOCHS (no improvement): 0
2020-09-16 01:02:05,026 ----------------------------------------------------------------------------------------------------
2020-09-16 01:02:40,379 epoch 68 - iter 58/585 - loss 0.60379426 - samples/sec: 52.52 - lr: 0.050000
2020-09-16 01:03:11,494 epoch 68 - iter 116/585 - loss 0.39934076 - samples/sec: 59.67 - lr: 0.050000
2020-09-16 01:03:41,579 epoch 68 - iter 174/585 - loss 0.34041804 - samples/sec: 61.71 - lr: 0.050000
2020-09-16 01:03:54,022 epoch 68 - iter 232/585 - loss 0.36254933 - samples/sec: 149.28 - lr: 0.050000
2020-09-16 01:04:05,810 epoch 68 - iter 290/585 - loss 0.33880727 - samples/sec: 157.57 - lr: 0.050000
2020-09-16 01:04:37,369 epoch 68 - iter 348/585 - loss 0.31984877 - samples/sec: 58.83 - lr: 0.050000
2020-09-16 01:05:08,844 epoch 68 - iter 406/585 - loss 0.30930321 - samples/sec: 58.98 - lr: 0.050000
2020-09-16 01:05:39,744 epoch 68 - iter 464/585 - loss 0.30267599 - samples/sec: 60.08 - lr: 0.050000
2020-09-16 01:06:10,232 epoch 68 - iter 522/585 - loss 0.29336136 - samples/sec: 60.89 - lr: 0.050000
2020-09-16 01:06:21,062 epoch 68 - iter 580/585 - loss 0.28732388 - samples/sec: 171.53 - lr: 0.050000
2020-09-16 01:06:22,261 ----------------------------------------------------------------------------------------------------
2020-09-16 01:06:22,261 EPOCH 68 done: loss 0.2867 - lr 0.0500000
2020-09-16 01:06:22,261 BAD EPOCHS (no improvement): 1
2020-09-16 01:06:22,265 ----------------------------------------------------------------------------------------------------
2020-09-16 01:06:34,276 epoch 69 - iter 58/585 - loss 0.25289236 - samples/sec: 154.71 - lr: 0.050000
2020-09-16 01:07:05,821 epoch 69 - iter 116/585 - loss 0.25017635 - samples/sec: 58.85 - lr: 0.050000
2020-09-16 01:07:37,360 epoch 69 - iter 174/585 - loss 0.24420716 - samples/sec: 58.86 - lr: 0.050000
2020-09-16 01:08:11,203 epoch 69 - iter 232/585 - loss 0.29854669 - samples/sec: 54.86 - lr: 0.050000
2020-09-16 01:08:39,801 epoch 69 - iter 290/585 - loss 0.28694267 - samples/sec: 64.92 - lr: 0.050000
2020-09-16 01:08:52,172 epoch 69 - iter 348/585 - loss 0.30604271 - samples/sec: 150.14 - lr: 0.050000
2020-09-16 01:09:05,958 epoch 69 - iter 406/585 - loss 0.28955225 - samples/sec: 134.73 - lr: 0.050000
2020-09-16 01:09:37,555 epoch 69 - iter 464/585 - loss 0.28033880 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 01:10:09,104 epoch 69 - iter 522/585 - loss 0.27252094 - samples/sec: 58.85 - lr: 0.050000
2020-09-16 01:10:41,790 epoch 69 - iter 580/585 - loss 0.28300918 - samples/sec: 56.80 - lr: 0.050000
2020-09-16 01:10:44,350 ----------------------------------------------------------------------------------------------------
2020-09-16 01:10:44,350 EPOCH 69 done: loss 0.2833 - lr 0.0500000
2020-09-16 01:10:44,350 BAD EPOCHS (no improvement): 2
2020-09-16 01:10:44,354 ----------------------------------------------------------------------------------------------------
2020-09-16 01:11:09,667 epoch 70 - iter 58/585 - loss 0.19627494 - samples/sec: 73.36 - lr: 0.050000
2020-09-16 01:11:23,650 epoch 70 - iter 116/585 - loss 0.29431045 - samples/sec: 132.81 - lr: 0.050000
2020-09-16 01:11:41,004 epoch 70 - iter 174/585 - loss 0.26663144 - samples/sec: 107.01 - lr: 0.050000
2020-09-16 01:12:12,603 epoch 70 - iter 232/585 - loss 0.25792094 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 01:12:44,165 epoch 70 - iter 290/585 - loss 0.25194158 - samples/sec: 58.82 - lr: 0.050000
2020-09-16 01:13:16,544 epoch 70 - iter 348/585 - loss 0.26189302 - samples/sec: 57.34 - lr: 0.050000
2020-09-16 01:13:39,859 epoch 70 - iter 406/585 - loss 0.27392132 - samples/sec: 79.64 - lr: 0.050000
2020-09-16 01:13:54,517 epoch 70 - iter 464/585 - loss 0.28807889 - samples/sec: 126.69 - lr: 0.050000
2020-09-16 01:14:18,968 epoch 70 - iter 522/585 - loss 0.27872749 - samples/sec: 75.93 - lr: 0.050000
2020-09-16 01:14:50,567 epoch 70 - iter 580/585 - loss 0.27205797 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 01:14:53,066 ----------------------------------------------------------------------------------------------------
2020-09-16 01:14:53,066 EPOCH 70 done: loss 0.2707 - lr 0.0500000
2020-09-16 01:14:53,066 BAD EPOCHS (no improvement): 0
2020-09-16 01:14:53,069 ----------------------------------------------------------------------------------------------------
2020-09-16 01:15:19,636 epoch 71 - iter 58/585 - loss 0.24318770 - samples/sec: 69.89 - lr: 0.050000
2020-09-16 01:15:46,375 epoch 71 - iter 116/585 - loss 0.24161263 - samples/sec: 69.43 - lr: 0.050000
2020-09-16 01:16:10,763 epoch 71 - iter 174/585 - loss 0.27201181 - samples/sec: 76.13 - lr: 0.050000
2020-09-16 01:16:24,470 epoch 71 - iter 232/585 - loss 0.26199905 - samples/sec: 135.49 - lr: 0.050000
2020-09-16 01:16:44,997 epoch 71 - iter 290/585 - loss 0.24773179 - samples/sec: 90.46 - lr: 0.050000
2020-09-16 01:17:16,538 epoch 71 - iter 348/585 - loss 0.24600842 - samples/sec: 58.86 - lr: 0.050000
2020-09-16 01:17:47,973 epoch 71 - iter 406/585 - loss 0.24479659 - samples/sec: 59.06 - lr: 0.050000
2020-09-16 01:18:22,925 epoch 71 - iter 464/585 - loss 0.28049331 - samples/sec: 53.11 - lr: 0.050000
2020-09-16 01:18:43,475 epoch 71 - iter 522/585 - loss 0.29236066 - samples/sec: 90.36 - lr: 0.050000
2020-09-16 01:18:55,570 epoch 71 - iter 580/585 - loss 0.28775155 - samples/sec: 153.57 - lr: 0.050000
2020-09-16 01:18:56,245 ----------------------------------------------------------------------------------------------------
2020-09-16 01:18:56,245 EPOCH 71 done: loss 0.2871 - lr 0.0500000
2020-09-16 01:18:56,245 BAD EPOCHS (no improvement): 1
2020-09-16 01:18:56,249 ----------------------------------------------------------------------------------------------------
2020-09-16 01:19:29,574 epoch 72 - iter 58/585 - loss 0.48158716 - samples/sec: 55.71 - lr: 0.050000
2020-09-16 01:20:01,157 epoch 72 - iter 116/585 - loss 0.35744243 - samples/sec: 58.78 - lr: 0.050000
2020-09-16 01:20:32,722 epoch 72 - iter 174/585 - loss 0.30753213 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 01:21:05,328 epoch 72 - iter 232/585 - loss 0.30015166 - samples/sec: 56.94 - lr: 0.050000
2020-09-16 01:21:16,173 epoch 72 - iter 290/585 - loss 0.27301736 - samples/sec: 171.29 - lr: 0.050000
2020-09-16 01:21:27,399 epoch 72 - iter 348/585 - loss 0.26478596 - samples/sec: 165.45 - lr: 0.050000
2020-09-16 01:21:58,729 epoch 72 - iter 406/585 - loss 0.25467304 - samples/sec: 59.26 - lr: 0.050000
2020-09-16 01:22:30,390 epoch 72 - iter 464/585 - loss 0.25691983 - samples/sec: 58.64 - lr: 0.050000
2020-09-16 01:23:02,778 epoch 72 - iter 522/585 - loss 0.26600198 - samples/sec: 57.32 - lr: 0.050000
2020-09-16 01:23:34,249 epoch 72 - iter 580/585 - loss 0.26176152 - samples/sec: 58.99 - lr: 0.050000
2020-09-16 01:23:35,365 ----------------------------------------------------------------------------------------------------
2020-09-16 01:23:35,365 EPOCH 72 done: loss 0.2614 - lr 0.0500000
2020-09-16 01:23:35,365 BAD EPOCHS (no improvement): 0
2020-09-16 01:23:35,369 ----------------------------------------------------------------------------------------------------
2020-09-16 01:23:47,262 epoch 73 - iter 58/585 - loss 0.20967519 - samples/sec: 156.20 - lr: 0.050000
2020-09-16 01:24:01,138 epoch 73 - iter 116/585 - loss 0.19294541 - samples/sec: 133.83 - lr: 0.050000
2020-09-16 01:24:32,664 epoch 73 - iter 174/585 - loss 0.21218429 - samples/sec: 58.89 - lr: 0.050000
2020-09-16 01:25:06,358 epoch 73 - iter 232/585 - loss 0.25359746 - samples/sec: 55.10 - lr: 0.050000
2020-09-16 01:25:37,991 epoch 73 - iter 290/585 - loss 0.25080448 - samples/sec: 58.69 - lr: 0.050000
2020-09-16 01:26:04,911 epoch 73 - iter 348/585 - loss 0.24484563 - samples/sec: 68.97 - lr: 0.050000
2020-09-16 01:26:18,156 epoch 73 - iter 406/585 - loss 0.24497670 - samples/sec: 140.22 - lr: 0.050000
2020-09-16 01:26:36,269 epoch 73 - iter 464/585 - loss 0.25731579 - samples/sec: 102.52 - lr: 0.050000
2020-09-16 01:27:07,894 epoch 73 - iter 522/585 - loss 0.25324464 - samples/sec: 58.70 - lr: 0.050000
2020-09-16 01:27:41,557 epoch 73 - iter 580/585 - loss 0.27624532 - samples/sec: 55.15 - lr: 0.050000
2020-09-16 01:27:44,073 ----------------------------------------------------------------------------------------------------
2020-09-16 01:27:44,073 EPOCH 73 done: loss 0.2752 - lr 0.0500000
2020-09-16 01:27:44,073 BAD EPOCHS (no improvement): 1
2020-09-16 01:27:44,077 ----------------------------------------------------------------------------------------------------
2020-09-16 01:28:16,367 epoch 74 - iter 58/585 - loss 0.21108516 - samples/sec: 57.50 - lr: 0.050000
2020-09-16 01:28:37,137 epoch 74 - iter 116/585 - loss 0.32925675 - samples/sec: 89.40 - lr: 0.050000
2020-09-16 01:28:50,822 epoch 74 - iter 174/585 - loss 0.32244239 - samples/sec: 135.72 - lr: 0.050000
2020-09-16 01:29:14,280 epoch 74 - iter 232/585 - loss 0.31594536 - samples/sec: 79.15 - lr: 0.050000
2020-09-16 01:29:45,828 epoch 74 - iter 290/585 - loss 0.29836702 - samples/sec: 58.85 - lr: 0.050000
2020-09-16 01:30:17,157 epoch 74 - iter 348/585 - loss 0.28474333 - samples/sec: 59.26 - lr: 0.050000
2020-09-16 01:30:45,864 epoch 74 - iter 406/585 - loss 0.27615401 - samples/sec: 64.67 - lr: 0.050000
2020-09-16 01:31:06,527 epoch 74 - iter 464/585 - loss 0.28849809 - samples/sec: 89.86 - lr: 0.050000
2020-09-16 01:31:19,739 epoch 74 - iter 522/585 - loss 0.27957103 - samples/sec: 140.57 - lr: 0.050000
2020-09-16 01:31:39,989 epoch 74 - iter 580/585 - loss 0.27499858 - samples/sec: 91.70 - lr: 0.050000
2020-09-16 01:31:42,470 ----------------------------------------------------------------------------------------------------
2020-09-16 01:31:42,470 EPOCH 74 done: loss 0.2762 - lr 0.0500000
2020-09-16 01:31:42,470 BAD EPOCHS (no improvement): 2
2020-09-16 01:31:42,473 ----------------------------------------------------------------------------------------------------
2020-09-16 01:32:16,809 epoch 75 - iter 58/585 - loss 0.50497477 - samples/sec: 54.07 - lr: 0.050000
2020-09-16 01:32:48,181 epoch 75 - iter 116/585 - loss 0.35465914 - samples/sec: 59.18 - lr: 0.050000
2020-09-16 01:33:20,621 epoch 75 - iter 174/585 - loss 0.35371421 - samples/sec: 57.23 - lr: 0.050000
2020-09-16 01:33:37,574 epoch 75 - iter 232/585 - loss 0.31481823 - samples/sec: 109.54 - lr: 0.050000
2020-09-16 01:33:50,247 epoch 75 - iter 290/585 - loss 0.29385596 - samples/sec: 146.55 - lr: 0.050000
2020-09-16 01:34:15,321 epoch 75 - iter 348/585 - loss 0.28124664 - samples/sec: 74.05 - lr: 0.050000
2020-09-16 01:34:47,621 epoch 75 - iter 406/585 - loss 0.27699152 - samples/sec: 57.48 - lr: 0.050000
2020-09-16 01:35:19,069 epoch 75 - iter 464/585 - loss 0.26800111 - samples/sec: 59.03 - lr: 0.050000
2020-09-16 01:35:50,598 epoch 75 - iter 522/585 - loss 0.25960972 - samples/sec: 58.88 - lr: 0.050000
2020-09-16 01:36:06,515 epoch 75 - iter 580/585 - loss 0.25428230 - samples/sec: 116.68 - lr: 0.050000
2020-09-16 01:36:07,744 ----------------------------------------------------------------------------------------------------
2020-09-16 01:36:07,744 EPOCH 75 done: loss 0.2533 - lr 0.0500000
2020-09-16 01:36:07,744 BAD EPOCHS (no improvement): 0
2020-09-16 01:36:07,750 ----------------------------------------------------------------------------------------------------
2020-09-16 01:36:19,072 epoch 76 - iter 58/585 - loss 0.21170240 - samples/sec: 164.07 - lr: 0.050000
2020-09-16 01:36:47,042 epoch 76 - iter 116/585 - loss 0.29244756 - samples/sec: 66.38 - lr: 0.050000
2020-09-16 01:37:06,334 epoch 76 - iter 174/585 - loss 0.25401513 - samples/sec: 96.25 - lr: 0.050000
2020-09-16 01:37:38,280 epoch 76 - iter 232/585 - loss 0.24594146 - samples/sec: 58.11 - lr: 0.050000
2020-09-16 01:38:12,006 epoch 76 - iter 290/585 - loss 0.28692190 - samples/sec: 55.05 - lr: 0.050000
2020-09-16 01:38:35,487 epoch 76 - iter 348/585 - loss 0.26941494 - samples/sec: 79.07 - lr: 0.050000
2020-09-16 01:38:48,958 epoch 76 - iter 406/585 - loss 0.25918561 - samples/sec: 137.86 - lr: 0.050000
2020-09-16 01:39:05,723 epoch 76 - iter 464/585 - loss 0.25681597 - samples/sec: 110.77 - lr: 0.050000
2020-09-16 01:39:37,288 epoch 76 - iter 522/585 - loss 0.25499034 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 01:40:09,596 epoch 76 - iter 580/585 - loss 0.25520281 - samples/sec: 57.46 - lr: 0.050000
2020-09-16 01:40:12,184 ----------------------------------------------------------------------------------------------------
2020-09-16 01:40:12,184 EPOCH 76 done: loss 0.2541 - lr 0.0500000
2020-09-16 01:40:12,184 BAD EPOCHS (no improvement): 1
2020-09-16 01:40:12,189 ----------------------------------------------------------------------------------------------------
2020-09-16 01:40:45,243 epoch 77 - iter 58/585 - loss 0.32636969 - samples/sec: 56.17 - lr: 0.050000
2020-09-16 01:41:05,384 epoch 77 - iter 116/585 - loss 0.26858479 - samples/sec: 92.20 - lr: 0.050000
2020-09-16 01:41:18,904 epoch 77 - iter 174/585 - loss 0.24857918 - samples/sec: 137.37 - lr: 0.050000
2020-09-16 01:41:39,423 epoch 77 - iter 232/585 - loss 0.23254776 - samples/sec: 90.49 - lr: 0.050000
2020-09-16 01:42:10,726 epoch 77 - iter 290/585 - loss 0.22904911 - samples/sec: 59.31 - lr: 0.050000
2020-09-16 01:42:42,522 epoch 77 - iter 348/585 - loss 0.22979569 - samples/sec: 58.39 - lr: 0.050000
2020-09-16 01:43:14,735 epoch 77 - iter 406/585 - loss 0.23236744 - samples/sec: 57.63 - lr: 0.050000
2020-09-16 01:43:34,082 epoch 77 - iter 464/585 - loss 0.22936300 - samples/sec: 95.97 - lr: 0.050000
2020-09-16 01:43:47,707 epoch 77 - iter 522/585 - loss 0.24438491 - samples/sec: 136.31 - lr: 0.050000
2020-09-16 01:44:15,095 epoch 77 - iter 580/585 - loss 0.25578736 - samples/sec: 67.79 - lr: 0.050000
2020-09-16 01:44:17,575 ----------------------------------------------------------------------------------------------------
2020-09-16 01:44:17,575 EPOCH 77 done: loss 0.2551 - lr 0.0500000
2020-09-16 01:44:17,576 BAD EPOCHS (no improvement): 2
2020-09-16 01:44:17,599 ----------------------------------------------------------------------------------------------------
2020-09-16 01:44:49,107 epoch 78 - iter 58/585 - loss 0.21318857 - samples/sec: 58.92 - lr: 0.050000
2020-09-16 01:45:20,745 epoch 78 - iter 116/585 - loss 0.19851794 - samples/sec: 58.68 - lr: 0.050000
2020-09-16 01:45:52,184 epoch 78 - iter 174/585 - loss 0.19124920 - samples/sec: 59.05 - lr: 0.050000
2020-09-16 01:46:06,058 epoch 78 - iter 232/585 - loss 0.19215719 - samples/sec: 133.87 - lr: 0.050000
2020-09-16 01:46:18,412 epoch 78 - iter 290/585 - loss 0.23609401 - samples/sec: 150.33 - lr: 0.050000
2020-09-16 01:46:47,674 epoch 78 - iter 348/585 - loss 0.23049835 - samples/sec: 63.44 - lr: 0.050000
2020-09-16 01:47:20,665 epoch 78 - iter 406/585 - loss 0.25127240 - samples/sec: 56.27 - lr: 0.050000
2020-09-16 01:47:52,150 epoch 78 - iter 464/585 - loss 0.24494332 - samples/sec: 58.97 - lr: 0.050000
2020-09-16 01:48:24,528 epoch 78 - iter 522/585 - loss 0.25658603 - samples/sec: 57.34 - lr: 0.050000
2020-09-16 01:48:37,253 epoch 78 - iter 580/585 - loss 0.25334335 - samples/sec: 145.96 - lr: 0.050000
2020-09-16 01:48:38,547 ----------------------------------------------------------------------------------------------------
2020-09-16 01:48:38,548 EPOCH 78 done: loss 0.2531 - lr 0.0500000
2020-09-16 01:48:38,548 BAD EPOCHS (no improvement): 0
2020-09-16 01:48:38,551 ----------------------------------------------------------------------------------------------------
2020-09-16 01:48:53,101 epoch 79 - iter 58/585 - loss 0.32088027 - samples/sec: 127.64 - lr: 0.050000
2020-09-16 01:49:24,559 epoch 79 - iter 116/585 - loss 0.24894959 - samples/sec: 59.01 - lr: 0.050000
2020-09-16 01:49:55,932 epoch 79 - iter 174/585 - loss 0.23659981 - samples/sec: 59.18 - lr: 0.050000
2020-09-16 01:50:30,309 epoch 79 - iter 232/585 - loss 0.32221967 - samples/sec: 54.00 - lr: 0.050000
2020-09-16 01:50:58,402 epoch 79 - iter 290/585 - loss 0.30015130 - samples/sec: 66.09 - lr: 0.050000
2020-09-16 01:51:10,087 epoch 79 - iter 348/585 - loss 0.27997082 - samples/sec: 158.97 - lr: 0.050000
2020-09-16 01:51:24,771 epoch 79 - iter 406/585 - loss 0.27402641 - samples/sec: 126.46 - lr: 0.050000
2020-09-16 01:51:56,348 epoch 79 - iter 464/585 - loss 0.26596420 - samples/sec: 58.79 - lr: 0.050000
2020-09-16 01:52:28,136 epoch 79 - iter 522/585 - loss 0.25941273 - samples/sec: 58.40 - lr: 0.050000
2020-09-16 01:52:59,633 epoch 79 - iter 580/585 - loss 0.25362687 - samples/sec: 58.94 - lr: 0.050000
2020-09-16 01:53:02,208 ----------------------------------------------------------------------------------------------------
2020-09-16 01:53:02,209 EPOCH 79 done: loss 0.2522 - lr 0.0500000
2020-09-16 01:53:02,209 BAD EPOCHS (no improvement): 0
2020-09-16 01:53:02,213 ----------------------------------------------------------------------------------------------------
2020-09-16 01:53:28,547 epoch 80 - iter 58/585 - loss 0.46566833 - samples/sec: 70.51 - lr: 0.050000
2020-09-16 01:53:41,872 epoch 80 - iter 116/585 - loss 0.33643463 - samples/sec: 139.37 - lr: 0.050000
2020-09-16 01:54:00,834 epoch 80 - iter 174/585 - loss 0.29338051 - samples/sec: 97.93 - lr: 0.050000
2020-09-16 01:54:32,452 epoch 80 - iter 232/585 - loss 0.26745275 - samples/sec: 58.72 - lr: 0.050000
2020-09-16 01:55:05,544 epoch 80 - iter 290/585 - loss 0.28975546 - samples/sec: 56.10 - lr: 0.050000
2020-09-16 01:55:36,991 epoch 80 - iter 348/585 - loss 0.27086223 - samples/sec: 59.03 - lr: 0.050000
2020-09-16 01:55:58,396 epoch 80 - iter 406/585 - loss 0.26775512 - samples/sec: 86.75 - lr: 0.050000
2020-09-16 01:56:11,815 epoch 80 - iter 464/585 - loss 0.25867555 - samples/sec: 138.40 - lr: 0.050000
2020-09-16 01:56:18,616 epoch 80 - iter 522/585 - loss 0.25367605 - samples/sec: 273.30 - lr: 0.050000
2020-09-16 01:56:25,192 epoch 80 - iter 580/585 - loss 0.25066963 - samples/sec: 282.65 - lr: 0.050000
2020-09-16 01:56:25,716 ----------------------------------------------------------------------------------------------------
2020-09-16 01:56:25,716 EPOCH 80 done: loss 0.2501 - lr 0.0500000
2020-09-16 01:56:25,716 BAD EPOCHS (no improvement): 0
2020-09-16 01:56:25,722 ----------------------------------------------------------------------------------------------------
2020-09-16 01:56:32,479 epoch 81 - iter 58/585 - loss 0.23621577 - samples/sec: 275.09 - lr: 0.050000
2020-09-16 01:56:39,719 epoch 81 - iter 116/585 - loss 0.29403159 - samples/sec: 256.62 - lr: 0.050000
2020-09-16 01:56:47,897 epoch 81 - iter 174/585 - loss 0.37561130 - samples/sec: 227.23 - lr: 0.050000
2020-09-16 01:56:54,669 epoch 81 - iter 232/585 - loss 0.32249372 - samples/sec: 274.51 - lr: 0.050000
2020-09-16 01:57:01,925 epoch 81 - iter 290/585 - loss 0.31974046 - samples/sec: 256.12 - lr: 0.050000
2020-09-16 01:57:08,582 epoch 81 - iter 348/585 - loss 0.30363702 - samples/sec: 279.21 - lr: 0.050000
2020-09-16 01:57:14,985 epoch 81 - iter 406/585 - loss 0.29211009 - samples/sec: 290.22 - lr: 0.050000
2020-09-16 01:57:21,562 epoch 81 - iter 464/585 - loss 0.27896852 - samples/sec: 282.60 - lr: 0.050000
2020-09-16 01:57:36,943 epoch 81 - iter 522/585 - loss 0.26875355 - samples/sec: 120.72 - lr: 0.050000
2020-09-16 01:57:57,701 epoch 81 - iter 580/585 - loss 0.26511413 - samples/sec: 89.45 - lr: 0.050000
2020-09-16 01:57:59,333 ----------------------------------------------------------------------------------------------------
2020-09-16 01:57:59,333 EPOCH 81 done: loss 0.2646 - lr 0.0500000
2020-09-16 01:57:59,334 BAD EPOCHS (no improvement): 1
2020-09-16 01:57:59,341 ----------------------------------------------------------------------------------------------------
2020-09-16 01:58:18,978 epoch 82 - iter 58/585 - loss 0.19141539 - samples/sec: 94.56 - lr: 0.050000
2020-09-16 01:58:39,808 epoch 82 - iter 116/585 - loss 0.20512385 - samples/sec: 89.13 - lr: 0.050000
2020-09-16 01:59:00,459 epoch 82 - iter 174/585 - loss 0.20251123 - samples/sec: 89.91 - lr: 0.050000
2020-09-16 01:59:15,142 epoch 82 - iter 232/585 - loss 0.20177928 - samples/sec: 126.48 - lr: 0.050000
2020-09-16 01:59:23,110 epoch 82 - iter 290/585 - loss 0.19935782 - samples/sec: 233.26 - lr: 0.050000
2020-09-16 01:59:43,216 epoch 82 - iter 348/585 - loss 0.23346882 - samples/sec: 92.35 - lr: 0.050000
2020-09-16 02:00:03,216 epoch 82 - iter 406/585 - loss 0.22708969 - samples/sec: 92.83 - lr: 0.050000
2020-09-16 02:00:24,550 epoch 82 - iter 464/585 - loss 0.24011827 - samples/sec: 87.03 - lr: 0.050000
2020-09-16 02:00:44,688 epoch 82 - iter 522/585 - loss 0.23590266 - samples/sec: 92.20 - lr: 0.050000
2020-09-16 02:01:05,056 epoch 82 - iter 580/585 - loss 0.24579690 - samples/sec: 91.16 - lr: 0.050000
2020-09-16 02:01:06,677 ----------------------------------------------------------------------------------------------------
2020-09-16 02:01:06,677 EPOCH 82 done: loss 0.2459 - lr 0.0500000
2020-09-16 02:01:06,677 BAD EPOCHS (no improvement): 0
2020-09-16 02:01:06,699 ----------------------------------------------------------------------------------------------------
2020-09-16 02:01:17,943 epoch 83 - iter 58/585 - loss 0.20239173 - samples/sec: 165.25 - lr: 0.050000
2020-09-16 02:01:27,645 epoch 83 - iter 116/585 - loss 0.23763695 - samples/sec: 191.52 - lr: 0.050000
2020-09-16 02:01:49,023 epoch 83 - iter 174/585 - loss 0.21927771 - samples/sec: 86.85 - lr: 0.050000
2020-09-16 02:02:08,944 epoch 83 - iter 232/585 - loss 0.21057514 - samples/sec: 93.21 - lr: 0.050000
2020-09-16 02:02:29,042 epoch 83 - iter 290/585 - loss 0.20679525 - samples/sec: 92.38 - lr: 0.050000
2020-09-16 02:02:49,895 epoch 83 - iter 348/585 - loss 0.22827344 - samples/sec: 89.04 - lr: 0.050000
2020-09-16 02:03:09,775 epoch 83 - iter 406/585 - loss 0.22527872 - samples/sec: 93.40 - lr: 0.050000
2020-09-16 02:03:19,829 epoch 83 - iter 464/585 - loss 0.21909240 - samples/sec: 184.79 - lr: 0.050000
2020-09-16 02:03:30,301 epoch 83 - iter 522/585 - loss 0.23015746 - samples/sec: 177.39 - lr: 0.050000
2020-09-16 02:03:51,348 epoch 83 - iter 580/585 - loss 0.24777434 - samples/sec: 88.22 - lr: 0.050000
2020-09-16 02:03:52,805 ----------------------------------------------------------------------------------------------------
2020-09-16 02:03:52,805 EPOCH 83 done: loss 0.2480 - lr 0.0500000
2020-09-16 02:03:52,805 BAD EPOCHS (no improvement): 1
2020-09-16 02:03:52,809 ----------------------------------------------------------------------------------------------------
2020-09-16 02:04:13,165 epoch 84 - iter 58/585 - loss 0.30750381 - samples/sec: 91.22 - lr: 0.050000
2020-09-16 02:04:33,586 epoch 84 - iter 116/585 - loss 0.24960681 - samples/sec: 90.92 - lr: 0.050000
2020-09-16 02:04:50,779 epoch 84 - iter 174/585 - loss 0.22237039 - samples/sec: 108.01 - lr: 0.050000
2020-09-16 02:05:12,136 epoch 84 - iter 232/585 - loss 0.24489053 - samples/sec: 86.93 - lr: 0.050000
2020-09-16 02:05:22,957 epoch 84 - iter 290/585 - loss 0.23639487 - samples/sec: 171.68 - lr: 0.050000
2020-09-16 02:05:32,596 epoch 84 - iter 348/585 - loss 0.23152669 - samples/sec: 192.76 - lr: 0.050000
2020-09-16 02:05:53,244 epoch 84 - iter 406/585 - loss 0.23389692 - samples/sec: 89.92 - lr: 0.050000
2020-09-16 02:06:12,437 epoch 84 - iter 464/585 - loss 0.23132791 - samples/sec: 96.74 - lr: 0.050000
2020-09-16 02:06:34,145 epoch 84 - iter 522/585 - loss 0.25148506 - samples/sec: 85.53 - lr: 0.050000
2020-09-16 02:06:54,333 epoch 84 - iter 580/585 - loss 0.24347800 - samples/sec: 91.97 - lr: 0.050000
2020-09-16 02:06:55,850 ----------------------------------------------------------------------------------------------------
2020-09-16 02:06:55,850 EPOCH 84 done: loss 0.2424 - lr 0.0500000
2020-09-16 02:06:55,850 BAD EPOCHS (no improvement): 0
2020-09-16 02:06:55,860 ----------------------------------------------------------------------------------------------------
2020-09-16 02:07:15,853 epoch 85 - iter 58/585 - loss 0.18653598 - samples/sec: 92.88 - lr: 0.050000
2020-09-16 02:07:27,685 epoch 85 - iter 116/585 - loss 0.35185076 - samples/sec: 157.00 - lr: 0.050000
2020-09-16 02:07:41,554 epoch 85 - iter 174/585 - loss 0.29323788 - samples/sec: 133.91 - lr: 0.050000
2020-09-16 02:08:02,171 epoch 85 - iter 232/585 - loss 0.26310176 - samples/sec: 90.06 - lr: 0.050000
2020-09-16 02:08:22,702 epoch 85 - iter 290/585 - loss 0.24811630 - samples/sec: 90.43 - lr: 0.050000
2020-09-16 02:08:43,302 epoch 85 - iter 348/585 - loss 0.24315220 - samples/sec: 90.13 - lr: 0.050000
2020-09-16 02:09:04,336 epoch 85 - iter 406/585 - loss 0.24692180 - samples/sec: 88.27 - lr: 0.050000
2020-09-16 02:09:20,755 epoch 85 - iter 464/585 - loss 0.23873634 - samples/sec: 113.10 - lr: 0.050000
2020-09-16 02:09:28,767 epoch 85 - iter 522/585 - loss 0.23523034 - samples/sec: 231.94 - lr: 0.050000
2020-09-16 02:09:43,722 epoch 85 - iter 580/585 - loss 0.23099413 - samples/sec: 124.17 - lr: 0.050000
2020-09-16 02:09:46,294 ----------------------------------------------------------------------------------------------------
2020-09-16 02:09:46,295 EPOCH 85 done: loss 0.2429 - lr 0.0500000
2020-09-16 02:09:46,295 BAD EPOCHS (no improvement): 1
2020-09-16 02:09:46,301 ----------------------------------------------------------------------------------------------------
2020-09-16 02:10:07,174 epoch 86 - iter 58/585 - loss 0.19416101 - samples/sec: 88.96 - lr: 0.050000
2020-09-16 02:10:27,221 epoch 86 - iter 116/585 - loss 0.19973533 - samples/sec: 92.62 - lr: 0.050000
2020-09-16 02:10:47,656 epoch 86 - iter 174/585 - loss 0.19170503 - samples/sec: 90.86 - lr: 0.050000
2020-09-16 02:11:08,236 epoch 86 - iter 232/585 - loss 0.19246180 - samples/sec: 90.22 - lr: 0.050000
2020-09-16 02:11:22,382 epoch 86 - iter 290/585 - loss 0.18797914 - samples/sec: 131.28 - lr: 0.050000
2020-09-16 02:11:30,237 epoch 86 - iter 348/585 - loss 0.18799742 - samples/sec: 236.57 - lr: 0.050000
2020-09-16 02:11:49,250 epoch 86 - iter 406/585 - loss 0.22216582 - samples/sec: 97.66 - lr: 0.050000
2020-09-16 02:12:08,970 epoch 86 - iter 464/585 - loss 0.21956065 - samples/sec: 94.16 - lr: 0.050000
2020-09-16 02:12:29,742 epoch 86 - iter 522/585 - loss 0.22579767 - samples/sec: 89.38 - lr: 0.050000
2020-09-16 02:12:50,827 epoch 86 - iter 580/585 - loss 0.23609336 - samples/sec: 88.06 - lr: 0.050000
2020-09-16 02:12:52,390 ----------------------------------------------------------------------------------------------------
2020-09-16 02:12:52,391 EPOCH 86 done: loss 0.2349 - lr 0.0500000
2020-09-16 02:12:52,391 BAD EPOCHS (no improvement): 0
2020-09-16 02:12:52,396 ----------------------------------------------------------------------------------------------------
2020-09-16 02:13:14,635 epoch 87 - iter 58/585 - loss 0.41745194 - samples/sec: 83.49 - lr: 0.050000
2020-09-16 02:13:26,685 epoch 87 - iter 116/585 - loss 0.30144321 - samples/sec: 154.15 - lr: 0.050000
2020-09-16 02:13:35,425 epoch 87 - iter 174/585 - loss 0.25807910 - samples/sec: 212.62 - lr: 0.050000
2020-09-16 02:13:55,707 epoch 87 - iter 232/585 - loss 0.24062365 - samples/sec: 91.54 - lr: 0.050000
2020-09-16 02:14:17,128 epoch 87 - iter 290/585 - loss 0.26971232 - samples/sec: 86.67 - lr: 0.050000
2020-09-16 02:14:37,919 epoch 87 - iter 348/585 - loss 0.26505690 - samples/sec: 89.30 - lr: 0.050000
2020-09-16 02:14:57,209 epoch 87 - iter 406/585 - loss 0.25231859 - samples/sec: 96.25 - lr: 0.050000
2020-09-16 02:15:17,273 epoch 87 - iter 464/585 - loss 0.24119378 - samples/sec: 92.54 - lr: 0.050000
2020-09-16 02:15:28,061 epoch 87 - iter 522/585 - loss 0.23677815 - samples/sec: 172.20 - lr: 0.050000
2020-09-16 02:15:37,552 epoch 87 - iter 580/585 - loss 0.23023630 - samples/sec: 195.76 - lr: 0.050000
2020-09-16 02:15:39,242 ----------------------------------------------------------------------------------------------------
2020-09-16 02:15:39,242 EPOCH 87 done: loss 0.2298 - lr 0.0500000
2020-09-16 02:15:39,242 BAD EPOCHS (no improvement): 0
2020-09-16 02:15:39,249 ----------------------------------------------------------------------------------------------------
2020-09-16 02:15:59,537 epoch 88 - iter 58/585 - loss 0.16833467 - samples/sec: 91.52 - lr: 0.050000
2020-09-16 02:16:20,879 epoch 88 - iter 116/585 - loss 0.17330418 - samples/sec: 87.00 - lr: 0.050000
2020-09-16 02:16:41,120 epoch 88 - iter 174/585 - loss 0.18310884 - samples/sec: 91.73 - lr: 0.050000
2020-09-16 02:17:01,613 epoch 88 - iter 232/585 - loss 0.19116003 - samples/sec: 90.60 - lr: 0.050000
2020-09-16 02:17:22,533 epoch 88 - iter 290/585 - loss 0.19236039 - samples/sec: 88.76 - lr: 0.050000
2020-09-16 02:17:31,473 epoch 88 - iter 348/585 - loss 0.18965532 - samples/sec: 207.84 - lr: 0.050000
2020-09-16 02:17:46,585 epoch 88 - iter 406/585 - loss 0.19426474 - samples/sec: 122.88 - lr: 0.050000
2020-09-16 02:18:08,166 epoch 88 - iter 464/585 - loss 0.21371798 - samples/sec: 86.03 - lr: 0.050000
2020-09-16 02:18:28,797 epoch 88 - iter 522/585 - loss 0.20692644 - samples/sec: 90.00 - lr: 0.050000
2020-09-16 02:18:51,467 epoch 88 - iter 580/585 - loss 0.24185422 - samples/sec: 81.90 - lr: 0.050000
2020-09-16 02:18:53,151 ----------------------------------------------------------------------------------------------------
2020-09-16 02:18:53,151 EPOCH 88 done: loss 0.2416 - lr 0.0500000
2020-09-16 02:18:53,151 BAD EPOCHS (no improvement): 1
2020-09-16 02:18:53,158 ----------------------------------------------------------------------------------------------------
2020-09-16 02:19:12,778 epoch 89 - iter 58/585 - loss 0.18042755 - samples/sec: 94.65 - lr: 0.050000
2020-09-16 02:19:25,956 epoch 89 - iter 116/585 - loss 0.18018476 - samples/sec: 140.95 - lr: 0.050000
2020-09-16 02:19:34,371 epoch 89 - iter 174/585 - loss 0.19398483 - samples/sec: 220.83 - lr: 0.050000
2020-09-16 02:19:54,264 epoch 89 - iter 232/585 - loss 0.19603512 - samples/sec: 93.34 - lr: 0.050000
2020-09-16 02:20:16,377 epoch 89 - iter 290/585 - loss 0.22218023 - samples/sec: 83.96 - lr: 0.050000
2020-09-16 02:20:38,142 epoch 89 - iter 348/585 - loss 0.24023667 - samples/sec: 85.31 - lr: 0.050000
2020-09-16 02:20:56,386 epoch 89 - iter 406/585 - loss 0.23370334 - samples/sec: 101.78 - lr: 0.050000
2020-09-16 02:21:16,080 epoch 89 - iter 464/585 - loss 0.22719072 - samples/sec: 94.28 - lr: 0.050000
2020-09-16 02:21:28,063 epoch 89 - iter 522/585 - loss 0.22274079 - samples/sec: 155.03 - lr: 0.050000
2020-09-16 02:21:38,418 epoch 89 - iter 580/585 - loss 0.22973366 - samples/sec: 179.42 - lr: 0.050000
2020-09-16 02:21:40,028 ----------------------------------------------------------------------------------------------------
2020-09-16 02:21:40,029 EPOCH 89 done: loss 0.2301 - lr 0.0500000
2020-09-16 02:21:40,029 BAD EPOCHS (no improvement): 2
2020-09-16 02:21:40,033 ----------------------------------------------------------------------------------------------------
2020-09-16 02:22:00,737 epoch 90 - iter 58/585 - loss 0.14877194 - samples/sec: 89.68 - lr: 0.050000
2020-09-16 02:22:20,324 epoch 90 - iter 116/585 - loss 0.16762097 - samples/sec: 94.80 - lr: 0.050000
2020-09-16 02:22:41,560 epoch 90 - iter 174/585 - loss 0.18056946 - samples/sec: 87.43 - lr: 0.050000
2020-09-16 02:23:00,088 epoch 90 - iter 232/585 - loss 0.17649340 - samples/sec: 100.21 - lr: 0.050000
2020-09-16 02:23:20,202 epoch 90 - iter 290/585 - loss 0.17944431 - samples/sec: 92.31 - lr: 0.050000
2020-09-16 02:23:30,431 epoch 90 - iter 348/585 - loss 0.18041709 - samples/sec: 181.62 - lr: 0.050000
2020-09-16 02:23:38,463 epoch 90 - iter 406/585 - loss 0.18016165 - samples/sec: 231.35 - lr: 0.050000
2020-09-16 02:23:58,746 epoch 90 - iter 464/585 - loss 0.19126291 - samples/sec: 91.54 - lr: 0.050000
2020-09-16 02:24:20,886 epoch 90 - iter 522/585 - loss 0.22954099 - samples/sec: 83.86 - lr: 0.050000
2020-09-16 02:24:40,319 epoch 90 - iter 580/585 - loss 0.22606916 - samples/sec: 95.54 - lr: 0.050000
2020-09-16 02:24:41,923 ----------------------------------------------------------------------------------------------------
2020-09-16 02:24:41,924 EPOCH 90 done: loss 0.2256 - lr 0.0500000
2020-09-16 02:24:41,924 BAD EPOCHS (no improvement): 0
2020-09-16 02:24:41,928 ----------------------------------------------------------------------------------------------------
2020-09-16 02:25:03,092 epoch 91 - iter 58/585 - loss 0.35840732 - samples/sec: 87.74 - lr: 0.050000
2020-09-16 02:25:24,738 epoch 91 - iter 116/585 - loss 0.35864500 - samples/sec: 85.77 - lr: 0.050000
2020-09-16 02:25:35,357 epoch 91 - iter 174/585 - loss 0.30571910 - samples/sec: 174.94 - lr: 0.050000
2020-09-16 02:25:45,353 epoch 91 - iter 232/585 - loss 0.26948755 - samples/sec: 185.88 - lr: 0.050000
2020-09-16 02:26:06,770 epoch 91 - iter 290/585 - loss 0.27367718 - samples/sec: 86.69 - lr: 0.050000
2020-09-16 02:26:26,674 epoch 91 - iter 348/585 - loss 0.25816476 - samples/sec: 93.28 - lr: 0.050000
2020-09-16 02:26:46,370 epoch 91 - iter 406/585 - loss 0.24790954 - samples/sec: 94.27 - lr: 0.050000
2020-09-16 02:27:06,789 epoch 91 - iter 464/585 - loss 0.24121234 - samples/sec: 90.93 - lr: 0.050000
2020-09-16 02:27:27,443 epoch 91 - iter 522/585 - loss 0.23732317 - samples/sec: 89.90 - lr: 0.050000
2020-09-16 02:27:36,220 epoch 91 - iter 580/585 - loss 0.23068370 - samples/sec: 211.68 - lr: 0.050000
2020-09-16 02:27:37,070 ----------------------------------------------------------------------------------------------------
2020-09-16 02:27:37,071 EPOCH 91 done: loss 0.2305 - lr 0.0500000
2020-09-16 02:27:37,071 BAD EPOCHS (no improvement): 1
2020-09-16 02:27:37,074 ----------------------------------------------------------------------------------------------------
2020-09-16 02:27:48,239 epoch 92 - iter 58/585 - loss 0.25483955 - samples/sec: 166.40 - lr: 0.050000
2020-09-16 02:28:09,097 epoch 92 - iter 116/585 - loss 0.22467118 - samples/sec: 89.01 - lr: 0.050000
2020-09-16 02:28:29,381 epoch 92 - iter 174/585 - loss 0.21575631 - samples/sec: 91.54 - lr: 0.050000
2020-09-16 02:28:50,588 epoch 92 - iter 232/585 - loss 0.23681222 - samples/sec: 87.55 - lr: 0.050000
2020-09-16 02:29:10,352 epoch 92 - iter 290/585 - loss 0.22595143 - samples/sec: 93.95 - lr: 0.050000
2020-09-16 02:29:30,723 epoch 92 - iter 348/585 - loss 0.24049382 - samples/sec: 91.15 - lr: 0.050000
2020-09-16 02:29:39,115 epoch 92 - iter 406/585 - loss 0.23113596 - samples/sec: 221.40 - lr: 0.050000
2020-09-16 02:29:51,098 epoch 92 - iter 464/585 - loss 0.22391893 - samples/sec: 155.02 - lr: 0.050000
2020-09-16 02:30:11,871 epoch 92 - iter 522/585 - loss 0.21903183 - samples/sec: 89.38 - lr: 0.050000
2020-09-16 02:30:32,322 epoch 92 - iter 580/585 - loss 0.23235070 - samples/sec: 90.79 - lr: 0.050000
2020-09-16 02:30:34,025 ----------------------------------------------------------------------------------------------------
2020-09-16 02:30:34,025 EPOCH 92 done: loss 0.2317 - lr 0.0500000
2020-09-16 02:30:34,025 BAD EPOCHS (no improvement): 2
2020-09-16 02:30:34,028 ----------------------------------------------------------------------------------------------------
2020-09-16 02:30:55,265 epoch 93 - iter 58/585 - loss 0.39201949 - samples/sec: 87.43 - lr: 0.050000
2020-09-16 02:31:16,789 epoch 93 - iter 116/585 - loss 0.31675051 - samples/sec: 86.26 - lr: 0.050000
2020-09-16 02:31:33,651 epoch 93 - iter 174/585 - loss 0.26691843 - samples/sec: 110.12 - lr: 0.050000
2020-09-16 02:31:41,817 epoch 93 - iter 232/585 - loss 0.24620797 - samples/sec: 227.57 - lr: 0.050000
2020-09-16 02:31:56,900 epoch 93 - iter 290/585 - loss 0.23001857 - samples/sec: 123.12 - lr: 0.050000
2020-09-16 02:32:16,905 epoch 93 - iter 348/585 - loss 0.22116154 - samples/sec: 92.81 - lr: 0.050000
2020-09-16 02:32:37,961 epoch 93 - iter 406/585 - loss 0.23544183 - samples/sec: 88.18 - lr: 0.050000
2020-09-16 02:32:57,984 epoch 93 - iter 464/585 - loss 0.22934133 - samples/sec: 92.73 - lr: 0.050000
2020-09-16 02:33:17,817 epoch 93 - iter 522/585 - loss 0.22229742 - samples/sec: 93.62 - lr: 0.050000
2020-09-16 02:33:35,246 epoch 93 - iter 580/585 - loss 0.23048514 - samples/sec: 106.54 - lr: 0.050000
2020-09-16 02:33:35,747 ----------------------------------------------------------------------------------------------------
2020-09-16 02:33:35,748 EPOCH 93 done: loss 0.2293 - lr 0.0500000
2020-09-16 02:33:35,748 BAD EPOCHS (no improvement): 3
2020-09-16 02:33:35,753 ----------------------------------------------------------------------------------------------------
2020-09-16 02:33:43,832 epoch 94 - iter 58/585 - loss 0.18128147 - samples/sec: 230.07 - lr: 0.050000
2020-09-16 02:34:01,457 epoch 94 - iter 116/585 - loss 0.18298876 - samples/sec: 105.35 - lr: 0.050000
2020-09-16 02:34:22,232 epoch 94 - iter 174/585 - loss 0.22259867 - samples/sec: 89.37 - lr: 0.050000
2020-09-16 02:34:42,863 epoch 94 - iter 232/585 - loss 0.20751675 - samples/sec: 90.00 - lr: 0.050000
2020-09-16 02:35:03,779 epoch 94 - iter 290/585 - loss 0.20407044 - samples/sec: 88.77 - lr: 0.050000
2020-09-16 02:35:25,182 epoch 94 - iter 348/585 - loss 0.22318268 - samples/sec: 86.75 - lr: 0.050000
2020-09-16 02:35:37,915 epoch 94 - iter 406/585 - loss 0.23838411 - samples/sec: 145.87 - lr: 0.050000
2020-09-16 02:35:47,139 epoch 94 - iter 464/585 - loss 0.23549148 - samples/sec: 201.44 - lr: 0.050000
2020-09-16 02:36:06,974 epoch 94 - iter 522/585 - loss 0.22973833 - samples/sec: 93.61 - lr: 0.050000
2020-09-16 02:36:27,425 epoch 94 - iter 580/585 - loss 0.22408579 - samples/sec: 90.78 - lr: 0.050000
2020-09-16 02:36:29,082 ----------------------------------------------------------------------------------------------------
2020-09-16 02:36:29,083 EPOCH 94 done: loss 0.2252 - lr 0.0500000
2020-09-16 02:36:29,083 BAD EPOCHS (no improvement): 0
2020-09-16 02:36:29,089 ----------------------------------------------------------------------------------------------------
2020-09-16 02:36:50,599 epoch 95 - iter 58/585 - loss 0.17962351 - samples/sec: 86.33 - lr: 0.050000
2020-09-16 02:37:11,299 epoch 95 - iter 116/585 - loss 0.17292976 - samples/sec: 89.70 - lr: 0.050000
2020-09-16 02:37:31,651 epoch 95 - iter 174/585 - loss 0.17956319 - samples/sec: 91.23 - lr: 0.050000
2020-09-16 02:37:41,172 epoch 95 - iter 232/585 - loss 0.21499324 - samples/sec: 195.15 - lr: 0.050000
2020-09-16 02:37:53,056 epoch 95 - iter 290/585 - loss 0.20897236 - samples/sec: 156.30 - lr: 0.050000
2020-09-16 02:38:13,134 epoch 95 - iter 348/585 - loss 0.20727988 - samples/sec: 92.47 - lr: 0.050000
2020-09-16 02:38:34,561 epoch 95 - iter 406/585 - loss 0.22176367 - samples/sec: 86.65 - lr: 0.050000
2020-09-16 02:38:56,855 epoch 95 - iter 464/585 - loss 0.24365903 - samples/sec: 83.28 - lr: 0.050000
2020-09-16 02:39:14,969 epoch 95 - iter 522/585 - loss 0.23810292 - samples/sec: 102.51 - lr: 0.050000
2020-09-16 02:39:35,133 epoch 95 - iter 580/585 - loss 0.23136780 - samples/sec: 92.08 - lr: 0.050000
2020-09-16 02:39:35,621 ----------------------------------------------------------------------------------------------------
2020-09-16 02:39:35,621 EPOCH 95 done: loss 0.2313 - lr 0.0500000
2020-09-16 02:39:35,621 BAD EPOCHS (no improvement): 1
2020-09-16 02:39:35,627 ----------------------------------------------------------------------------------------------------
2020-09-16 02:39:43,792 epoch 96 - iter 58/585 - loss 0.16700222 - samples/sec: 227.62 - lr: 0.050000
2020-09-16 02:39:57,316 epoch 96 - iter 116/585 - loss 0.16500521 - samples/sec: 137.32 - lr: 0.050000
2020-09-16 02:40:17,474 epoch 96 - iter 174/585 - loss 0.18779284 - samples/sec: 92.11 - lr: 0.050000
2020-09-16 02:40:36,811 epoch 96 - iter 232/585 - loss 0.18841596 - samples/sec: 96.02 - lr: 0.050000
2020-09-16 02:40:56,969 epoch 96 - iter 290/585 - loss 0.18696955 - samples/sec: 92.10 - lr: 0.050000
2020-09-16 02:41:16,999 epoch 96 - iter 348/585 - loss 0.18635398 - samples/sec: 92.70 - lr: 0.050000
2020-09-16 02:41:36,446 epoch 96 - iter 406/585 - loss 0.18068339 - samples/sec: 95.47 - lr: 0.050000
2020-09-16 02:41:45,176 epoch 96 - iter 464/585 - loss 0.19565593 - samples/sec: 212.85 - lr: 0.050000
2020-09-16 02:42:00,571 epoch 96 - iter 522/585 - loss 0.21607549 - samples/sec: 120.63 - lr: 0.050000
2020-09-16 02:42:22,000 epoch 96 - iter 580/585 - loss 0.22413551 - samples/sec: 86.64 - lr: 0.050000
2020-09-16 02:42:23,535 ----------------------------------------------------------------------------------------------------
2020-09-16 02:42:23,535 EPOCH 96 done: loss 0.2237 - lr 0.0500000
2020-09-16 02:42:23,536 BAD EPOCHS (no improvement): 0
2020-09-16 02:42:23,858 ----------------------------------------------------------------------------------------------------
2020-09-16 02:42:44,135 epoch 97 - iter 58/585 - loss 0.28159582 - samples/sec: 91.58 - lr: 0.050000
2020-09-16 02:42:58,409 epoch 97 - iter 116/585 - loss 0.23727876 - samples/sec: 130.11 - lr: 0.050000
2020-09-16 02:43:18,965 epoch 97 - iter 174/585 - loss 0.21920570 - samples/sec: 90.32 - lr: 0.050000
2020-09-16 02:43:39,678 epoch 97 - iter 232/585 - loss 0.22094754 - samples/sec: 89.64 - lr: 0.050000
2020-09-16 02:43:48,735 epoch 97 - iter 290/585 - loss 0.21300543 - samples/sec: 205.18 - lr: 0.050000
2020-09-16 02:43:59,428 epoch 97 - iter 348/585 - loss 0.20353708 - samples/sec: 173.73 - lr: 0.050000
2020-09-16 02:44:20,618 epoch 97 - iter 406/585 - loss 0.21952102 - samples/sec: 87.62 - lr: 0.050000
2020-09-16 02:44:40,716 epoch 97 - iter 464/585 - loss 0.21747548 - samples/sec: 92.38 - lr: 0.050000
2020-09-16 02:45:00,963 epoch 97 - iter 522/585 - loss 0.23446623 - samples/sec: 91.70 - lr: 0.050000
2020-09-16 02:45:20,996 epoch 97 - iter 580/585 - loss 0.22633835 - samples/sec: 92.68 - lr: 0.050000
2020-09-16 02:45:22,622 ----------------------------------------------------------------------------------------------------
2020-09-16 02:45:22,622 EPOCH 97 done: loss 0.2262 - lr 0.0500000
2020-09-16 02:45:22,623 BAD EPOCHS (no improvement): 1
2020-09-16 02:45:22,626 ----------------------------------------------------------------------------------------------------
2020-09-16 02:45:42,781 epoch 98 - iter 58/585 - loss 0.19207466 - samples/sec: 92.13 - lr: 0.050000
2020-09-16 02:45:51,563 epoch 98 - iter 116/585 - loss 0.22553302 - samples/sec: 211.55 - lr: 0.050000
2020-09-16 02:46:07,909 epoch 98 - iter 174/585 - loss 0.25623838 - samples/sec: 113.60 - lr: 0.050000
2020-09-16 02:46:28,570 epoch 98 - iter 232/585 - loss 0.27229686 - samples/sec: 89.87 - lr: 0.050000
2020-09-16 02:46:48,855 epoch 98 - iter 290/585 - loss 0.26283289 - samples/sec: 91.53 - lr: 0.050000
2020-09-16 02:47:08,700 epoch 98 - iter 348/585 - loss 0.24597310 - samples/sec: 93.56 - lr: 0.050000
2020-09-16 02:47:28,218 epoch 98 - iter 406/585 - loss 0.23235372 - samples/sec: 95.13 - lr: 0.050000
2020-09-16 02:47:45,603 epoch 98 - iter 464/585 - loss 0.22649686 - samples/sec: 106.81 - lr: 0.050000
2020-09-16 02:47:53,607 epoch 98 - iter 522/585 - loss 0.22283342 - samples/sec: 232.14 - lr: 0.050000
2020-09-16 02:48:08,187 epoch 98 - iter 580/585 - loss 0.21790804 - samples/sec: 127.38 - lr: 0.050000
2020-09-16 02:48:09,812 ----------------------------------------------------------------------------------------------------
2020-09-16 02:48:09,812 EPOCH 98 done: loss 0.2182 - lr 0.0500000
2020-09-16 02:48:09,812 BAD EPOCHS (no improvement): 0
2020-09-16 02:48:09,818 ----------------------------------------------------------------------------------------------------
2020-09-16 02:48:30,094 epoch 99 - iter 58/585 - loss 0.19621872 - samples/sec: 91.58 - lr: 0.050000
2020-09-16 02:48:53,298 epoch 99 - iter 116/585 - loss 0.39603789 - samples/sec: 80.01 - lr: 0.050000
2020-09-16 02:49:13,168 epoch 99 - iter 174/585 - loss 0.31475714 - samples/sec: 93.45 - lr: 0.050000
2020-09-16 02:49:33,146 epoch 99 - iter 232/585 - loss 0.27408928 - samples/sec: 92.94 - lr: 0.050000
2020-09-16 02:49:47,883 epoch 99 - iter 290/585 - loss 0.25362298 - samples/sec: 126.02 - lr: 0.050000
2020-09-16 02:49:56,138 epoch 99 - iter 348/585 - loss 0.23876715 - samples/sec: 225.13 - lr: 0.050000
2020-09-16 02:50:14,001 epoch 99 - iter 406/585 - loss 0.23624836 - samples/sec: 103.95 - lr: 0.050000
2020-09-16 02:50:33,418 epoch 99 - iter 464/585 - loss 0.22758698 - samples/sec: 95.62 - lr: 0.050000
2020-09-16 02:50:53,383 epoch 99 - iter 522/585 - loss 0.22353615 - samples/sec: 93.01 - lr: 0.050000
2020-09-16 02:51:13,524 epoch 99 - iter 580/585 - loss 0.21699185 - samples/sec: 92.18 - lr: 0.050000
2020-09-16 02:51:15,187 ----------------------------------------------------------------------------------------------------
2020-09-16 02:51:15,187 EPOCH 99 done: loss 0.2159 - lr 0.0500000
2020-09-16 02:51:15,187 BAD EPOCHS (no improvement): 0
2020-09-16 02:51:15,192 ----------------------------------------------------------------------------------------------------
2020-09-16 02:51:32,730 epoch 100 - iter 58/585 - loss 0.26993444 - samples/sec: 105.89 - lr: 0.050000
2020-09-16 02:51:49,796 epoch 100 - iter 116/585 - loss 0.21845969 - samples/sec: 108.81 - lr: 0.050000
2020-09-16 02:51:59,023 epoch 100 - iter 174/585 - loss 0.26937363 - samples/sec: 201.37 - lr: 0.050000
2020-09-16 02:52:14,209 epoch 100 - iter 232/585 - loss 0.24443118 - samples/sec: 122.28 - lr: 0.050000
2020-09-16 02:52:34,059 epoch 100 - iter 290/585 - loss 0.22849062 - samples/sec: 93.54 - lr: 0.050000
2020-09-16 02:52:53,640 epoch 100 - iter 348/585 - loss 0.21563255 - samples/sec: 94.82 - lr: 0.050000
2020-09-16 02:53:14,601 epoch 100 - iter 406/585 - loss 0.23263029 - samples/sec: 88.58 - lr: 0.050000
2020-09-16 02:53:34,996 epoch 100 - iter 464/585 - loss 0.22300084 - samples/sec: 91.04 - lr: 0.050000
2020-09-16 02:53:51,871 epoch 100 - iter 522/585 - loss 0.21755839 - samples/sec: 110.04 - lr: 0.050000
2020-09-16 02:53:59,972 epoch 100 - iter 580/585 - loss 0.21115357 - samples/sec: 229.39 - lr: 0.050000
2020-09-16 02:54:00,511 ----------------------------------------------------------------------------------------------------
2020-09-16 02:54:00,511 EPOCH 100 done: loss 0.2110 - lr 0.0500000
2020-09-16 02:54:00,511 BAD EPOCHS (no improvement): 0
2020-09-16 02:54:00,516 ----------------------------------------------------------------------------------------------------
2020-09-16 02:54:16,473 epoch 101 - iter 58/585 - loss 0.12736058 - samples/sec: 116.39 - lr: 0.050000
2020-09-16 02:54:37,348 epoch 101 - iter 116/585 - loss 0.17761988 - samples/sec: 88.94 - lr: 0.050000
2020-09-16 02:54:57,419 epoch 101 - iter 174/585 - loss 0.17826884 - samples/sec: 92.51 - lr: 0.050000
2020-09-16 02:55:17,521 epoch 101 - iter 232/585 - loss 0.16964743 - samples/sec: 92.37 - lr: 0.050000
2020-09-16 02:55:37,616 epoch 101 - iter 290/585 - loss 0.16993018 - samples/sec: 92.40 - lr: 0.050000
2020-09-16 02:55:53,998 epoch 101 - iter 348/585 - loss 0.16808180 - samples/sec: 113.36 - lr: 0.050000
2020-09-16 02:56:03,359 epoch 101 - iter 406/585 - loss 0.19152365 - samples/sec: 198.52 - lr: 0.050000
2020-09-16 02:56:22,606 epoch 101 - iter 464/585 - loss 0.19077852 - samples/sec: 96.47 - lr: 0.050000
2020-09-16 02:56:43,002 epoch 101 - iter 522/585 - loss 0.19919246 - samples/sec: 91.04 - lr: 0.050000
2020-09-16 02:57:04,168 epoch 101 - iter 580/585 - loss 0.21270200 - samples/sec: 87.72 - lr: 0.050000
2020-09-16 02:57:05,632 ----------------------------------------------------------------------------------------------------
2020-09-16 02:57:05,632 EPOCH 101 done: loss 0.2118 - lr 0.0500000
2020-09-16 02:57:05,632 BAD EPOCHS (no improvement): 1
2020-09-16 02:57:05,638 ----------------------------------------------------------------------------------------------------
2020-09-16 02:57:25,917 epoch 102 - iter 58/585 - loss 0.16497841 - samples/sec: 91.56 - lr: 0.050000
2020-09-16 02:57:47,168 epoch 102 - iter 116/585 - loss 0.19031306 - samples/sec: 87.37 - lr: 0.050000
2020-09-16 02:57:58,514 epoch 102 - iter 174/585 - loss 0.17954808 - samples/sec: 163.72 - lr: 0.050000
2020-09-16 02:58:06,472 epoch 102 - iter 232/585 - loss 0.17500706 - samples/sec: 233.51 - lr: 0.050000
2020-09-16 02:58:26,563 epoch 102 - iter 290/585 - loss 0.16703013 - samples/sec: 92.42 - lr: 0.050000
2020-09-16 02:58:58,121 epoch 102 - iter 348/585 - loss 0.16582888 - samples/sec: 58.83 - lr: 0.050000
2020-09-16 02:59:30,539 epoch 102 - iter 406/585 - loss 0.17868696 - samples/sec: 57.27 - lr: 0.050000
2020-09-16 03:00:03,567 epoch 102 - iter 464/585 - loss 0.20085434 - samples/sec: 56.21 - lr: 0.050000
2020-09-16 03:00:23,396 epoch 102 - iter 522/585 - loss 0.21046327 - samples/sec: 93.65 - lr: 0.050000
2020-09-16 03:00:36,282 epoch 102 - iter 580/585 - loss 0.20609604 - samples/sec: 144.12 - lr: 0.050000
2020-09-16 03:00:36,802 ----------------------------------------------------------------------------------------------------
2020-09-16 03:00:36,802 EPOCH 102 done: loss 0.2057 - lr 0.0500000
2020-09-16 03:00:36,802 BAD EPOCHS (no improvement): 0
2020-09-16 03:00:36,808 ----------------------------------------------------------------------------------------------------
2020-09-16 03:01:02,370 epoch 103 - iter 58/585 - loss 0.34161739 - samples/sec: 72.65 - lr: 0.050000
2020-09-16 03:01:35,472 epoch 103 - iter 116/585 - loss 0.34461702 - samples/sec: 56.08 - lr: 0.050000
2020-09-16 03:02:08,380 epoch 103 - iter 174/585 - loss 0.31534460 - samples/sec: 56.41 - lr: 0.050000
2020-09-16 03:02:39,976 epoch 103 - iter 232/585 - loss 0.28221771 - samples/sec: 58.76 - lr: 0.050000
2020-09-16 03:02:55,383 epoch 103 - iter 290/585 - loss 0.25571990 - samples/sec: 120.54 - lr: 0.050000
2020-09-16 03:03:07,324 epoch 103 - iter 348/585 - loss 0.24312888 - samples/sec: 155.55 - lr: 0.050000
2020-09-16 03:03:30,571 epoch 103 - iter 406/585 - loss 0.22976210 - samples/sec: 79.87 - lr: 0.050000
2020-09-16 03:04:01,902 epoch 103 - iter 464/585 - loss 0.22393246 - samples/sec: 59.25 - lr: 0.050000
2020-09-16 03:04:33,209 epoch 103 - iter 522/585 - loss 0.21534215 - samples/sec: 59.30 - lr: 0.050000
2020-09-16 03:05:04,758 epoch 103 - iter 580/585 - loss 0.20834744 - samples/sec: 58.84 - lr: 0.050000
2020-09-16 03:05:07,205 ----------------------------------------------------------------------------------------------------
2020-09-16 03:05:07,205 EPOCH 103 done: loss 0.2087 - lr 0.0500000
2020-09-16 03:05:07,205 BAD EPOCHS (no improvement): 1
2020-09-16 03:05:07,209 ----------------------------------------------------------------------------------------------------
2020-09-16 03:05:23,894 epoch 104 - iter 58/585 - loss 0.16638896 - samples/sec: 111.31 - lr: 0.050000
2020-09-16 03:05:36,366 epoch 104 - iter 116/585 - loss 0.15891830 - samples/sec: 148.92 - lr: 0.050000
2020-09-16 03:05:58,763 epoch 104 - iter 174/585 - loss 0.18413942 - samples/sec: 82.90 - lr: 0.050000
2020-09-16 03:06:30,364 epoch 104 - iter 232/585 - loss 0.17948383 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 03:07:02,223 epoch 104 - iter 290/585 - loss 0.17664631 - samples/sec: 58.27 - lr: 0.050000
2020-09-16 03:07:33,760 epoch 104 - iter 348/585 - loss 0.17688392 - samples/sec: 58.87 - lr: 0.050000
2020-09-16 03:07:51,596 epoch 104 - iter 406/585 - loss 0.17538939 - samples/sec: 104.11 - lr: 0.050000
2020-09-16 03:08:05,367 epoch 104 - iter 464/585 - loss 0.19070400 - samples/sec: 134.86 - lr: 0.050000
2020-09-16 03:08:18,845 epoch 104 - iter 522/585 - loss 0.18522570 - samples/sec: 137.80 - lr: 0.050000
2020-09-16 03:08:53,271 epoch 104 - iter 580/585 - loss 0.20937979 - samples/sec: 53.93 - lr: 0.050000
2020-09-16 03:08:55,841 ----------------------------------------------------------------------------------------------------
2020-09-16 03:08:55,841 EPOCH 104 done: loss 0.2086 - lr 0.0500000
2020-09-16 03:08:55,841 BAD EPOCHS (no improvement): 2
2020-09-16 03:08:55,844 ----------------------------------------------------------------------------------------------------
2020-09-16 03:09:27,354 epoch 105 - iter 58/585 - loss 0.12716629 - samples/sec: 58.92 - lr: 0.050000
2020-09-16 03:09:58,716 epoch 105 - iter 116/585 - loss 0.14568471 - samples/sec: 59.20 - lr: 0.050000
2020-09-16 03:10:21,177 epoch 105 - iter 174/585 - loss 0.15476144 - samples/sec: 82.67 - lr: 0.050000
2020-09-16 03:10:34,682 epoch 105 - iter 232/585 - loss 0.15402046 - samples/sec: 137.52 - lr: 0.050000
2020-09-16 03:10:47,111 epoch 105 - iter 290/585 - loss 0.15633317 - samples/sec: 149.44 - lr: 0.050000
2020-09-16 03:11:20,738 epoch 105 - iter 348/585 - loss 0.19285984 - samples/sec: 55.21 - lr: 0.050000
2020-09-16 03:11:52,228 epoch 105 - iter 406/585 - loss 0.19027687 - samples/sec: 58.96 - lr: 0.050000
2020-09-16 03:12:23,742 epoch 105 - iter 464/585 - loss 0.18792741 - samples/sec: 58.91 - lr: 0.050000
2020-09-16 03:12:51,035 epoch 105 - iter 522/585 - loss 0.19582624 - samples/sec: 68.03 - lr: 0.050000
2020-09-16 03:13:04,945 epoch 105 - iter 580/585 - loss 0.20569801 - samples/sec: 133.51 - lr: 0.050000
2020-09-16 03:13:05,512 ----------------------------------------------------------------------------------------------------
2020-09-16 03:13:05,512 EPOCH 105 done: loss 0.2057 - lr 0.0500000
2020-09-16 03:13:05,512 BAD EPOCHS (no improvement): 0
2020-09-16 03:13:05,518 ----------------------------------------------------------------------------------------------------
2020-09-16 03:13:25,326 epoch 106 - iter 58/585 - loss 0.26706785 - samples/sec: 93.75 - lr: 0.050000
2020-09-16 03:13:56,828 epoch 106 - iter 116/585 - loss 0.21457287 - samples/sec: 58.93 - lr: 0.050000
2020-09-16 03:14:30,512 epoch 106 - iter 174/585 - loss 0.26697704 - samples/sec: 55.11 - lr: 0.050000
2020-09-16 03:15:02,115 epoch 106 - iter 232/585 - loss 0.24333962 - samples/sec: 58.74 - lr: 0.050000
2020-09-16 03:15:22,597 epoch 106 - iter 290/585 - loss 0.25950966 - samples/sec: 90.66 - lr: 0.050000
2020-09-16 03:15:36,006 epoch 106 - iter 348/585 - loss 0.24360293 - samples/sec: 138.50 - lr: 0.050000
2020-09-16 03:15:56,048 epoch 106 - iter 406/585 - loss 0.23648168 - samples/sec: 92.65 - lr: 0.050000
2020-09-16 03:16:27,554 epoch 106 - iter 464/585 - loss 0.22405264 - samples/sec: 58.92 - lr: 0.050000
2020-09-16 03:16:59,127 epoch 106 - iter 522/585 - loss 0.21745449 - samples/sec: 58.80 - lr: 0.050000
2020-09-16 03:17:30,696 epoch 106 - iter 580/585 - loss 0.21213477 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 03:17:33,307 ----------------------------------------------------------------------------------------------------
2020-09-16 03:17:33,308 EPOCH 106 done: loss 0.2116 - lr 0.0500000
2020-09-16 03:17:33,308 BAD EPOCHS (no improvement): 1
2020-09-16 03:17:33,311 ----------------------------------------------------------------------------------------------------
2020-09-16 03:17:51,791 epoch 107 - iter 58/585 - loss 0.19487793 - samples/sec: 100.49 - lr: 0.050000
2020-09-16 03:18:05,219 epoch 107 - iter 116/585 - loss 0.17450105 - samples/sec: 138.31 - lr: 0.050000
2020-09-16 03:18:25,766 epoch 107 - iter 174/585 - loss 0.21108907 - samples/sec: 90.37 - lr: 0.050000
2020-09-16 03:18:57,334 epoch 107 - iter 232/585 - loss 0.19284136 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 03:19:28,673 epoch 107 - iter 290/585 - loss 0.18561957 - samples/sec: 59.24 - lr: 0.050000
2020-09-16 03:20:00,259 epoch 107 - iter 348/585 - loss 0.18395077 - samples/sec: 58.78 - lr: 0.050000
2020-09-16 03:20:22,669 epoch 107 - iter 406/585 - loss 0.22527168 - samples/sec: 82.86 - lr: 0.050000
2020-09-16 03:20:35,220 epoch 107 - iter 464/585 - loss 0.21768109 - samples/sec: 147.98 - lr: 0.050000
2020-09-16 03:20:57,624 epoch 107 - iter 522/585 - loss 0.21168378 - samples/sec: 82.87 - lr: 0.050000
2020-09-16 03:21:29,182 epoch 107 - iter 580/585 - loss 0.20795009 - samples/sec: 58.83 - lr: 0.050000
2020-09-16 03:21:31,619 ----------------------------------------------------------------------------------------------------
2020-09-16 03:21:31,620 EPOCH 107 done: loss 0.2073 - lr 0.0500000
2020-09-16 03:21:31,620 BAD EPOCHS (no improvement): 2
2020-09-16 03:21:31,623 ----------------------------------------------------------------------------------------------------
2020-09-16 03:22:02,684 epoch 108 - iter 58/585 - loss 0.15141304 - samples/sec: 59.77 - lr: 0.050000
2020-09-16 03:22:34,194 epoch 108 - iter 116/585 - loss 0.14799356 - samples/sec: 58.92 - lr: 0.050000
2020-09-16 03:22:51,931 epoch 108 - iter 174/585 - loss 0.16289585 - samples/sec: 104.70 - lr: 0.050000
2020-09-16 03:23:04,596 epoch 108 - iter 232/585 - loss 0.16047655 - samples/sec: 146.64 - lr: 0.050000
2020-09-16 03:23:26,815 epoch 108 - iter 290/585 - loss 0.16352468 - samples/sec: 83.57 - lr: 0.050000
2020-09-16 03:24:01,290 epoch 108 - iter 348/585 - loss 0.20666163 - samples/sec: 53.85 - lr: 0.050000
2020-09-16 03:24:32,791 epoch 108 - iter 406/585 - loss 0.20352855 - samples/sec: 58.93 - lr: 0.050000
2020-09-16 03:25:05,712 epoch 108 - iter 464/585 - loss 0.21782480 - samples/sec: 56.39 - lr: 0.050000
2020-09-16 03:25:21,742 epoch 108 - iter 522/585 - loss 0.21127812 - samples/sec: 115.85 - lr: 0.050000
2020-09-16 03:25:34,359 epoch 108 - iter 580/585 - loss 0.20653314 - samples/sec: 147.20 - lr: 0.050000
2020-09-16 03:25:34,918 ----------------------------------------------------------------------------------------------------
2020-09-16 03:25:34,918 EPOCH 108 done: loss 0.2058 - lr 0.0500000
2020-09-16 03:25:34,918 BAD EPOCHS (no improvement): 3
2020-09-16 03:25:34,922 ----------------------------------------------------------------------------------------------------
2020-09-16 03:26:02,258 epoch 109 - iter 58/585 - loss 0.25891489 - samples/sec: 67.92 - lr: 0.050000
2020-09-16 03:26:35,194 epoch 109 - iter 116/585 - loss 0.26136786 - samples/sec: 56.37 - lr: 0.050000
2020-09-16 03:27:06,749 epoch 109 - iter 174/585 - loss 0.23017140 - samples/sec: 58.83 - lr: 0.050000
2020-09-16 03:27:38,382 epoch 109 - iter 232/585 - loss 0.21451328 - samples/sec: 58.69 - lr: 0.050000
2020-09-16 03:27:52,818 epoch 109 - iter 290/585 - loss 0.20071338 - samples/sec: 128.65 - lr: 0.050000
2020-09-16 03:28:04,522 epoch 109 - iter 348/585 - loss 0.19153790 - samples/sec: 158.70 - lr: 0.050000
2020-09-16 03:28:30,490 epoch 109 - iter 406/585 - loss 0.18688240 - samples/sec: 71.50 - lr: 0.050000
2020-09-16 03:29:02,454 epoch 109 - iter 464/585 - loss 0.18900668 - samples/sec: 58.08 - lr: 0.050000
2020-09-16 03:29:35,539 epoch 109 - iter 522/585 - loss 0.20193473 - samples/sec: 56.11 - lr: 0.050000
2020-09-16 03:30:07,108 epoch 109 - iter 580/585 - loss 0.19908118 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 03:30:09,601 ----------------------------------------------------------------------------------------------------
2020-09-16 03:30:09,601 EPOCH 109 done: loss 0.1983 - lr 0.0500000
2020-09-16 03:30:09,601 BAD EPOCHS (no improvement): 0
2020-09-16 03:30:09,606 ----------------------------------------------------------------------------------------------------
2020-09-16 03:30:22,962 epoch 110 - iter 58/585 - loss 0.16085070 - samples/sec: 139.08 - lr: 0.050000
2020-09-16 03:30:34,169 epoch 110 - iter 116/585 - loss 0.15699110 - samples/sec: 165.74 - lr: 0.050000
2020-09-16 03:31:02,766 epoch 110 - iter 174/585 - loss 0.19898682 - samples/sec: 64.92 - lr: 0.050000
2020-09-16 03:31:35,642 epoch 110 - iter 232/585 - loss 0.22705137 - samples/sec: 56.47 - lr: 0.050000
2020-09-16 03:32:07,162 epoch 110 - iter 290/585 - loss 0.21673789 - samples/sec: 58.90 - lr: 0.050000
2020-09-16 03:32:38,999 epoch 110 - iter 348/585 - loss 0.20681215 - samples/sec: 58.31 - lr: 0.050000
2020-09-16 03:32:54,209 epoch 110 - iter 406/585 - loss 0.22418459 - samples/sec: 122.10 - lr: 0.050000
2020-09-16 03:33:04,470 epoch 110 - iter 464/585 - loss 0.21741202 - samples/sec: 181.06 - lr: 0.050000
2020-09-16 03:33:31,088 epoch 110 - iter 522/585 - loss 0.20999083 - samples/sec: 69.75 - lr: 0.050000
2020-09-16 03:34:02,673 epoch 110 - iter 580/585 - loss 0.20276530 - samples/sec: 58.78 - lr: 0.050000
2020-09-16 03:34:05,273 ----------------------------------------------------------------------------------------------------
2020-09-16 03:34:05,274 EPOCH 110 done: loss 0.2019 - lr 0.0500000
2020-09-16 03:34:05,274 BAD EPOCHS (no improvement): 1
2020-09-16 03:34:05,277 ----------------------------------------------------------------------------------------------------
2020-09-16 03:34:37,723 epoch 111 - iter 58/585 - loss 0.18752654 - samples/sec: 57.22 - lr: 0.050000
2020-09-16 03:35:09,247 epoch 111 - iter 116/585 - loss 0.16501749 - samples/sec: 58.89 - lr: 0.050000
2020-09-16 03:35:23,274 epoch 111 - iter 174/585 - loss 0.19543376 - samples/sec: 132.41 - lr: 0.050000
2020-09-16 03:35:34,586 epoch 111 - iter 232/585 - loss 0.22400580 - samples/sec: 164.20 - lr: 0.050000
2020-09-16 03:36:04,637 epoch 111 - iter 290/585 - loss 0.21354277 - samples/sec: 61.78 - lr: 0.050000
2020-09-16 03:36:36,327 epoch 111 - iter 348/585 - loss 0.20473020 - samples/sec: 58.58 - lr: 0.050000
2020-09-16 03:37:07,836 epoch 111 - iter 406/585 - loss 0.19663869 - samples/sec: 58.92 - lr: 0.050000
2020-09-16 03:37:40,218 epoch 111 - iter 464/585 - loss 0.20925889 - samples/sec: 57.33 - lr: 0.050000
2020-09-16 03:37:52,462 epoch 111 - iter 522/585 - loss 0.20469330 - samples/sec: 151.71 - lr: 0.050000
2020-09-16 03:38:03,106 epoch 111 - iter 580/585 - loss 0.19826021 - samples/sec: 174.51 - lr: 0.050000
2020-09-16 03:38:03,655 ----------------------------------------------------------------------------------------------------
2020-09-16 03:38:03,656 EPOCH 111 done: loss 0.1975 - lr 0.0500000
2020-09-16 03:38:03,656 BAD EPOCHS (no improvement): 0
2020-09-16 03:38:03,665 ----------------------------------------------------------------------------------------------------
2020-09-16 03:38:34,113 epoch 112 - iter 58/585 - loss 0.13395009 - samples/sec: 60.98 - lr: 0.050000
2020-09-16 03:39:06,815 epoch 112 - iter 116/585 - loss 0.22880252 - samples/sec: 56.77 - lr: 0.050000
2020-09-16 03:39:38,179 epoch 112 - iter 174/585 - loss 0.20045073 - samples/sec: 59.19 - lr: 0.050000
2020-09-16 03:40:09,636 epoch 112 - iter 232/585 - loss 0.18451455 - samples/sec: 59.02 - lr: 0.050000
2020-09-16 03:40:22,303 epoch 112 - iter 290/585 - loss 0.18246672 - samples/sec: 146.64 - lr: 0.050000
2020-09-16 03:40:32,656 epoch 112 - iter 348/585 - loss 0.17981756 - samples/sec: 179.45 - lr: 0.050000
2020-09-16 03:41:03,137 epoch 112 - iter 406/585 - loss 0.17304420 - samples/sec: 60.91 - lr: 0.050000
2020-09-16 03:41:37,640 epoch 112 - iter 464/585 - loss 0.20493705 - samples/sec: 53.80 - lr: 0.050000
2020-09-16 03:42:09,205 epoch 112 - iter 522/585 - loss 0.20095999 - samples/sec: 58.82 - lr: 0.050000
2020-09-16 03:42:40,832 epoch 112 - iter 580/585 - loss 0.19478131 - samples/sec: 58.70 - lr: 0.050000
2020-09-16 03:42:42,623 ----------------------------------------------------------------------------------------------------
2020-09-16 03:42:42,623 EPOCH 112 done: loss 0.1940 - lr 0.0500000
2020-09-16 03:42:42,623 BAD EPOCHS (no improvement): 0
2020-09-16 03:42:42,631 ----------------------------------------------------------------------------------------------------
2020-09-16 03:42:53,364 epoch 113 - iter 58/585 - loss 0.14306584 - samples/sec: 173.11 - lr: 0.050000
2020-09-16 03:43:06,893 epoch 113 - iter 116/585 - loss 0.27168178 - samples/sec: 137.29 - lr: 0.050000
2020-09-16 03:43:38,546 epoch 113 - iter 174/585 - loss 0.23540722 - samples/sec: 58.65 - lr: 0.050000
2020-09-16 03:44:09,824 epoch 113 - iter 232/585 - loss 0.21419393 - samples/sec: 59.35 - lr: 0.050000
2020-09-16 03:44:43,092 epoch 113 - iter 290/585 - loss 0.23494175 - samples/sec: 55.80 - lr: 0.050000
2020-09-16 03:45:12,573 epoch 113 - iter 348/585 - loss 0.21926956 - samples/sec: 62.97 - lr: 0.050000
2020-09-16 03:45:23,383 epoch 113 - iter 406/585 - loss 0.21165134 - samples/sec: 171.85 - lr: 0.050000
2020-09-16 03:45:35,591 epoch 113 - iter 464/585 - loss 0.20897489 - samples/sec: 152.14 - lr: 0.050000
2020-09-16 03:46:07,011 epoch 113 - iter 522/585 - loss 0.20425653 - samples/sec: 59.09 - lr: 0.050000
2020-09-16 03:46:38,580 epoch 113 - iter 580/585 - loss 0.19869227 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 03:46:41,056 ----------------------------------------------------------------------------------------------------
2020-09-16 03:46:41,057 EPOCH 113 done: loss 0.1979 - lr 0.0500000
2020-09-16 03:46:41,057 BAD EPOCHS (no improvement): 1
2020-09-16 03:46:41,060 ----------------------------------------------------------------------------------------------------
2020-09-16 03:47:12,577 epoch 114 - iter 58/585 - loss 0.14737761 - samples/sec: 58.91 - lr: 0.050000
2020-09-16 03:47:42,435 epoch 114 - iter 116/585 - loss 0.20593398 - samples/sec: 62.18 - lr: 0.050000
2020-09-16 03:47:53,540 epoch 114 - iter 174/585 - loss 0.18739314 - samples/sec: 167.28 - lr: 0.050000
2020-09-16 03:48:05,392 epoch 114 - iter 232/585 - loss 0.18324396 - samples/sec: 156.72 - lr: 0.050000
2020-09-16 03:48:36,967 epoch 114 - iter 290/585 - loss 0.18120445 - samples/sec: 58.80 - lr: 0.050000
2020-09-16 03:49:08,532 epoch 114 - iter 348/585 - loss 0.17318277 - samples/sec: 58.81 - lr: 0.050000
2020-09-16 03:49:40,993 epoch 114 - iter 406/585 - loss 0.18988970 - samples/sec: 57.19 - lr: 0.050000
2020-09-16 03:50:11,626 epoch 114 - iter 464/585 - loss 0.19240942 - samples/sec: 60.61 - lr: 0.050000
2020-09-16 03:50:22,611 epoch 114 - iter 522/585 - loss 0.18806549 - samples/sec: 169.10 - lr: 0.050000
2020-09-16 03:50:37,212 epoch 114 - iter 580/585 - loss 0.20325386 - samples/sec: 127.19 - lr: 0.050000
2020-09-16 03:50:39,621 ----------------------------------------------------------------------------------------------------
2020-09-16 03:50:39,621 EPOCH 114 done: loss 0.2032 - lr 0.0500000
2020-09-16 03:50:39,621 BAD EPOCHS (no improvement): 2
2020-09-16 03:50:39,628 ----------------------------------------------------------------------------------------------------
2020-09-16 03:51:12,187 epoch 115 - iter 58/585 - loss 0.31193477 - samples/sec: 57.02 - lr: 0.050000
2020-09-16 03:51:43,855 epoch 115 - iter 116/585 - loss 0.23539732 - samples/sec: 58.62 - lr: 0.050000
2020-09-16 03:52:15,690 epoch 115 - iter 174/585 - loss 0.21308803 - samples/sec: 58.32 - lr: 0.050000
2020-09-16 03:52:41,767 epoch 115 - iter 232/585 - loss 0.19183687 - samples/sec: 71.20 - lr: 0.050000
2020-09-16 03:52:54,287 epoch 115 - iter 290/585 - loss 0.18488154 - samples/sec: 148.35 - lr: 0.050000
2020-09-16 03:53:08,042 epoch 115 - iter 348/585 - loss 0.18433641 - samples/sec: 135.02 - lr: 0.050000
2020-09-16 03:53:40,713 epoch 115 - iter 406/585 - loss 0.19397371 - samples/sec: 56.82 - lr: 0.050000
2020-09-16 03:54:12,392 epoch 115 - iter 464/585 - loss 0.19006269 - samples/sec: 58.60 - lr: 0.050000
2020-09-16 03:54:44,297 epoch 115 - iter 522/585 - loss 0.18658997 - samples/sec: 58.19 - lr: 0.050000
2020-09-16 03:55:11,949 epoch 115 - iter 580/585 - loss 0.20382145 - samples/sec: 67.14 - lr: 0.050000
2020-09-16 03:55:12,452 ----------------------------------------------------------------------------------------------------
2020-09-16 03:55:12,452 EPOCH 115 done: loss 0.2038 - lr 0.0500000
2020-09-16 03:55:12,452 BAD EPOCHS (no improvement): 3
2020-09-16 03:55:12,455 ----------------------------------------------------------------------------------------------------
2020-09-16 03:55:25,886 epoch 116 - iter 58/585 - loss 0.13910995 - samples/sec: 138.29 - lr: 0.050000
2020-09-16 03:55:47,006 epoch 116 - iter 116/585 - loss 0.14434249 - samples/sec: 87.92 - lr: 0.050000
2020-09-16 03:56:18,613 epoch 116 - iter 174/585 - loss 0.14657817 - samples/sec: 58.74 - lr: 0.050000
2020-09-16 03:56:50,085 epoch 116 - iter 232/585 - loss 0.14971831 - samples/sec: 58.99 - lr: 0.050000
2020-09-16 03:57:21,576 epoch 116 - iter 290/585 - loss 0.14606188 - samples/sec: 58.95 - lr: 0.050000
2020-09-16 03:57:42,110 epoch 116 - iter 348/585 - loss 0.15380128 - samples/sec: 90.44 - lr: 0.050000
2020-09-16 03:57:56,694 epoch 116 - iter 406/585 - loss 0.18647932 - samples/sec: 127.33 - lr: 0.050000
2020-09-16 03:58:23,051 epoch 116 - iter 464/585 - loss 0.18135915 - samples/sec: 70.44 - lr: 0.050000
2020-09-16 03:58:55,787 epoch 116 - iter 522/585 - loss 0.19116512 - samples/sec: 56.71 - lr: 0.050000
2020-09-16 03:59:27,123 epoch 116 - iter 580/585 - loss 0.18561699 - samples/sec: 59.25 - lr: 0.050000
2020-09-16 03:59:29,716 ----------------------------------------------------------------------------------------------------
2020-09-16 03:59:29,717 EPOCH 116 done: loss 0.1862 - lr 0.0500000
2020-09-16 03:59:29,717 BAD EPOCHS (no improvement): 0
2020-09-16 03:59:29,720 ----------------------------------------------------------------------------------------------------
2020-09-16 04:00:01,321 epoch 117 - iter 58/585 - loss 0.15500627 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 04:00:16,415 epoch 117 - iter 116/585 - loss 0.22417978 - samples/sec: 123.04 - lr: 0.050000
2020-09-16 04:00:27,561 epoch 117 - iter 174/585 - loss 0.23098182 - samples/sec: 166.66 - lr: 0.050000
2020-09-16 04:00:58,969 epoch 117 - iter 232/585 - loss 0.20761897 - samples/sec: 59.11 - lr: 0.050000
2020-09-16 04:01:30,293 epoch 117 - iter 290/585 - loss 0.19466687 - samples/sec: 59.27 - lr: 0.050000
2020-09-16 04:02:01,898 epoch 117 - iter 348/585 - loss 0.18985176 - samples/sec: 58.74 - lr: 0.050000
2020-09-16 04:02:33,857 epoch 117 - iter 406/585 - loss 0.18627188 - samples/sec: 58.09 - lr: 0.050000
2020-09-16 04:02:45,833 epoch 117 - iter 464/585 - loss 0.18226155 - samples/sec: 155.11 - lr: 0.050000
2020-09-16 04:02:56,781 epoch 117 - iter 522/585 - loss 0.19584863 - samples/sec: 169.67 - lr: 0.050000
2020-09-16 04:03:28,237 epoch 117 - iter 580/585 - loss 0.19459647 - samples/sec: 59.02 - lr: 0.050000
2020-09-16 04:03:30,820 ----------------------------------------------------------------------------------------------------
2020-09-16 04:03:30,820 EPOCH 117 done: loss 0.1936 - lr 0.0500000
2020-09-16 04:03:30,820 BAD EPOCHS (no improvement): 1
2020-09-16 04:03:30,844 ----------------------------------------------------------------------------------------------------
2020-09-16 04:04:02,200 epoch 118 - iter 58/585 - loss 0.13207474 - samples/sec: 59.21 - lr: 0.050000
2020-09-16 04:04:34,459 epoch 118 - iter 116/585 - loss 0.15694147 - samples/sec: 57.55 - lr: 0.050000
2020-09-16 04:05:06,531 epoch 118 - iter 174/585 - loss 0.19350770 - samples/sec: 57.88 - lr: 0.050000
2020-09-16 04:05:17,418 epoch 118 - iter 232/585 - loss 0.18338636 - samples/sec: 170.65 - lr: 0.050000
2020-09-16 04:05:27,732 epoch 118 - iter 290/585 - loss 0.17499897 - samples/sec: 180.11 - lr: 0.050000
2020-09-16 04:06:01,698 epoch 118 - iter 348/585 - loss 0.21948803 - samples/sec: 54.65 - lr: 0.050000
2020-09-16 04:06:33,337 epoch 118 - iter 406/585 - loss 0.20995066 - samples/sec: 58.68 - lr: 0.050000
2020-09-16 04:07:04,815 epoch 118 - iter 464/585 - loss 0.19982989 - samples/sec: 58.98 - lr: 0.050000
2020-09-16 04:07:35,859 epoch 118 - iter 522/585 - loss 0.19272127 - samples/sec: 59.80 - lr: 0.050000
2020-09-16 04:07:46,502 epoch 118 - iter 580/585 - loss 0.18714033 - samples/sec: 174.54 - lr: 0.050000
2020-09-16 04:07:47,692 ----------------------------------------------------------------------------------------------------
2020-09-16 04:07:47,693 EPOCH 118 done: loss 0.1875 - lr 0.0500000
2020-09-16 04:07:47,693 BAD EPOCHS (no improvement): 2
2020-09-16 04:07:47,698 ----------------------------------------------------------------------------------------------------
2020-09-16 04:08:02,048 epoch 119 - iter 58/585 - loss 0.27037587 - samples/sec: 129.43 - lr: 0.050000
2020-09-16 04:08:33,552 epoch 119 - iter 116/585 - loss 0.19812594 - samples/sec: 58.93 - lr: 0.050000
2020-09-16 04:09:04,811 epoch 119 - iter 174/585 - loss 0.18500970 - samples/sec: 59.39 - lr: 0.050000
2020-09-16 04:09:36,427 epoch 119 - iter 232/585 - loss 0.17529209 - samples/sec: 58.72 - lr: 0.050000
2020-09-16 04:10:05,460 epoch 119 - iter 290/585 - loss 0.16817166 - samples/sec: 63.94 - lr: 0.050000
2020-09-16 04:10:17,212 epoch 119 - iter 348/585 - loss 0.17363544 - samples/sec: 158.04 - lr: 0.050000
2020-09-16 04:10:32,686 epoch 119 - iter 406/585 - loss 0.18999117 - samples/sec: 120.02 - lr: 0.050000
2020-09-16 04:11:04,232 epoch 119 - iter 464/585 - loss 0.18399690 - samples/sec: 58.85 - lr: 0.050000
2020-09-16 04:11:35,823 epoch 119 - iter 522/585 - loss 0.18060467 - samples/sec: 58.77 - lr: 0.050000
2020-09-16 04:12:08,182 epoch 119 - iter 580/585 - loss 0.18132488 - samples/sec: 57.37 - lr: 0.050000
2020-09-16 04:12:10,783 ----------------------------------------------------------------------------------------------------
2020-09-16 04:12:10,783 EPOCH 119 done: loss 0.1815 - lr 0.0500000
2020-09-16 04:12:10,783 BAD EPOCHS (no improvement): 0
2020-09-16 04:12:10,789 ----------------------------------------------------------------------------------------------------
2020-09-16 04:12:36,205 epoch 120 - iter 58/585 - loss 0.15376148 - samples/sec: 73.05 - lr: 0.050000
2020-09-16 04:12:48,856 epoch 120 - iter 116/585 - loss 0.14001351 - samples/sec: 146.81 - lr: 0.050000
2020-09-16 04:13:03,099 epoch 120 - iter 174/585 - loss 0.20280236 - samples/sec: 130.38 - lr: 0.050000
2020-09-16 04:13:34,685 epoch 120 - iter 232/585 - loss 0.18771761 - samples/sec: 58.78 - lr: 0.050000
2020-09-16 04:14:06,245 epoch 120 - iter 290/585 - loss 0.17879355 - samples/sec: 58.82 - lr: 0.050000
2020-09-16 04:14:39,838 epoch 120 - iter 348/585 - loss 0.20061455 - samples/sec: 55.26 - lr: 0.050000
2020-09-16 04:15:06,050 epoch 120 - iter 406/585 - loss 0.19668302 - samples/sec: 70.83 - lr: 0.050000
2020-09-16 04:15:19,052 epoch 120 - iter 464/585 - loss 0.20608412 - samples/sec: 142.85 - lr: 0.050000
2020-09-16 04:15:30,376 epoch 120 - iter 522/585 - loss 0.19980107 - samples/sec: 164.03 - lr: 0.050000
2020-09-16 04:16:01,540 epoch 120 - iter 580/585 - loss 0.19253881 - samples/sec: 59.57 - lr: 0.050000
2020-09-16 04:16:04,107 ----------------------------------------------------------------------------------------------------
2020-09-16 04:16:04,107 EPOCH 120 done: loss 0.1915 - lr 0.0500000
2020-09-16 04:16:04,108 BAD EPOCHS (no improvement): 1
2020-09-16 04:16:04,112 ----------------------------------------------------------------------------------------------------
2020-09-16 04:16:36,637 epoch 121 - iter 58/585 - loss 0.20669274 - samples/sec: 57.08 - lr: 0.050000
2020-09-16 04:17:08,235 epoch 121 - iter 116/585 - loss 0.18213024 - samples/sec: 58.75 - lr: 0.050000
2020-09-16 04:17:35,663 epoch 121 - iter 174/585 - loss 0.17037975 - samples/sec: 67.69 - lr: 0.050000
2020-09-16 04:17:49,027 epoch 121 - iter 232/585 - loss 0.20496816 - samples/sec: 138.98 - lr: 0.050000
2020-09-16 04:18:02,118 epoch 121 - iter 290/585 - loss 0.19514729 - samples/sec: 141.87 - lr: 0.050000
2020-09-16 04:18:33,793 epoch 121 - iter 348/585 - loss 0.18659336 - samples/sec: 58.61 - lr: 0.050000
2020-09-16 04:19:05,308 epoch 121 - iter 406/585 - loss 0.18044680 - samples/sec: 58.91 - lr: 0.050000
2020-09-16 04:19:38,193 epoch 121 - iter 464/585 - loss 0.19202266 - samples/sec: 56.45 - lr: 0.050000
2020-09-16 04:20:05,071 epoch 121 - iter 522/585 - loss 0.18885253 - samples/sec: 69.07 - lr: 0.050000
2020-09-16 04:20:16,867 epoch 121 - iter 580/585 - loss 0.18556791 - samples/sec: 157.45 - lr: 0.050000
2020-09-16 04:20:18,919 ----------------------------------------------------------------------------------------------------
2020-09-16 04:20:18,919 EPOCH 121 done: loss 0.1972 - lr 0.0500000
2020-09-16 04:20:18,919 BAD EPOCHS (no improvement): 2
2020-09-16 04:20:18,922 ----------------------------------------------------------------------------------------------------
2020-09-16 04:20:32,434 epoch 122 - iter 58/585 - loss 0.15742803 - samples/sec: 137.47 - lr: 0.050000
2020-09-16 04:21:03,824 epoch 122 - iter 116/585 - loss 0.16056181 - samples/sec: 59.14 - lr: 0.050000
2020-09-16 04:21:35,213 epoch 122 - iter 174/585 - loss 0.14459849 - samples/sec: 59.15 - lr: 0.050000
2020-09-16 04:22:09,064 epoch 122 - iter 232/585 - loss 0.22483565 - samples/sec: 54.84 - lr: 0.050000
2020-09-16 04:22:35,166 epoch 122 - iter 290/585 - loss 0.20555734 - samples/sec: 71.13 - lr: 0.050000
2020-09-16 04:22:47,309 epoch 122 - iter 348/585 - loss 0.18969481 - samples/sec: 152.97 - lr: 0.050000
2020-09-16 04:23:00,196 epoch 122 - iter 406/585 - loss 0.18194406 - samples/sec: 144.13 - lr: 0.050000
2020-09-16 04:23:32,785 epoch 122 - iter 464/585 - loss 0.18349702 - samples/sec: 56.97 - lr: 0.050000
2020-09-16 04:24:04,315 epoch 122 - iter 522/585 - loss 0.17879635 - samples/sec: 58.88 - lr: 0.050000
2020-09-16 04:24:37,042 epoch 122 - iter 580/585 - loss 0.18416843 - samples/sec: 56.73 - lr: 0.050000
2020-09-16 04:24:39,614 ----------------------------------------------------------------------------------------------------
2020-09-16 04:24:39,614 EPOCH 122 done: loss 0.1838 - lr 0.0500000
2020-09-16 04:24:39,615 BAD EPOCHS (no improvement): 3
2020-09-16 04:24:39,618 ----------------------------------------------------------------------------------------------------
2020-09-16 04:25:04,534 epoch 123 - iter 58/585 - loss 0.13567675 - samples/sec: 74.52 - lr: 0.050000
2020-09-16 04:25:16,923 epoch 123 - iter 116/585 - loss 0.14443834 - samples/sec: 149.92 - lr: 0.050000
2020-09-16 04:25:31,390 epoch 123 - iter 174/585 - loss 0.16227857 - samples/sec: 128.39 - lr: 0.050000
2020-09-16 04:26:02,994 epoch 123 - iter 232/585 - loss 0.15716837 - samples/sec: 58.74 - lr: 0.050000
2020-09-16 04:26:34,334 epoch 123 - iter 290/585 - loss 0.15605939 - samples/sec: 59.24 - lr: 0.050000
2020-09-16 04:27:06,108 epoch 123 - iter 348/585 - loss 0.15279216 - samples/sec: 58.43 - lr: 0.050000
2020-09-16 04:27:33,715 epoch 123 - iter 406/585 - loss 0.17441151 - samples/sec: 67.25 - lr: 0.050000
2020-09-16 04:27:46,794 epoch 123 - iter 464/585 - loss 0.18632266 - samples/sec: 141.99 - lr: 0.050000
2020-09-16 04:28:00,810 epoch 123 - iter 522/585 - loss 0.18041086 - samples/sec: 132.52 - lr: 0.050000
2020-09-16 04:28:33,590 epoch 123 - iter 580/585 - loss 0.18536166 - samples/sec: 56.63 - lr: 0.050000
2020-09-16 04:28:36,140 ----------------------------------------------------------------------------------------------------
2020-09-16 04:28:36,140 EPOCH 123 done: loss 0.1849 - lr 0.0500000
2020-09-16 04:28:36,141 BAD EPOCHS (no improvement): 4
2020-09-16 04:28:36,144 ----------------------------------------------------------------------------------------------------
2020-09-16 04:29:07,573 epoch 124 - iter 58/585 - loss 0.11988282 - samples/sec: 59.07 - lr: 0.025000
2020-09-16 04:29:39,025 epoch 124 - iter 116/585 - loss 0.13832107 - samples/sec: 59.03 - lr: 0.025000
2020-09-16 04:30:03,391 epoch 124 - iter 174/585 - loss 0.13672897 - samples/sec: 76.20 - lr: 0.025000
2020-09-16 04:30:17,477 epoch 124 - iter 232/585 - loss 0.17420581 - samples/sec: 131.84 - lr: 0.025000
2020-09-16 04:30:33,042 epoch 124 - iter 290/585 - loss 0.16886789 - samples/sec: 119.31 - lr: 0.025000
2020-09-16 04:31:05,697 epoch 124 - iter 348/585 - loss 0.17715615 - samples/sec: 56.85 - lr: 0.025000
2020-09-16 04:31:38,333 epoch 124 - iter 406/585 - loss 0.19510603 - samples/sec: 56.88 - lr: 0.025000
2020-09-16 04:32:09,673 epoch 124 - iter 464/585 - loss 0.18613203 - samples/sec: 59.24 - lr: 0.025000
2020-09-16 04:32:33,583 epoch 124 - iter 522/585 - loss 0.18050136 - samples/sec: 77.66 - lr: 0.025000
2020-09-16 04:32:46,964 epoch 124 - iter 580/585 - loss 0.17588492 - samples/sec: 138.78 - lr: 0.025000
2020-09-16 04:32:47,578 ----------------------------------------------------------------------------------------------------
2020-09-16 04:32:47,578 EPOCH 124 done: loss 0.1750 - lr 0.0250000
2020-09-16 04:32:47,579 BAD EPOCHS (no improvement): 0
2020-09-16 04:32:47,586 ----------------------------------------------------------------------------------------------------
2020-09-16 04:33:04,916 epoch 125 - iter 58/585 - loss 0.13610462 - samples/sec: 107.17 - lr: 0.025000
2020-09-16 04:33:38,033 epoch 125 - iter 116/585 - loss 0.21398670 - samples/sec: 56.06 - lr: 0.025000
2020-09-16 04:34:11,029 epoch 125 - iter 174/585 - loss 0.23383192 - samples/sec: 56.26 - lr: 0.025000
2020-09-16 04:34:42,593 epoch 125 - iter 232/585 - loss 0.20531150 - samples/sec: 58.82 - lr: 0.025000
2020-09-16 04:35:03,919 epoch 125 - iter 290/585 - loss 0.18909252 - samples/sec: 87.07 - lr: 0.025000
2020-09-16 04:35:17,718 epoch 125 - iter 348/585 - loss 0.20183047 - samples/sec: 134.59 - lr: 0.025000
2020-09-16 04:35:36,218 epoch 125 - iter 406/585 - loss 0.19187014 - samples/sec: 100.38 - lr: 0.025000
2020-09-16 04:36:07,385 epoch 125 - iter 464/585 - loss 0.18563644 - samples/sec: 59.56 - lr: 0.025000
2020-09-16 04:36:39,004 epoch 125 - iter 522/585 - loss 0.17984337 - samples/sec: 58.71 - lr: 0.025000
2020-09-16 04:37:09,906 epoch 125 - iter 580/585 - loss 0.17466483 - samples/sec: 60.08 - lr: 0.025000
2020-09-16 04:37:12,431 ----------------------------------------------------------------------------------------------------
2020-09-16 04:37:12,432 EPOCH 125 done: loss 0.1742 - lr 0.0250000
2020-09-16 04:37:12,432 BAD EPOCHS (no improvement): 0
2020-09-16 04:37:12,435 ----------------------------------------------------------------------------------------------------
2020-09-16 04:37:32,783 epoch 126 - iter 58/585 - loss 0.16087529 - samples/sec: 91.26 - lr: 0.025000
2020-09-16 04:37:46,267 epoch 126 - iter 116/585 - loss 0.14412406 - samples/sec: 137.74 - lr: 0.025000
2020-09-16 04:38:04,793 epoch 126 - iter 174/585 - loss 0.14054914 - samples/sec: 100.23 - lr: 0.025000
2020-09-16 04:38:36,440 epoch 126 - iter 232/585 - loss 0.13953517 - samples/sec: 58.66 - lr: 0.025000
2020-09-16 04:39:07,957 epoch 126 - iter 290/585 - loss 0.13491371 - samples/sec: 58.90 - lr: 0.025000
2020-09-16 04:39:41,243 epoch 126 - iter 348/585 - loss 0.16308730 - samples/sec: 55.77 - lr: 0.025000
2020-09-16 04:40:02,048 epoch 126 - iter 406/585 - loss 0.15613079 - samples/sec: 89.25 - lr: 0.025000
2020-09-16 04:40:16,005 epoch 126 - iter 464/585 - loss 0.17303700 - samples/sec: 133.06 - lr: 0.025000
2020-09-16 04:40:33,968 epoch 126 - iter 522/585 - loss 0.16689154 - samples/sec: 103.38 - lr: 0.025000
2020-09-16 04:41:05,302 epoch 126 - iter 580/585 - loss 0.16218981 - samples/sec: 59.25 - lr: 0.025000
2020-09-16 04:41:07,882 ----------------------------------------------------------------------------------------------------
2020-09-16 04:41:07,882 EPOCH 126 done: loss 0.1621 - lr 0.0250000
2020-09-16 04:41:07,882 BAD EPOCHS (no improvement): 0
2020-09-16 04:41:07,888 ----------------------------------------------------------------------------------------------------
2020-09-16 04:41:39,368 epoch 127 - iter 58/585 - loss 0.13915837 - samples/sec: 58.98 - lr: 0.025000
2020-09-16 04:42:10,464 epoch 127 - iter 116/585 - loss 0.13649998 - samples/sec: 59.70 - lr: 0.025000
2020-09-16 04:42:31,205 epoch 127 - iter 174/585 - loss 0.14708428 - samples/sec: 89.52 - lr: 0.025000
2020-09-16 04:42:44,913 epoch 127 - iter 232/585 - loss 0.16464390 - samples/sec: 135.48 - lr: 0.025000
2020-09-16 04:43:10,184 epoch 127 - iter 290/585 - loss 0.18018489 - samples/sec: 73.47 - lr: 0.025000
2020-09-16 04:43:41,658 epoch 127 - iter 348/585 - loss 0.17072483 - samples/sec: 58.99 - lr: 0.025000
2020-09-16 04:44:14,436 epoch 127 - iter 406/585 - loss 0.18574534 - samples/sec: 56.64 - lr: 0.025000
2020-09-16 04:44:45,955 epoch 127 - iter 464/585 - loss 0.17603682 - samples/sec: 58.90 - lr: 0.025000
2020-09-16 04:45:01,681 epoch 127 - iter 522/585 - loss 0.16824409 - samples/sec: 118.09 - lr: 0.025000
2020-09-16 04:45:14,453 epoch 127 - iter 580/585 - loss 0.16266438 - samples/sec: 145.43 - lr: 0.025000
2020-09-16 04:45:14,985 ----------------------------------------------------------------------------------------------------
2020-09-16 04:45:14,985 EPOCH 127 done: loss 0.1619 - lr 0.0250000
2020-09-16 04:45:14,985 BAD EPOCHS (no improvement): 0
2020-09-16 04:45:14,988 ----------------------------------------------------------------------------------------------------
2020-09-16 04:45:39,576 epoch 128 - iter 58/585 - loss 0.12012013 - samples/sec: 75.52 - lr: 0.025000
2020-09-16 04:46:11,923 epoch 128 - iter 116/585 - loss 0.12572493 - samples/sec: 57.39 - lr: 0.025000
2020-09-16 04:46:43,481 epoch 128 - iter 174/585 - loss 0.11647199 - samples/sec: 58.83 - lr: 0.025000
2020-09-16 04:47:14,996 epoch 128 - iter 232/585 - loss 0.11869596 - samples/sec: 58.91 - lr: 0.025000
2020-09-16 04:47:33,846 epoch 128 - iter 290/585 - loss 0.17813156 - samples/sec: 98.51 - lr: 0.025000
2020-09-16 04:47:45,011 epoch 128 - iter 348/585 - loss 0.17247209 - samples/sec: 166.37 - lr: 0.025000
2020-09-16 04:48:13,837 epoch 128 - iter 406/585 - loss 0.17868432 - samples/sec: 64.40 - lr: 0.025000
2020-09-16 04:48:45,353 epoch 128 - iter 464/585 - loss 0.17197152 - samples/sec: 58.91 - lr: 0.025000
2020-09-16 04:49:16,720 epoch 128 - iter 522/585 - loss 0.16425945 - samples/sec: 59.19 - lr: 0.025000
2020-09-16 04:49:48,560 epoch 128 - iter 580/585 - loss 0.15856771 - samples/sec: 58.31 - lr: 0.025000
2020-09-16 04:49:51,146 ----------------------------------------------------------------------------------------------------
2020-09-16 04:49:51,146 EPOCH 128 done: loss 0.1580 - lr 0.0250000
2020-09-16 04:49:51,147 BAD EPOCHS (no improvement): 0
2020-09-16 04:49:51,165 ----------------------------------------------------------------------------------------------------
2020-09-16 04:50:03,623 epoch 129 - iter 58/585 - loss 0.11089738 - samples/sec: 149.12 - lr: 0.025000
2020-09-16 04:50:14,303 epoch 129 - iter 116/585 - loss 0.10539963 - samples/sec: 173.92 - lr: 0.025000
2020-09-16 04:50:43,744 epoch 129 - iter 174/585 - loss 0.15506810 - samples/sec: 63.06 - lr: 0.025000
2020-09-16 04:51:15,329 epoch 129 - iter 232/585 - loss 0.14808561 - samples/sec: 58.78 - lr: 0.025000
2020-09-16 04:51:49,004 epoch 129 - iter 290/585 - loss 0.18683929 - samples/sec: 55.13 - lr: 0.025000
2020-09-16 04:52:20,546 epoch 129 - iter 348/585 - loss 0.17670959 - samples/sec: 58.86 - lr: 0.025000
2020-09-16 04:52:33,302 epoch 129 - iter 406/585 - loss 0.16929397 - samples/sec: 145.61 - lr: 0.025000
2020-09-16 04:52:43,970 epoch 129 - iter 464/585 - loss 0.16287636 - samples/sec: 174.13 - lr: 0.025000
2020-09-16 04:53:13,109 epoch 129 - iter 522/585 - loss 0.16437800 - samples/sec: 63.71 - lr: 0.025000
2020-09-16 04:53:44,436 epoch 129 - iter 580/585 - loss 0.15864329 - samples/sec: 59.26 - lr: 0.025000
2020-09-16 04:53:47,027 ----------------------------------------------------------------------------------------------------
2020-09-16 04:53:47,028 EPOCH 129 done: loss 0.1581 - lr 0.0250000
2020-09-16 04:53:47,028 BAD EPOCHS (no improvement): 1
2020-09-16 04:53:47,031 ----------------------------------------------------------------------------------------------------
2020-09-16 04:54:18,527 epoch 130 - iter 58/585 - loss 0.10675224 - samples/sec: 58.95 - lr: 0.025000
2020-09-16 04:54:50,020 epoch 130 - iter 116/585 - loss 0.10936503 - samples/sec: 58.95 - lr: 0.025000
2020-09-16 04:55:03,260 epoch 130 - iter 174/585 - loss 0.11694722 - samples/sec: 140.28 - lr: 0.025000
2020-09-16 04:55:13,892 epoch 130 - iter 232/585 - loss 0.11917992 - samples/sec: 174.72 - lr: 0.025000
2020-09-16 04:55:45,342 epoch 130 - iter 290/585 - loss 0.13921796 - samples/sec: 59.03 - lr: 0.025000
2020-09-16 04:56:16,871 epoch 130 - iter 348/585 - loss 0.13485046 - samples/sec: 58.88 - lr: 0.025000
2020-09-16 04:56:48,448 epoch 130 - iter 406/585 - loss 0.13155394 - samples/sec: 58.79 - lr: 0.025000
2020-09-16 04:57:22,843 epoch 130 - iter 464/585 - loss 0.16294547 - samples/sec: 53.97 - lr: 0.025000
2020-09-16 04:57:35,235 epoch 130 - iter 522/585 - loss 0.16501885 - samples/sec: 149.89 - lr: 0.025000
2020-09-16 04:57:46,057 epoch 130 - iter 580/585 - loss 0.15998040 - samples/sec: 171.65 - lr: 0.025000
2020-09-16 04:57:48,655 ----------------------------------------------------------------------------------------------------
2020-09-16 04:57:48,655 EPOCH 130 done: loss 0.1595 - lr 0.0250000
2020-09-16 04:57:48,656 BAD EPOCHS (no improvement): 2
2020-09-16 04:57:48,660 ----------------------------------------------------------------------------------------------------
2020-09-16 04:58:23,501 epoch 131 - iter 58/585 - loss 0.40710105 - samples/sec: 53.29 - lr: 0.025000
2020-09-16 04:58:55,123 epoch 131 - iter 116/585 - loss 0.26219033 - samples/sec: 58.71 - lr: 0.025000
2020-09-16 04:59:26,678 epoch 131 - iter 174/585 - loss 0.21287317 - samples/sec: 58.84 - lr: 0.025000
2020-09-16 04:59:55,204 epoch 131 - iter 232/585 - loss 0.20171873 - samples/sec: 65.08 - lr: 0.025000
2020-09-16 05:00:09,359 epoch 131 - iter 290/585 - loss 0.20006685 - samples/sec: 131.21 - lr: 0.025000
2020-09-16 05:00:24,380 epoch 131 - iter 348/585 - loss 0.18540864 - samples/sec: 123.64 - lr: 0.025000
2020-09-16 05:00:55,055 epoch 131 - iter 406/585 - loss 0.17828642 - samples/sec: 60.52 - lr: 0.025000
2020-09-16 05:01:13,248 epoch 131 - iter 464/585 - loss 0.17257300 - samples/sec: 102.07 - lr: 0.025000
2020-09-16 05:01:44,749 epoch 131 - iter 522/585 - loss 0.16380445 - samples/sec: 58.94 - lr: 0.025000
2020-09-16 05:02:16,595 epoch 131 - iter 580/585 - loss 0.15744086 - samples/sec: 58.30 - lr: 0.025000
2020-09-16 05:02:19,162 ----------------------------------------------------------------------------------------------------
2020-09-16 05:02:19,163 EPOCH 131 done: loss 0.1566 - lr 0.0250000
2020-09-16 05:02:19,163 BAD EPOCHS (no improvement): 0
2020-09-16 05:02:19,168 ----------------------------------------------------------------------------------------------------
2020-09-16 05:02:34,845 epoch 132 - iter 58/585 - loss 0.26076373 - samples/sec: 118.48 - lr: 0.025000
2020-09-16 05:02:45,581 epoch 132 - iter 116/585 - loss 0.17841375 - samples/sec: 173.04 - lr: 0.025000
2020-09-16 05:02:52,310 epoch 132 - iter 174/585 - loss 0.16460057 - samples/sec: 276.27 - lr: 0.025000
2020-09-16 05:02:58,977 epoch 132 - iter 232/585 - loss 0.15242944 - samples/sec: 278.80 - lr: 0.025000
2020-09-16 05:03:06,431 epoch 132 - iter 290/585 - loss 0.16325086 - samples/sec: 249.30 - lr: 0.025000
2020-09-16 05:03:12,944 epoch 132 - iter 348/585 - loss 0.15636639 - samples/sec: 285.37 - lr: 0.025000
2020-09-16 05:03:20,715 epoch 132 - iter 406/585 - loss 0.17095639 - samples/sec: 239.18 - lr: 0.025000
2020-09-16 05:03:27,422 epoch 132 - iter 464/585 - loss 0.16095883 - samples/sec: 277.16 - lr: 0.025000
2020-09-16 05:03:34,044 epoch 132 - iter 522/585 - loss 0.15555698 - samples/sec: 280.70 - lr: 0.025000
2020-09-16 05:03:40,682 epoch 132 - iter 580/585 - loss 0.15241335 - samples/sec: 279.99 - lr: 0.025000
2020-09-16 05:03:41,192 ----------------------------------------------------------------------------------------------------
2020-09-16 05:03:41,192 EPOCH 132 done: loss 0.1521 - lr 0.0250000
2020-09-16 05:03:41,193 BAD EPOCHS (no improvement): 0
2020-09-16 05:03:41,197 ----------------------------------------------------------------------------------------------------
2020-09-16 05:03:47,947 epoch 133 - iter 58/585 - loss 0.10968638 - samples/sec: 275.36 - lr: 0.025000
2020-09-16 05:03:54,574 epoch 133 - iter 116/585 - loss 0.11597002 - samples/sec: 280.40 - lr: 0.025000
2020-09-16 05:04:08,700 epoch 133 - iter 174/585 - loss 0.11399867 - samples/sec: 131.46 - lr: 0.025000
2020-09-16 05:04:29,595 epoch 133 - iter 232/585 - loss 0.11145493 - samples/sec: 88.86 - lr: 0.025000
2020-09-16 05:04:49,606 epoch 133 - iter 290/585 - loss 0.11005726 - samples/sec: 92.78 - lr: 0.025000
2020-09-16 05:05:10,671 epoch 133 - iter 348/585 - loss 0.11556956 - samples/sec: 88.14 - lr: 0.025000
2020-09-16 05:05:30,156 epoch 133 - iter 406/585 - loss 0.11456899 - samples/sec: 95.30 - lr: 0.025000
2020-09-16 05:05:47,607 epoch 133 - iter 464/585 - loss 0.13071891 - samples/sec: 106.41 - lr: 0.025000
2020-09-16 05:05:56,412 epoch 133 - iter 522/585 - loss 0.14542615 - samples/sec: 211.03 - lr: 0.025000
2020-09-16 05:06:15,012 epoch 133 - iter 580/585 - loss 0.15104250 - samples/sec: 99.83 - lr: 0.025000
2020-09-16 05:06:16,604 ----------------------------------------------------------------------------------------------------
2020-09-16 05:06:16,604 EPOCH 133 done: loss 0.1507 - lr 0.0250000
2020-09-16 05:06:16,605 BAD EPOCHS (no improvement): 0
2020-09-16 05:06:16,610 ----------------------------------------------------------------------------------------------------
2020-09-16 05:06:37,986 epoch 134 - iter 58/585 - loss 0.20603471 - samples/sec: 86.87 - lr: 0.025000
2020-09-16 05:06:57,553 epoch 134 - iter 116/585 - loss 0.16423717 - samples/sec: 94.89 - lr: 0.025000
2020-09-16 05:07:17,498 epoch 134 - iter 174/585 - loss 0.14189425 - samples/sec: 93.09 - lr: 0.025000
2020-09-16 05:07:37,285 epoch 134 - iter 232/585 - loss 0.13282608 - samples/sec: 93.84 - lr: 0.025000
2020-09-16 05:07:50,509 epoch 134 - iter 290/585 - loss 0.14100863 - samples/sec: 140.45 - lr: 0.025000
2020-09-16 05:07:58,305 epoch 134 - iter 348/585 - loss 0.13866145 - samples/sec: 238.38 - lr: 0.025000
2020-09-16 05:08:15,420 epoch 134 - iter 406/585 - loss 0.13582372 - samples/sec: 108.49 - lr: 0.025000
2020-09-16 05:08:35,455 epoch 134 - iter 464/585 - loss 0.13250188 - samples/sec: 92.68 - lr: 0.025000
2020-09-16 05:08:56,300 epoch 134 - iter 522/585 - loss 0.14363136 - samples/sec: 89.07 - lr: 0.025000
2020-09-16 05:09:17,045 epoch 134 - iter 580/585 - loss 0.15770904 - samples/sec: 89.50 - lr: 0.025000
2020-09-16 05:09:18,586 ----------------------------------------------------------------------------------------------------
2020-09-16 05:09:18,586 EPOCH 134 done: loss 0.1575 - lr 0.0250000
2020-09-16 05:09:18,587 BAD EPOCHS (no improvement): 1
2020-09-16 05:09:18,590 ----------------------------------------------------------------------------------------------------
2020-09-16 05:09:39,609 epoch 135 - iter 58/585 - loss 0.21370282 - samples/sec: 88.34 - lr: 0.025000
2020-09-16 05:09:52,713 epoch 135 - iter 116/585 - loss 0.16628038 - samples/sec: 141.73 - lr: 0.025000
2020-09-16 05:10:00,600 epoch 135 - iter 174/585 - loss 0.14493818 - samples/sec: 235.61 - lr: 0.025000
2020-09-16 05:10:18,834 epoch 135 - iter 232/585 - loss 0.12943246 - samples/sec: 101.83 - lr: 0.025000
2020-09-16 05:10:39,710 epoch 135 - iter 290/585 - loss 0.13267695 - samples/sec: 88.94 - lr: 0.025000
2020-09-16 05:11:00,667 epoch 135 - iter 348/585 - loss 0.12868407 - samples/sec: 88.59 - lr: 0.025000
2020-09-16 05:11:21,056 epoch 135 - iter 406/585 - loss 0.12419396 - samples/sec: 91.06 - lr: 0.025000
2020-09-16 05:11:43,325 epoch 135 - iter 464/585 - loss 0.14376165 - samples/sec: 83.37 - lr: 0.025000
2020-09-16 05:11:54,428 epoch 135 - iter 522/585 - loss 0.14208483 - samples/sec: 167.33 - lr: 0.025000
2020-09-16 05:12:04,107 epoch 135 - iter 580/585 - loss 0.15066590 - samples/sec: 191.95 - lr: 0.025000
2020-09-16 05:12:05,715 ----------------------------------------------------------------------------------------------------
2020-09-16 05:12:05,715 EPOCH 135 done: loss 0.1503 - lr 0.0250000
2020-09-16 05:12:05,715 BAD EPOCHS (no improvement): 0
2020-09-16 05:12:05,718 ----------------------------------------------------------------------------------------------------
2020-09-16 05:12:26,067 epoch 136 - iter 58/585 - loss 0.12929643 - samples/sec: 91.24 - lr: 0.025000
2020-09-16 05:12:46,215 epoch 136 - iter 116/585 - loss 0.11970532 - samples/sec: 92.15 - lr: 0.025000
2020-09-16 05:13:06,686 epoch 136 - iter 174/585 - loss 0.11994963 - samples/sec: 90.70 - lr: 0.025000
2020-09-16 05:13:27,363 epoch 136 - iter 232/585 - loss 0.12004483 - samples/sec: 89.80 - lr: 0.025000
2020-09-16 05:13:47,024 epoch 136 - iter 290/585 - loss 0.11668040 - samples/sec: 94.44 - lr: 0.025000
2020-09-16 05:13:57,305 epoch 136 - iter 348/585 - loss 0.11841057 - samples/sec: 180.69 - lr: 0.025000
2020-09-16 05:14:12,332 epoch 136 - iter 406/585 - loss 0.16124373 - samples/sec: 123.58 - lr: 0.025000
2020-09-16 05:14:32,608 epoch 136 - iter 464/585 - loss 0.15531615 - samples/sec: 91.57 - lr: 0.025000
2020-09-16 05:14:53,148 epoch 136 - iter 522/585 - loss 0.15901804 - samples/sec: 90.40 - lr: 0.025000
2020-09-16 05:15:12,670 epoch 136 - iter 580/585 - loss 0.15494515 - samples/sec: 95.11 - lr: 0.025000
2020-09-16 05:15:14,055 ----------------------------------------------------------------------------------------------------
2020-09-16 05:15:14,055 EPOCH 136 done: loss 0.1546 - lr 0.0250000
2020-09-16 05:15:14,055 BAD EPOCHS (no improvement): 1
2020-09-16 05:15:14,064 ----------------------------------------------------------------------------------------------------
2020-09-16 05:15:33,653 epoch 137 - iter 58/585 - loss 0.11409493 - samples/sec: 94.79 - lr: 0.025000
2020-09-16 05:15:53,915 epoch 137 - iter 116/585 - loss 0.13792827 - samples/sec: 91.63 - lr: 0.025000
2020-09-16 05:16:02,679 epoch 137 - iter 174/585 - loss 0.17536718 - samples/sec: 212.03 - lr: 0.025000
2020-09-16 05:16:16,832 epoch 137 - iter 232/585 - loss 0.15195351 - samples/sec: 131.23 - lr: 0.025000
2020-09-16 05:16:37,423 epoch 137 - iter 290/585 - loss 0.14377467 - samples/sec: 90.17 - lr: 0.025000
2020-09-16 05:16:58,800 epoch 137 - iter 348/585 - loss 0.13855069 - samples/sec: 86.86 - lr: 0.025000
2020-09-16 05:17:18,906 epoch 137 - iter 406/585 - loss 0.13511746 - samples/sec: 92.35 - lr: 0.025000
2020-09-16 05:17:39,244 epoch 137 - iter 464/585 - loss 0.13176770 - samples/sec: 91.29 - lr: 0.025000
2020-09-16 05:17:55,866 epoch 137 - iter 522/585 - loss 0.14599222 - samples/sec: 111.72 - lr: 0.025000
2020-09-16 05:18:04,809 epoch 137 - iter 580/585 - loss 0.15432100 - samples/sec: 207.78 - lr: 0.025000
2020-09-16 05:18:05,401 ----------------------------------------------------------------------------------------------------
2020-09-16 05:18:05,401 EPOCH 137 done: loss 0.1541 - lr 0.0250000
2020-09-16 05:18:05,401 BAD EPOCHS (no improvement): 2
2020-09-16 05:18:05,406 ----------------------------------------------------------------------------------------------------
2020-09-16 05:18:23,867 epoch 138 - iter 58/585 - loss 0.21300962 - samples/sec: 100.59 - lr: 0.025000
2020-09-16 05:18:45,351 epoch 138 - iter 116/585 - loss 0.24309403 - samples/sec: 86.42 - lr: 0.025000
2020-09-16 05:19:05,354 epoch 138 - iter 174/585 - loss 0.19840877 - samples/sec: 92.83 - lr: 0.025000
2020-09-16 05:19:25,489 epoch 138 - iter 232/585 - loss 0.17050365 - samples/sec: 92.21 - lr: 0.025000
2020-09-16 05:19:45,122 epoch 138 - iter 290/585 - loss 0.16192555 - samples/sec: 94.57 - lr: 0.025000
2020-09-16 05:19:59,370 epoch 138 - iter 348/585 - loss 0.16045909 - samples/sec: 130.34 - lr: 0.025000
2020-09-16 05:20:07,367 epoch 138 - iter 406/585 - loss 0.15244798 - samples/sec: 232.37 - lr: 0.025000
2020-09-16 05:20:25,659 epoch 138 - iter 464/585 - loss 0.14798191 - samples/sec: 101.51 - lr: 0.025000
2020-09-16 05:20:45,133 epoch 138 - iter 522/585 - loss 0.14538880 - samples/sec: 95.34 - lr: 0.025000
2020-09-16 05:21:02,174 epoch 138 - iter 580/585 - loss 0.15543304 - samples/sec: 108.97 - lr: 0.025000
2020-09-16 05:21:03,825 ----------------------------------------------------------------------------------------------------
2020-09-16 05:21:03,825 EPOCH 138 done: loss 0.1554 - lr 0.0250000
2020-09-16 05:21:03,825 BAD EPOCHS (no improvement): 3
2020-09-16 05:21:03,843 ----------------------------------------------------------------------------------------------------
2020-09-16 05:21:24,029 epoch 139 - iter 58/585 - loss 0.11556100 - samples/sec: 91.99 - lr: 0.025000
2020-09-16 05:21:43,942 epoch 139 - iter 116/585 - loss 0.10552736 - samples/sec: 93.24 - lr: 0.025000
2020-09-16 05:22:00,961 epoch 139 - iter 174/585 - loss 0.11395003 - samples/sec: 109.11 - lr: 0.025000
2020-09-16 05:22:10,145 epoch 139 - iter 232/585 - loss 0.15194371 - samples/sec: 202.32 - lr: 0.025000
2020-09-16 05:22:23,945 epoch 139 - iter 290/585 - loss 0.16245676 - samples/sec: 134.58 - lr: 0.025000
2020-09-16 05:22:43,672 epoch 139 - iter 348/585 - loss 0.15277275 - samples/sec: 94.12 - lr: 0.025000
2020-09-16 05:23:04,508 epoch 139 - iter 406/585 - loss 0.17334224 - samples/sec: 89.11 - lr: 0.025000
2020-09-16 05:23:24,847 epoch 139 - iter 464/585 - loss 0.16313739 - samples/sec: 91.29 - lr: 0.025000
2020-09-16 05:23:45,023 epoch 139 - iter 522/585 - loss 0.15690477 - samples/sec: 92.03 - lr: 0.025000
2020-09-16 05:24:04,211 epoch 139 - iter 580/585 - loss 0.15065499 - samples/sec: 96.77 - lr: 0.025000
2020-09-16 05:24:04,699 ----------------------------------------------------------------------------------------------------
2020-09-16 05:24:04,700 EPOCH 139 done: loss 0.1500 - lr 0.0250000
2020-09-16 05:24:04,700 BAD EPOCHS (no improvement): 0
2020-09-16 05:24:04,703 ----------------------------------------------------------------------------------------------------
2020-09-16 05:24:13,282 epoch 140 - iter 58/585 - loss 0.10678034 - samples/sec: 216.70 - lr: 0.025000
2020-09-16 05:24:27,232 epoch 140 - iter 116/585 - loss 0.10884500 - samples/sec: 133.14 - lr: 0.025000
2020-09-16 05:24:48,141 epoch 140 - iter 174/585 - loss 0.12545685 - samples/sec: 88.80 - lr: 0.025000
2020-09-16 05:25:07,761 epoch 140 - iter 232/585 - loss 0.12409527 - samples/sec: 94.64 - lr: 0.025000
2020-09-16 05:25:27,932 epoch 140 - iter 290/585 - loss 0.12234604 - samples/sec: 92.05 - lr: 0.025000
2020-09-16 05:25:48,805 epoch 140 - iter 348/585 - loss 0.14961213 - samples/sec: 88.96 - lr: 0.025000
2020-09-16 05:26:07,440 epoch 140 - iter 406/585 - loss 0.15881813 - samples/sec: 99.64 - lr: 0.025000
2020-09-16 05:26:15,681 epoch 140 - iter 464/585 - loss 0.15241653 - samples/sec: 225.51 - lr: 0.025000
2020-09-16 05:26:29,937 epoch 140 - iter 522/585 - loss 0.15942478 - samples/sec: 130.27 - lr: 0.025000
2020-09-16 05:26:50,085 epoch 140 - iter 580/585 - loss 0.15494858 - samples/sec: 92.16 - lr: 0.025000
2020-09-16 05:26:51,690 ----------------------------------------------------------------------------------------------------
2020-09-16 05:26:51,690 EPOCH 140 done: loss 0.1542 - lr 0.0250000
2020-09-16 05:26:51,690 BAD EPOCHS (no improvement): 1
2020-09-16 05:26:51,693 ----------------------------------------------------------------------------------------------------
2020-09-16 05:27:11,376 epoch 141 - iter 58/585 - loss 0.10918453 - samples/sec: 94.34 - lr: 0.025000
2020-09-16 05:27:31,794 epoch 141 - iter 116/585 - loss 0.10346274 - samples/sec: 90.93 - lr: 0.025000
2020-09-16 05:27:52,600 epoch 141 - iter 174/585 - loss 0.10797089 - samples/sec: 89.24 - lr: 0.025000
2020-09-16 05:28:10,226 epoch 141 - iter 232/585 - loss 0.13644200 - samples/sec: 105.35 - lr: 0.025000
2020-09-16 05:28:18,952 epoch 141 - iter 290/585 - loss 0.15238556 - samples/sec: 212.95 - lr: 0.025000
2020-09-16 05:28:35,560 epoch 141 - iter 348/585 - loss 0.14557671 - samples/sec: 111.81 - lr: 0.025000
2020-09-16 05:28:56,224 epoch 141 - iter 406/585 - loss 0.14107555 - samples/sec: 89.85 - lr: 0.025000
2020-09-16 05:29:16,210 epoch 141 - iter 464/585 - loss 0.13661630 - samples/sec: 92.91 - lr: 0.025000
2020-09-16 05:29:35,664 epoch 141 - iter 522/585 - loss 0.13568127 - samples/sec: 95.44 - lr: 0.025000
2020-09-16 05:29:56,559 epoch 141 - iter 580/585 - loss 0.14350752 - samples/sec: 88.86 - lr: 0.025000
2020-09-16 05:29:58,771 ----------------------------------------------------------------------------------------------------
2020-09-16 05:29:58,772 EPOCH 141 done: loss 0.1487 - lr 0.0250000
2020-09-16 05:29:58,772 BAD EPOCHS (no improvement): 0
2020-09-16 05:29:58,776 ----------------------------------------------------------------------------------------------------
2020-09-16 05:30:12,666 epoch 142 - iter 58/585 - loss 0.10749098 - samples/sec: 133.73 - lr: 0.025000
2020-09-16 05:30:21,028 epoch 142 - iter 116/585 - loss 0.10793522 - samples/sec: 222.22 - lr: 0.025000
2020-09-16 05:30:41,244 epoch 142 - iter 174/585 - loss 0.15049309 - samples/sec: 91.84 - lr: 0.025000
2020-09-16 05:31:01,321 epoch 142 - iter 232/585 - loss 0.13602331 - samples/sec: 92.48 - lr: 0.025000
2020-09-16 05:31:22,995 epoch 142 - iter 290/585 - loss 0.15162961 - samples/sec: 85.66 - lr: 0.025000
2020-09-16 05:31:42,739 epoch 142 - iter 348/585 - loss 0.14285890 - samples/sec: 94.04 - lr: 0.025000
2020-09-16 05:32:04,954 epoch 142 - iter 406/585 - loss 0.16425920 - samples/sec: 83.57 - lr: 0.025000
2020-09-16 05:32:15,496 epoch 142 - iter 464/585 - loss 0.15569592 - samples/sec: 176.22 - lr: 0.025000
2020-09-16 05:32:25,687 epoch 142 - iter 522/585 - loss 0.14849650 - samples/sec: 182.29 - lr: 0.025000
2020-09-16 05:32:45,935 epoch 142 - iter 580/585 - loss 0.14438008 - samples/sec: 91.70 - lr: 0.025000
2020-09-16 05:32:47,615 ----------------------------------------------------------------------------------------------------
2020-09-16 05:32:47,615 EPOCH 142 done: loss 0.1445 - lr 0.0250000
2020-09-16 05:32:47,616 BAD EPOCHS (no improvement): 0
2020-09-16 05:32:47,619 ----------------------------------------------------------------------------------------------------
2020-09-16 05:33:07,565 epoch 143 - iter 58/585 - loss 0.11077001 - samples/sec: 93.09 - lr: 0.025000
2020-09-16 05:33:28,795 epoch 143 - iter 116/585 - loss 0.17772407 - samples/sec: 87.46 - lr: 0.025000
2020-09-16 05:33:47,901 epoch 143 - iter 174/585 - loss 0.15356683 - samples/sec: 97.19 - lr: 0.025000
2020-09-16 05:34:09,565 epoch 143 - iter 232/585 - loss 0.17219971 - samples/sec: 85.70 - lr: 0.025000
2020-09-16 05:34:19,610 epoch 143 - iter 290/585 - loss 0.15990460 - samples/sec: 184.95 - lr: 0.025000
2020-09-16 05:34:30,402 epoch 143 - iter 348/585 - loss 0.15142998 - samples/sec: 172.14 - lr: 0.025000
2020-09-16 05:34:51,694 epoch 143 - iter 406/585 - loss 0.16727290 - samples/sec: 87.20 - lr: 0.025000
2020-09-16 05:35:11,759 epoch 143 - iter 464/585 - loss 0.15910166 - samples/sec: 92.53 - lr: 0.025000
2020-09-16 05:35:32,014 epoch 143 - iter 522/585 - loss 0.15348011 - samples/sec: 91.67 - lr: 0.025000
2020-09-16 05:35:52,806 epoch 143 - iter 580/585 - loss 0.14913715 - samples/sec: 89.29 - lr: 0.025000
2020-09-16 05:35:54,401 ----------------------------------------------------------------------------------------------------
2020-09-16 05:35:54,402 EPOCH 143 done: loss 0.1492 - lr 0.0250000
2020-09-16 05:35:54,402 BAD EPOCHS (no improvement): 1
2020-09-16 05:35:54,410 ----------------------------------------------------------------------------------------------------
2020-09-16 05:36:14,492 epoch 144 - iter 58/585 - loss 0.20345899 - samples/sec: 92.47 - lr: 0.025000
2020-09-16 05:36:22,784 epoch 144 - iter 116/585 - loss 0.18791195 - samples/sec: 224.12 - lr: 0.025000
2020-09-16 05:36:38,785 epoch 144 - iter 174/585 - loss 0.19205120 - samples/sec: 116.05 - lr: 0.025000
2020-09-16 05:36:58,594 epoch 144 - iter 232/585 - loss 0.17481378 - samples/sec: 93.73 - lr: 0.025000
2020-09-16 05:37:18,593 epoch 144 - iter 290/585 - loss 0.16285716 - samples/sec: 92.84 - lr: 0.025000
2020-09-16 05:37:39,865 epoch 144 - iter 348/585 - loss 0.17375099 - samples/sec: 87.28 - lr: 0.025000
2020-09-16 05:38:00,522 epoch 144 - iter 406/585 - loss 0.16456878 - samples/sec: 89.88 - lr: 0.025000
2020-09-16 05:38:16,917 epoch 144 - iter 464/585 - loss 0.15567223 - samples/sec: 113.27 - lr: 0.025000
2020-09-16 05:38:24,983 epoch 144 - iter 522/585 - loss 0.14870951 - samples/sec: 230.39 - lr: 0.025000
2020-09-16 05:38:42,122 epoch 144 - iter 580/585 - loss 0.14746969 - samples/sec: 108.34 - lr: 0.025000
2020-09-16 05:38:43,849 ----------------------------------------------------------------------------------------------------
2020-09-16 05:38:43,849 EPOCH 144 done: loss 0.1470 - lr 0.0250000
2020-09-16 05:38:43,849 BAD EPOCHS (no improvement): 2
2020-09-16 05:38:43,853 ----------------------------------------------------------------------------------------------------
2020-09-16 05:39:04,961 epoch 145 - iter 58/585 - loss 0.10691969 - samples/sec: 87.97 - lr: 0.025000
2020-09-16 05:39:24,816 epoch 145 - iter 116/585 - loss 0.10147836 - samples/sec: 93.51 - lr: 0.025000
2020-09-16 05:39:44,725 epoch 145 - iter 174/585 - loss 0.09832784 - samples/sec: 93.26 - lr: 0.025000
2020-09-16 05:40:04,969 epoch 145 - iter 232/585 - loss 0.10083645 - samples/sec: 91.72 - lr: 0.025000
2020-09-16 05:40:18,148 epoch 145 - iter 290/585 - loss 0.09778087 - samples/sec: 140.93 - lr: 0.025000
2020-09-16 05:40:26,075 epoch 145 - iter 348/585 - loss 0.09600353 - samples/sec: 234.40 - lr: 0.025000
2020-09-16 05:40:44,906 epoch 145 - iter 406/585 - loss 0.10643189 - samples/sec: 98.61 - lr: 0.025000
2020-09-16 05:41:04,786 epoch 145 - iter 464/585 - loss 0.10534021 - samples/sec: 93.39 - lr: 0.025000
2020-09-16 05:41:27,477 epoch 145 - iter 522/585 - loss 0.13269143 - samples/sec: 81.82 - lr: 0.025000
2020-09-16 05:41:48,487 epoch 145 - iter 580/585 - loss 0.13560327 - samples/sec: 88.37 - lr: 0.025000
2020-09-16 05:41:50,117 ----------------------------------------------------------------------------------------------------
2020-09-16 05:41:50,117 EPOCH 145 done: loss 0.1349 - lr 0.0250000
2020-09-16 05:41:50,117 BAD EPOCHS (no improvement): 0
2020-09-16 05:41:50,134 ----------------------------------------------------------------------------------------------------
2020-09-16 05:42:10,463 epoch 146 - iter 58/585 - loss 0.09552957 - samples/sec: 91.34 - lr: 0.025000
2020-09-16 05:42:21,494 epoch 146 - iter 116/585 - loss 0.09435199 - samples/sec: 168.39 - lr: 0.025000
2020-09-16 05:42:29,920 epoch 146 - iter 174/585 - loss 0.09965603 - samples/sec: 220.55 - lr: 0.025000
2020-09-16 05:42:51,441 epoch 146 - iter 232/585 - loss 0.14246381 - samples/sec: 86.27 - lr: 0.025000
2020-09-16 05:43:11,575 epoch 146 - iter 290/585 - loss 0.15381612 - samples/sec: 92.21 - lr: 0.025000
2020-09-16 05:43:31,974 epoch 146 - iter 348/585 - loss 0.15379120 - samples/sec: 91.02 - lr: 0.025000
2020-09-16 05:43:52,140 epoch 146 - iter 406/585 - loss 0.14730298 - samples/sec: 92.07 - lr: 0.025000
2020-09-16 05:44:12,935 epoch 146 - iter 464/585 - loss 0.14061149 - samples/sec: 89.29 - lr: 0.025000
2020-09-16 05:44:25,470 epoch 146 - iter 522/585 - loss 0.14616321 - samples/sec: 148.18 - lr: 0.025000
2020-09-16 05:44:35,424 epoch 146 - iter 580/585 - loss 0.14160916 - samples/sec: 186.64 - lr: 0.025000
2020-09-16 05:44:36,798 ----------------------------------------------------------------------------------------------------
2020-09-16 05:44:36,798 EPOCH 146 done: loss 0.1413 - lr 0.0250000
2020-09-16 05:44:36,798 BAD EPOCHS (no improvement): 1
2020-09-16 05:44:36,807 ----------------------------------------------------------------------------------------------------
2020-09-16 05:44:57,933 epoch 147 - iter 58/585 - loss 0.18494606 - samples/sec: 87.89 - lr: 0.025000
2020-09-16 05:45:18,945 epoch 147 - iter 116/585 - loss 0.20260335 - samples/sec: 88.36 - lr: 0.025000
2020-09-16 05:45:39,614 epoch 147 - iter 174/585 - loss 0.17878829 - samples/sec: 89.83 - lr: 0.025000
2020-09-16 05:46:00,285 epoch 147 - iter 232/585 - loss 0.15671209 - samples/sec: 89.82 - lr: 0.025000
2020-09-16 05:46:20,472 epoch 147 - iter 290/585 - loss 0.17202175 - samples/sec: 91.98 - lr: 0.025000
2020-09-16 05:46:28,425 epoch 147 - iter 348/585 - loss 0.16143866 - samples/sec: 233.68 - lr: 0.025000
2020-09-16 05:46:42,483 epoch 147 - iter 406/585 - loss 0.15199776 - samples/sec: 132.10 - lr: 0.025000
2020-09-16 05:47:02,797 epoch 147 - iter 464/585 - loss 0.14453330 - samples/sec: 91.40 - lr: 0.025000
2020-09-16 05:47:23,452 epoch 147 - iter 522/585 - loss 0.14054089 - samples/sec: 89.89 - lr: 0.025000
2020-09-16 05:47:43,881 epoch 147 - iter 580/585 - loss 0.13683229 - samples/sec: 90.89 - lr: 0.025000
2020-09-16 05:47:45,436 ----------------------------------------------------------------------------------------------------
2020-09-16 05:47:45,436 EPOCH 147 done: loss 0.1364 - lr 0.0250000
2020-09-16 05:47:45,436 BAD EPOCHS (no improvement): 2
2020-09-16 05:47:45,439 ----------------------------------------------------------------------------------------------------
2020-09-16 05:48:06,303 epoch 148 - iter 58/585 - loss 0.11032320 - samples/sec: 89.00 - lr: 0.025000
2020-09-16 05:48:21,945 epoch 148 - iter 116/585 - loss 0.10971539 - samples/sec: 118.72 - lr: 0.025000
2020-09-16 05:48:30,832 epoch 148 - iter 174/585 - loss 0.15431069 - samples/sec: 209.08 - lr: 0.025000
2020-09-16 05:48:47,960 epoch 148 - iter 232/585 - loss 0.17170578 - samples/sec: 108.42 - lr: 0.025000
2020-09-16 05:49:08,238 epoch 148 - iter 290/585 - loss 0.15478486 - samples/sec: 91.56 - lr: 0.025000
2020-09-16 05:49:28,533 epoch 148 - iter 348/585 - loss 0.14792613 - samples/sec: 91.49 - lr: 0.025000
2020-09-16 05:49:50,149 epoch 148 - iter 406/585 - loss 0.15606589 - samples/sec: 85.90 - lr: 0.025000
2020-09-16 05:50:10,354 epoch 148 - iter 464/585 - loss 0.14858950 - samples/sec: 91.89 - lr: 0.025000
2020-09-16 05:50:25,036 epoch 148 - iter 522/585 - loss 0.14424754 - samples/sec: 126.50 - lr: 0.025000
2020-09-16 05:50:33,662 epoch 148 - iter 580/585 - loss 0.14430122 - samples/sec: 215.45 - lr: 0.025000
2020-09-16 05:50:34,211 ----------------------------------------------------------------------------------------------------
2020-09-16 05:50:34,211 EPOCH 148 done: loss 0.1444 - lr 0.0250000
2020-09-16 05:50:34,211 BAD EPOCHS (no improvement): 3
2020-09-16 05:50:34,215 ----------------------------------------------------------------------------------------------------
2020-09-16 05:50:50,464 epoch 149 - iter 58/585 - loss 0.11786343 - samples/sec: 114.30 - lr: 0.025000
2020-09-16 05:51:12,643 epoch 149 - iter 116/585 - loss 0.11040224 - samples/sec: 83.72 - lr: 0.025000
2020-09-16 05:51:34,855 epoch 149 - iter 174/585 - loss 0.10877889 - samples/sec: 83.60 - lr: 0.025000
2020-09-16 05:51:59,573 epoch 149 - iter 232/585 - loss 0.18603061 - samples/sec: 75.11 - lr: 0.025000
2020-09-16 05:52:21,730 epoch 149 - iter 290/585 - loss 0.17294921 - samples/sec: 83.81 - lr: 0.025000
2020-09-16 05:52:31,718 epoch 149 - iter 348/585 - loss 0.17447615 - samples/sec: 186.03 - lr: 0.025000
2020-09-16 05:52:41,172 epoch 149 - iter 406/585 - loss 0.17357985 - samples/sec: 196.55 - lr: 0.025000
2020-09-16 05:53:01,843 epoch 149 - iter 464/585 - loss 0.16650029 - samples/sec: 89.83 - lr: 0.025000
2020-09-16 05:53:22,534 epoch 149 - iter 522/585 - loss 0.16155690 - samples/sec: 89.74 - lr: 0.025000
2020-09-16 05:53:42,637 epoch 149 - iter 580/585 - loss 0.15624299 - samples/sec: 92.36 - lr: 0.025000
2020-09-16 05:53:44,268 ----------------------------------------------------------------------------------------------------
2020-09-16 05:53:44,269 EPOCH 149 done: loss 0.1557 - lr 0.0250000
2020-09-16 05:53:44,269 BAD EPOCHS (no improvement): 4
2020-09-16 05:53:44,272 ----------------------------------------------------------------------------------------------------
2020-09-16 05:54:06,673 epoch 150 - iter 58/585 - loss 0.33113541 - samples/sec: 82.89 - lr: 0.012500
2020-09-16 05:54:26,879 epoch 150 - iter 116/585 - loss 0.21415919 - samples/sec: 91.89 - lr: 0.012500
2020-09-16 05:54:34,381 epoch 150 - iter 174/585 - loss 0.17218858 - samples/sec: 247.76 - lr: 0.012500
2020-09-16 05:54:41,775 epoch 150 - iter 232/585 - loss 0.15671718 - samples/sec: 251.37 - lr: 0.012500
2020-09-16 05:55:02,490 epoch 150 - iter 290/585 - loss 0.14439272 - samples/sec: 89.63 - lr: 0.012500
2020-09-16 05:55:24,460 epoch 150 - iter 348/585 - loss 0.15870041 - samples/sec: 84.51 - lr: 0.012500
2020-09-16 05:55:45,529 epoch 150 - iter 406/585 - loss 0.15071797 - samples/sec: 88.13 - lr: 0.012500
2020-09-16 05:56:06,426 epoch 150 - iter 464/585 - loss 0.14439552 - samples/sec: 88.85 - lr: 0.012500
2020-09-16 05:56:27,297 epoch 150 - iter 522/585 - loss 0.14059762 - samples/sec: 88.96 - lr: 0.012500
2020-09-16 05:56:35,569 epoch 150 - iter 580/585 - loss 0.13691053 - samples/sec: 224.66 - lr: 0.012500
2020-09-16 05:56:36,461 ----------------------------------------------------------------------------------------------------
2020-09-16 05:56:36,462 EPOCH 150 done: loss 0.1364 - lr 0.0125000
2020-09-16 05:56:36,462 BAD EPOCHS (no improvement): 1
2020-09-16 05:56:51,923 ----------------------------------------------------------------------------------------------------
2020-09-16 05:56:51,923 Testing using best model ...
2020-09-16 05:59:10,420 0.9235	0.9163	0.9199
2020-09-16 05:59:10,420 
Results:
- F1-score (micro) 0.9199
- F1-score (macro) 0.9207

By class:
LOC        tp: 720 - fp: 46 - fn: 54 - precision: 0.9399 - recall: 0.9302 - f1-score: 0.9351
MISC       tp: 1026 - fp: 88 - fn: 161 - precision: 0.9210 - recall: 0.8644 - f1-score: 0.8918
ORG        tp: 814 - fp: 101 - fn: 68 - precision: 0.8896 - recall: 0.9229 - f1-score: 0.9060
PER        tp: 1051 - fp: 64 - fn: 47 - precision: 0.9426 - recall: 0.9572 - f1-score: 0.9498
2020-09-16 05:59:10,420 ----------------------------------------------------------------------------------------------------