diff --git "a/training.log" "b/training.log" new file mode 100644--- /dev/null +++ "b/training.log" @@ -0,0 +1,1891 @@ +2023-03-29 16:42:30,589 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:30,589 Model: "SequenceTagger( + (embeddings): StackedEmbeddings( + (list_embedding_0): WordEmbeddings( + 'de' + (embedding): Embedding(1000000, 300) + ) + (list_embedding_1): FlairEmbeddings( + (lm): LanguageModel( + (drop): Dropout(p=0.25, inplace=False) + (encoder): Embedding(275, 100) + (rnn): LSTM(100, 2048) + ) + ) + (list_embedding_2): FlairEmbeddings( + (lm): LanguageModel( + (drop): Dropout(p=0.25, inplace=False) + (encoder): Embedding(275, 100) + (rnn): LSTM(100, 2048) + ) + ) + ) + (word_dropout): WordDropout(p=0.05) + (locked_dropout): LockedDropout(p=0.5) + (embedding2nn): Linear(in_features=4396, out_features=4396, bias=True) + (rnn): LSTM(4396, 256, batch_first=True, bidirectional=True) + (linear): Linear(in_features=512, out_features=19, bias=True) + (loss_function): ViterbiLoss() + (crf): CRF() +)" +2023-03-29 16:42:30,589 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:30,589 Corpus: "Corpus: 12705 train + 3068 dev + 3160 test sentences" +2023-03-29 16:42:30,589 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:30,590 Parameters: +2023-03-29 16:42:30,590 - learning_rate: "0.100000" +2023-03-29 16:42:30,590 - mini_batch_size: "32" +2023-03-29 16:42:30,590 - patience: "3" +2023-03-29 16:42:30,590 - anneal_factor: "0.5" +2023-03-29 16:42:30,590 - max_epochs: "150" +2023-03-29 16:42:30,590 - shuffle: "True" +2023-03-29 16:42:30,590 - train_with_dev: "True" +2023-03-29 16:42:30,590 - batch_growth_annealing: "False" +2023-03-29 16:42:30,590 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:30,590 Model training base path: "resources/taggers/release-de-ner-0" +2023-03-29 16:42:30,590 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:30,590 Device: cuda:2 +2023-03-29 16:42:30,590 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:30,590 Embeddings storage mode: cpu +2023-03-29 16:42:30,590 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:42:39,764 epoch 1 - iter 49/493 - loss 0.46644716 - time (sec): 9.17 - samples/sec: 3034.05 - lr: 0.100000 +2023-03-29 16:42:48,338 epoch 1 - iter 98/493 - loss 0.31988353 - time (sec): 17.75 - samples/sec: 3117.17 - lr: 0.100000 +2023-03-29 16:42:56,178 epoch 1 - iter 147/493 - loss 0.27195175 - time (sec): 25.59 - samples/sec: 3102.09 - lr: 0.100000 +2023-03-29 16:43:06,551 epoch 1 - iter 196/493 - loss 0.23366763 - time (sec): 35.96 - samples/sec: 2905.85 - lr: 0.100000 +2023-03-29 16:43:14,061 epoch 1 - iter 245/493 - loss 0.21486776 - time (sec): 43.47 - samples/sec: 2968.67 - lr: 0.100000 +2023-03-29 16:43:21,787 epoch 1 - iter 294/493 - loss 0.20025894 - time (sec): 51.20 - samples/sec: 2991.22 - lr: 0.100000 +2023-03-29 16:43:29,873 epoch 1 - iter 343/493 - loss 0.18706718 - time (sec): 59.28 - samples/sec: 3016.39 - lr: 0.100000 +2023-03-29 16:43:38,046 epoch 1 - iter 392/493 - loss 0.17935330 - time (sec): 67.46 - samples/sec: 3044.55 - lr: 0.100000 +2023-03-29 16:43:46,005 epoch 1 - iter 441/493 - loss 0.17112302 - time (sec): 75.42 - samples/sec: 3063.40 - lr: 0.100000 +2023-03-29 16:43:55,198 epoch 1 - iter 490/493 - loss 0.16739534 - time (sec): 84.61 - samples/sec: 3046.95 - lr: 0.100000 +2023-03-29 16:43:55,603 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:43:55,603 EPOCH 1 done: loss 0.1671 - lr 0.100000 +2023-03-29 16:43:55,603 BAD EPOCHS (no improvement): 0 +2023-03-29 16:43:55,607 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:43:59,136 epoch 2 - iter 49/493 - loss 0.09655865 - time (sec): 3.53 - samples/sec: 7203.04 - lr: 0.100000 +2023-03-29 16:44:02,516 epoch 2 - iter 98/493 - loss 0.09332598 - time (sec): 6.91 - samples/sec: 7379.31 - lr: 0.100000 +2023-03-29 16:44:05,867 epoch 2 - iter 147/493 - loss 0.08847197 - time (sec): 10.26 - samples/sec: 7473.16 - lr: 0.100000 +2023-03-29 16:44:09,403 epoch 2 - iter 196/493 - loss 0.08720627 - time (sec): 13.80 - samples/sec: 7464.19 - lr: 0.100000 +2023-03-29 16:44:12,849 epoch 2 - iter 245/493 - loss 0.08579958 - time (sec): 17.24 - samples/sec: 7429.85 - lr: 0.100000 +2023-03-29 16:44:16,401 epoch 2 - iter 294/493 - loss 0.08543270 - time (sec): 20.79 - samples/sec: 7423.51 - lr: 0.100000 +2023-03-29 16:44:19,885 epoch 2 - iter 343/493 - loss 0.08456374 - time (sec): 24.28 - samples/sec: 7417.79 - lr: 0.100000 +2023-03-29 16:44:23,379 epoch 2 - iter 392/493 - loss 0.08342429 - time (sec): 27.77 - samples/sec: 7414.44 - lr: 0.100000 +2023-03-29 16:44:26,982 epoch 2 - iter 441/493 - loss 0.08165096 - time (sec): 31.38 - samples/sec: 7388.68 - lr: 0.100000 +2023-03-29 16:44:30,537 epoch 2 - iter 490/493 - loss 0.08070827 - time (sec): 34.93 - samples/sec: 7373.67 - lr: 0.100000 +2023-03-29 16:44:30,760 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:44:30,760 EPOCH 2 done: loss 0.0806 - lr 0.100000 +2023-03-29 16:44:30,760 BAD EPOCHS (no improvement): 0 +2023-03-29 16:44:30,763 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:44:34,387 epoch 3 - iter 49/493 - loss 0.07044696 - time (sec): 3.62 - samples/sec: 7085.11 - lr: 0.100000 +2023-03-29 16:44:37,948 epoch 3 - iter 98/493 - loss 0.07021930 - time (sec): 7.18 - samples/sec: 7193.38 - lr: 0.100000 +2023-03-29 16:44:41,435 epoch 3 - iter 147/493 - loss 0.06980087 - time (sec): 10.67 - samples/sec: 7252.82 - lr: 0.100000 +2023-03-29 16:44:44,806 epoch 3 - iter 196/493 - loss 0.06875732 - time (sec): 14.04 - samples/sec: 7274.11 - lr: 0.100000 +2023-03-29 16:44:48,514 epoch 3 - iter 245/493 - loss 0.06766544 - time (sec): 17.75 - samples/sec: 7267.36 - lr: 0.100000 +2023-03-29 16:44:52,022 epoch 3 - iter 294/493 - loss 0.06729169 - time (sec): 21.26 - samples/sec: 7303.83 - lr: 0.100000 +2023-03-29 16:44:55,573 epoch 3 - iter 343/493 - loss 0.06677841 - time (sec): 24.81 - samples/sec: 7284.11 - lr: 0.100000 +2023-03-29 16:44:59,021 epoch 3 - iter 392/493 - loss 0.06648263 - time (sec): 28.26 - samples/sec: 7285.31 - lr: 0.100000 +2023-03-29 16:45:02,393 epoch 3 - iter 441/493 - loss 0.06542096 - time (sec): 31.63 - samples/sec: 7318.28 - lr: 0.100000 +2023-03-29 16:45:06,092 epoch 3 - iter 490/493 - loss 0.06462579 - time (sec): 35.33 - samples/sec: 7292.72 - lr: 0.100000 +2023-03-29 16:45:06,314 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:45:06,314 EPOCH 3 done: loss 0.0645 - lr 0.100000 +2023-03-29 16:45:06,314 BAD EPOCHS (no improvement): 0 +2023-03-29 16:45:06,317 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:45:09,880 epoch 4 - iter 49/493 - loss 0.05399821 - time (sec): 3.56 - samples/sec: 7237.97 - lr: 0.100000 +2023-03-29 16:45:13,503 epoch 4 - iter 98/493 - loss 0.05873254 - time (sec): 7.19 - samples/sec: 7293.58 - lr: 0.100000 +2023-03-29 16:45:17,064 epoch 4 - iter 147/493 - loss 0.05794216 - time (sec): 10.75 - samples/sec: 7232.18 - lr: 0.100000 +2023-03-29 16:45:20,625 epoch 4 - iter 196/493 - loss 0.05804724 - time (sec): 14.31 - samples/sec: 7255.24 - lr: 0.100000 +2023-03-29 16:45:24,173 epoch 4 - iter 245/493 - loss 0.05661678 - time (sec): 17.86 - samples/sec: 7238.34 - lr: 0.100000 +2023-03-29 16:45:27,805 epoch 4 - iter 294/493 - loss 0.05627032 - time (sec): 21.49 - samples/sec: 7234.24 - lr: 0.100000 +2023-03-29 16:45:31,363 epoch 4 - iter 343/493 - loss 0.05755638 - time (sec): 25.05 - samples/sec: 7221.15 - lr: 0.100000 +2023-03-29 16:45:34,810 epoch 4 - iter 392/493 - loss 0.05756938 - time (sec): 28.49 - samples/sec: 7233.02 - lr: 0.100000 +2023-03-29 16:45:38,266 epoch 4 - iter 441/493 - loss 0.05668179 - time (sec): 31.95 - samples/sec: 7252.68 - lr: 0.100000 +2023-03-29 16:45:41,729 epoch 4 - iter 490/493 - loss 0.05688996 - time (sec): 35.41 - samples/sec: 7277.98 - lr: 0.100000 +2023-03-29 16:45:41,927 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:45:41,927 EPOCH 4 done: loss 0.0568 - lr 0.100000 +2023-03-29 16:45:41,927 BAD EPOCHS (no improvement): 0 +2023-03-29 16:45:41,930 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:45:45,411 epoch 5 - iter 49/493 - loss 0.05633686 - time (sec): 3.48 - samples/sec: 7345.05 - lr: 0.100000 +2023-03-29 16:45:48,905 epoch 5 - iter 98/493 - loss 0.05432266 - time (sec): 6.98 - samples/sec: 7381.72 - lr: 0.100000 +2023-03-29 16:45:52,377 epoch 5 - iter 147/493 - loss 0.05132033 - time (sec): 10.45 - samples/sec: 7362.57 - lr: 0.100000 +2023-03-29 16:45:56,158 epoch 5 - iter 196/493 - loss 0.05227944 - time (sec): 14.23 - samples/sec: 7264.72 - lr: 0.100000 +2023-03-29 16:45:59,673 epoch 5 - iter 245/493 - loss 0.05224815 - time (sec): 17.74 - samples/sec: 7290.39 - lr: 0.100000 +2023-03-29 16:46:03,123 epoch 5 - iter 294/493 - loss 0.05241316 - time (sec): 21.19 - samples/sec: 7286.62 - lr: 0.100000 +2023-03-29 16:46:06,533 epoch 5 - iter 343/493 - loss 0.05160962 - time (sec): 24.60 - samples/sec: 7294.67 - lr: 0.100000 +2023-03-29 16:46:10,050 epoch 5 - iter 392/493 - loss 0.05166800 - time (sec): 28.12 - samples/sec: 7309.76 - lr: 0.100000 +2023-03-29 16:46:13,499 epoch 5 - iter 441/493 - loss 0.05105173 - time (sec): 31.57 - samples/sec: 7325.58 - lr: 0.100000 +2023-03-29 16:46:17,066 epoch 5 - iter 490/493 - loss 0.05112971 - time (sec): 35.14 - samples/sec: 7330.55 - lr: 0.100000 +2023-03-29 16:46:17,299 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:46:17,299 EPOCH 5 done: loss 0.0511 - lr 0.100000 +2023-03-29 16:46:17,300 BAD EPOCHS (no improvement): 0 +2023-03-29 16:46:17,302 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:46:20,810 epoch 6 - iter 49/493 - loss 0.05209740 - time (sec): 3.51 - samples/sec: 7243.72 - lr: 0.100000 +2023-03-29 16:46:24,419 epoch 6 - iter 98/493 - loss 0.04942847 - time (sec): 7.12 - samples/sec: 7217.24 - lr: 0.100000 +2023-03-29 16:46:27,996 epoch 6 - iter 147/493 - loss 0.04744082 - time (sec): 10.69 - samples/sec: 7219.87 - lr: 0.100000 +2023-03-29 16:46:31,549 epoch 6 - iter 196/493 - loss 0.04695821 - time (sec): 14.25 - samples/sec: 7231.42 - lr: 0.100000 +2023-03-29 16:46:35,001 epoch 6 - iter 245/493 - loss 0.04703050 - time (sec): 17.70 - samples/sec: 7278.84 - lr: 0.100000 +2023-03-29 16:46:38,512 epoch 6 - iter 294/493 - loss 0.04711416 - time (sec): 21.21 - samples/sec: 7284.29 - lr: 0.100000 +2023-03-29 16:46:41,958 epoch 6 - iter 343/493 - loss 0.04731643 - time (sec): 24.66 - samples/sec: 7309.44 - lr: 0.100000 +2023-03-29 16:46:45,554 epoch 6 - iter 392/493 - loss 0.04712845 - time (sec): 28.25 - samples/sec: 7292.92 - lr: 0.100000 +2023-03-29 16:46:49,021 epoch 6 - iter 441/493 - loss 0.04714741 - time (sec): 31.72 - samples/sec: 7295.85 - lr: 0.100000 +2023-03-29 16:46:52,535 epoch 6 - iter 490/493 - loss 0.04727371 - time (sec): 35.23 - samples/sec: 7310.68 - lr: 0.100000 +2023-03-29 16:46:52,737 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:46:52,737 EPOCH 6 done: loss 0.0472 - lr 0.100000 +2023-03-29 16:46:52,737 BAD EPOCHS (no improvement): 0 +2023-03-29 16:46:52,740 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:46:56,160 epoch 7 - iter 49/493 - loss 0.04490630 - time (sec): 3.42 - samples/sec: 7473.27 - lr: 0.100000 +2023-03-29 16:46:59,809 epoch 7 - iter 98/493 - loss 0.04517921 - time (sec): 7.07 - samples/sec: 7257.92 - lr: 0.100000 +2023-03-29 16:47:03,343 epoch 7 - iter 147/493 - loss 0.04423338 - time (sec): 10.60 - samples/sec: 7298.80 - lr: 0.100000 +2023-03-29 16:47:06,805 epoch 7 - iter 196/493 - loss 0.04484448 - time (sec): 14.07 - samples/sec: 7357.24 - lr: 0.100000 +2023-03-29 16:47:10,248 epoch 7 - iter 245/493 - loss 0.04447620 - time (sec): 17.51 - samples/sec: 7371.12 - lr: 0.100000 +2023-03-29 16:47:13,563 epoch 7 - iter 294/493 - loss 0.04512531 - time (sec): 20.82 - samples/sec: 7405.23 - lr: 0.100000 +2023-03-29 16:47:17,032 epoch 7 - iter 343/493 - loss 0.04506370 - time (sec): 24.29 - samples/sec: 7421.62 - lr: 0.100000 +2023-03-29 16:47:20,518 epoch 7 - iter 392/493 - loss 0.04479532 - time (sec): 27.78 - samples/sec: 7415.90 - lr: 0.100000 +2023-03-29 16:47:23,841 epoch 7 - iter 441/493 - loss 0.04451346 - time (sec): 31.10 - samples/sec: 7444.63 - lr: 0.100000 +2023-03-29 16:47:27,177 epoch 7 - iter 490/493 - loss 0.04423305 - time (sec): 34.44 - samples/sec: 7476.12 - lr: 0.100000 +2023-03-29 16:47:27,386 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:47:27,386 EPOCH 7 done: loss 0.0443 - lr 0.100000 +2023-03-29 16:47:27,386 BAD EPOCHS (no improvement): 0 +2023-03-29 16:47:27,389 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:47:30,790 epoch 8 - iter 49/493 - loss 0.04066354 - time (sec): 3.40 - samples/sec: 7515.74 - lr: 0.100000 +2023-03-29 16:47:34,240 epoch 8 - iter 98/493 - loss 0.03882795 - time (sec): 6.85 - samples/sec: 7489.75 - lr: 0.100000 +2023-03-29 16:47:37,791 epoch 8 - iter 147/493 - loss 0.04099944 - time (sec): 10.40 - samples/sec: 7454.65 - lr: 0.100000 +2023-03-29 16:47:41,245 epoch 8 - iter 196/493 - loss 0.03977522 - time (sec): 13.86 - samples/sec: 7447.01 - lr: 0.100000 +2023-03-29 16:47:44,658 epoch 8 - iter 245/493 - loss 0.04034347 - time (sec): 17.27 - samples/sec: 7468.39 - lr: 0.100000 +2023-03-29 16:47:48,216 epoch 8 - iter 294/493 - loss 0.04126713 - time (sec): 20.83 - samples/sec: 7431.95 - lr: 0.100000 +2023-03-29 16:47:51,764 epoch 8 - iter 343/493 - loss 0.04131202 - time (sec): 24.37 - samples/sec: 7404.65 - lr: 0.100000 +2023-03-29 16:47:55,253 epoch 8 - iter 392/493 - loss 0.04137829 - time (sec): 27.86 - samples/sec: 7401.41 - lr: 0.100000 +2023-03-29 16:47:58,769 epoch 8 - iter 441/493 - loss 0.04110908 - time (sec): 31.38 - samples/sec: 7388.98 - lr: 0.100000 +2023-03-29 16:48:02,337 epoch 8 - iter 490/493 - loss 0.04130897 - time (sec): 34.95 - samples/sec: 7370.69 - lr: 0.100000 +2023-03-29 16:48:02,556 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:48:02,556 EPOCH 8 done: loss 0.0413 - lr 0.100000 +2023-03-29 16:48:02,556 BAD EPOCHS (no improvement): 0 +2023-03-29 16:48:02,559 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:48:06,058 epoch 9 - iter 49/493 - loss 0.03553756 - time (sec): 3.50 - samples/sec: 7473.85 - lr: 0.100000 +2023-03-29 16:48:09,597 epoch 9 - iter 98/493 - loss 0.03648757 - time (sec): 7.04 - samples/sec: 7394.93 - lr: 0.100000 +2023-03-29 16:48:13,214 epoch 9 - iter 147/493 - loss 0.03650184 - time (sec): 10.66 - samples/sec: 7324.75 - lr: 0.100000 +2023-03-29 16:48:16,770 epoch 9 - iter 196/493 - loss 0.03747618 - time (sec): 14.21 - samples/sec: 7308.40 - lr: 0.100000 +2023-03-29 16:48:20,177 epoch 9 - iter 245/493 - loss 0.03841574 - time (sec): 17.62 - samples/sec: 7311.52 - lr: 0.100000 +2023-03-29 16:48:23,540 epoch 9 - iter 294/493 - loss 0.03813335 - time (sec): 20.98 - samples/sec: 7325.15 - lr: 0.100000 +2023-03-29 16:48:26,998 epoch 9 - iter 343/493 - loss 0.03850934 - time (sec): 24.44 - samples/sec: 7343.88 - lr: 0.100000 +2023-03-29 16:48:30,551 epoch 9 - iter 392/493 - loss 0.03817715 - time (sec): 27.99 - samples/sec: 7342.64 - lr: 0.100000 +2023-03-29 16:48:34,191 epoch 9 - iter 441/493 - loss 0.03798437 - time (sec): 31.63 - samples/sec: 7318.14 - lr: 0.100000 +2023-03-29 16:48:37,761 epoch 9 - iter 490/493 - loss 0.03837003 - time (sec): 35.20 - samples/sec: 7316.20 - lr: 0.100000 +2023-03-29 16:48:37,979 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:48:37,979 EPOCH 9 done: loss 0.0384 - lr 0.100000 +2023-03-29 16:48:37,979 BAD EPOCHS (no improvement): 0 +2023-03-29 16:48:37,983 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:48:41,533 epoch 10 - iter 49/493 - loss 0.03833640 - time (sec): 3.55 - samples/sec: 7325.14 - lr: 0.100000 +2023-03-29 16:48:45,057 epoch 10 - iter 98/493 - loss 0.03736996 - time (sec): 7.07 - samples/sec: 7339.41 - lr: 0.100000 +2023-03-29 16:48:48,540 epoch 10 - iter 147/493 - loss 0.03792437 - time (sec): 10.56 - samples/sec: 7342.35 - lr: 0.100000 +2023-03-29 16:48:52,017 epoch 10 - iter 196/493 - loss 0.03777501 - time (sec): 14.03 - samples/sec: 7347.24 - lr: 0.100000 +2023-03-29 16:48:55,567 epoch 10 - iter 245/493 - loss 0.03717360 - time (sec): 17.58 - samples/sec: 7350.60 - lr: 0.100000 +2023-03-29 16:48:59,084 epoch 10 - iter 294/493 - loss 0.03729877 - time (sec): 21.10 - samples/sec: 7332.27 - lr: 0.100000 +2023-03-29 16:49:02,599 epoch 10 - iter 343/493 - loss 0.03714881 - time (sec): 24.62 - samples/sec: 7344.72 - lr: 0.100000 +2023-03-29 16:49:06,176 epoch 10 - iter 392/493 - loss 0.03692179 - time (sec): 28.19 - samples/sec: 7327.47 - lr: 0.100000 +2023-03-29 16:49:09,708 epoch 10 - iter 441/493 - loss 0.03705621 - time (sec): 31.73 - samples/sec: 7324.63 - lr: 0.100000 +2023-03-29 16:49:13,187 epoch 10 - iter 490/493 - loss 0.03696067 - time (sec): 35.20 - samples/sec: 7317.72 - lr: 0.100000 +2023-03-29 16:49:13,405 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:49:13,405 EPOCH 10 done: loss 0.0370 - lr 0.100000 +2023-03-29 16:49:13,405 BAD EPOCHS (no improvement): 0 +2023-03-29 16:49:13,408 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:49:16,859 epoch 11 - iter 49/493 - loss 0.03358704 - time (sec): 3.45 - samples/sec: 7366.50 - lr: 0.100000 +2023-03-29 16:49:20,414 epoch 11 - iter 98/493 - loss 0.03487343 - time (sec): 7.01 - samples/sec: 7328.15 - lr: 0.100000 +2023-03-29 16:49:24,007 epoch 11 - iter 147/493 - loss 0.03544229 - time (sec): 10.60 - samples/sec: 7304.00 - lr: 0.100000 +2023-03-29 16:49:27,731 epoch 11 - iter 196/493 - loss 0.03582510 - time (sec): 14.32 - samples/sec: 7262.77 - lr: 0.100000 +2023-03-29 16:49:31,302 epoch 11 - iter 245/493 - loss 0.03594562 - time (sec): 17.89 - samples/sec: 7234.66 - lr: 0.100000 +2023-03-29 16:49:34,722 epoch 11 - iter 294/493 - loss 0.03626975 - time (sec): 21.31 - samples/sec: 7257.21 - lr: 0.100000 +2023-03-29 16:49:38,208 epoch 11 - iter 343/493 - loss 0.03596812 - time (sec): 24.80 - samples/sec: 7271.58 - lr: 0.100000 +2023-03-29 16:49:44,560 epoch 11 - iter 392/493 - loss 0.03562583 - time (sec): 31.15 - samples/sec: 6615.04 - lr: 0.100000 +2023-03-29 16:49:48,180 epoch 11 - iter 441/493 - loss 0.03555375 - time (sec): 34.77 - samples/sec: 6673.95 - lr: 0.100000 +2023-03-29 16:49:51,555 epoch 11 - iter 490/493 - loss 0.03555316 - time (sec): 38.15 - samples/sec: 6751.87 - lr: 0.100000 +2023-03-29 16:49:51,751 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:49:51,751 EPOCH 11 done: loss 0.0356 - lr 0.100000 +2023-03-29 16:49:51,751 BAD EPOCHS (no improvement): 0 +2023-03-29 16:49:51,754 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:49:55,217 epoch 12 - iter 49/493 - loss 0.03491700 - time (sec): 3.46 - samples/sec: 7415.38 - lr: 0.100000 +2023-03-29 16:49:58,947 epoch 12 - iter 98/493 - loss 0.03448655 - time (sec): 7.19 - samples/sec: 7195.86 - lr: 0.100000 +2023-03-29 16:50:02,185 epoch 12 - iter 147/493 - loss 0.03407943 - time (sec): 10.43 - samples/sec: 7325.52 - lr: 0.100000 +2023-03-29 16:50:05,726 epoch 12 - iter 196/493 - loss 0.03345478 - time (sec): 13.97 - samples/sec: 7345.91 - lr: 0.100000 +2023-03-29 16:50:09,187 epoch 12 - iter 245/493 - loss 0.03372026 - time (sec): 17.43 - samples/sec: 7356.45 - lr: 0.100000 +2023-03-29 16:50:12,547 epoch 12 - iter 294/493 - loss 0.03358878 - time (sec): 20.79 - samples/sec: 7387.20 - lr: 0.100000 +2023-03-29 16:50:15,920 epoch 12 - iter 343/493 - loss 0.03394292 - time (sec): 24.17 - samples/sec: 7434.85 - lr: 0.100000 +2023-03-29 16:50:19,576 epoch 12 - iter 392/493 - loss 0.03407674 - time (sec): 27.82 - samples/sec: 7385.66 - lr: 0.100000 +2023-03-29 16:50:23,092 epoch 12 - iter 441/493 - loss 0.03392460 - time (sec): 31.34 - samples/sec: 7387.42 - lr: 0.100000 +2023-03-29 16:50:26,631 epoch 12 - iter 490/493 - loss 0.03411242 - time (sec): 34.88 - samples/sec: 7384.04 - lr: 0.100000 +2023-03-29 16:50:26,852 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:50:26,852 EPOCH 12 done: loss 0.0340 - lr 0.100000 +2023-03-29 16:50:26,852 BAD EPOCHS (no improvement): 0 +2023-03-29 16:50:26,855 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:50:30,525 epoch 13 - iter 49/493 - loss 0.03286744 - time (sec): 3.67 - samples/sec: 7186.84 - lr: 0.100000 +2023-03-29 16:50:34,045 epoch 13 - iter 98/493 - loss 0.03406802 - time (sec): 7.19 - samples/sec: 7255.69 - lr: 0.100000 +2023-03-29 16:50:37,643 epoch 13 - iter 147/493 - loss 0.03504269 - time (sec): 10.79 - samples/sec: 7267.80 - lr: 0.100000 +2023-03-29 16:50:41,176 epoch 13 - iter 196/493 - loss 0.03368493 - time (sec): 14.32 - samples/sec: 7238.02 - lr: 0.100000 +2023-03-29 16:50:44,549 epoch 13 - iter 245/493 - loss 0.03403303 - time (sec): 17.69 - samples/sec: 7286.09 - lr: 0.100000 +2023-03-29 16:50:48,076 epoch 13 - iter 294/493 - loss 0.03351105 - time (sec): 21.22 - samples/sec: 7317.20 - lr: 0.100000 +2023-03-29 16:50:51,477 epoch 13 - iter 343/493 - loss 0.03355732 - time (sec): 24.62 - samples/sec: 7337.05 - lr: 0.100000 +2023-03-29 16:50:55,117 epoch 13 - iter 392/493 - loss 0.03308972 - time (sec): 28.26 - samples/sec: 7319.27 - lr: 0.100000 +2023-03-29 16:50:58,441 epoch 13 - iter 441/493 - loss 0.03303461 - time (sec): 31.59 - samples/sec: 7339.40 - lr: 0.100000 +2023-03-29 16:51:02,113 epoch 13 - iter 490/493 - loss 0.03317976 - time (sec): 35.26 - samples/sec: 7306.18 - lr: 0.100000 +2023-03-29 16:51:02,313 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:51:02,313 EPOCH 13 done: loss 0.0332 - lr 0.100000 +2023-03-29 16:51:02,313 BAD EPOCHS (no improvement): 0 +2023-03-29 16:51:02,316 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:51:06,005 epoch 14 - iter 49/493 - loss 0.02607393 - time (sec): 3.69 - samples/sec: 7078.16 - lr: 0.100000 +2023-03-29 16:51:09,637 epoch 14 - iter 98/493 - loss 0.02998247 - time (sec): 7.32 - samples/sec: 7198.45 - lr: 0.100000 +2023-03-29 16:51:13,083 epoch 14 - iter 147/493 - loss 0.03053717 - time (sec): 10.77 - samples/sec: 7234.39 - lr: 0.100000 +2023-03-29 16:51:16,555 epoch 14 - iter 196/493 - loss 0.03118994 - time (sec): 14.24 - samples/sec: 7255.24 - lr: 0.100000 +2023-03-29 16:51:20,008 epoch 14 - iter 245/493 - loss 0.03121169 - time (sec): 17.69 - samples/sec: 7274.30 - lr: 0.100000 +2023-03-29 16:51:23,499 epoch 14 - iter 294/493 - loss 0.03151520 - time (sec): 21.18 - samples/sec: 7288.50 - lr: 0.100000 +2023-03-29 16:51:26,894 epoch 14 - iter 343/493 - loss 0.03136935 - time (sec): 24.58 - samples/sec: 7304.39 - lr: 0.100000 +2023-03-29 16:51:30,450 epoch 14 - iter 392/493 - loss 0.03147462 - time (sec): 28.13 - samples/sec: 7307.28 - lr: 0.100000 +2023-03-29 16:51:33,891 epoch 14 - iter 441/493 - loss 0.03181244 - time (sec): 31.58 - samples/sec: 7340.58 - lr: 0.100000 +2023-03-29 16:51:37,309 epoch 14 - iter 490/493 - loss 0.03192350 - time (sec): 34.99 - samples/sec: 7364.55 - lr: 0.100000 +2023-03-29 16:51:37,520 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:51:37,521 EPOCH 14 done: loss 0.0319 - lr 0.100000 +2023-03-29 16:51:37,521 BAD EPOCHS (no improvement): 0 +2023-03-29 16:51:37,523 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:51:40,987 epoch 15 - iter 49/493 - loss 0.02819409 - time (sec): 3.46 - samples/sec: 7526.26 - lr: 0.100000 +2023-03-29 16:51:44,515 epoch 15 - iter 98/493 - loss 0.02975221 - time (sec): 6.99 - samples/sec: 7532.35 - lr: 0.100000 +2023-03-29 16:51:47,886 epoch 15 - iter 147/493 - loss 0.02896187 - time (sec): 10.36 - samples/sec: 7563.21 - lr: 0.100000 +2023-03-29 16:51:51,243 epoch 15 - iter 196/493 - loss 0.02871311 - time (sec): 13.72 - samples/sec: 7602.57 - lr: 0.100000 +2023-03-29 16:51:54,604 epoch 15 - iter 245/493 - loss 0.02948830 - time (sec): 17.08 - samples/sec: 7601.25 - lr: 0.100000 +2023-03-29 16:51:58,096 epoch 15 - iter 294/493 - loss 0.02948580 - time (sec): 20.57 - samples/sec: 7526.29 - lr: 0.100000 +2023-03-29 16:52:01,798 epoch 15 - iter 343/493 - loss 0.02958343 - time (sec): 24.27 - samples/sec: 7453.85 - lr: 0.100000 +2023-03-29 16:52:05,344 epoch 15 - iter 392/493 - loss 0.02970103 - time (sec): 27.82 - samples/sec: 7432.83 - lr: 0.100000 +2023-03-29 16:52:08,761 epoch 15 - iter 441/493 - loss 0.02973647 - time (sec): 31.24 - samples/sec: 7421.93 - lr: 0.100000 +2023-03-29 16:52:12,289 epoch 15 - iter 490/493 - loss 0.03001027 - time (sec): 34.77 - samples/sec: 7410.79 - lr: 0.100000 +2023-03-29 16:52:12,503 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:52:12,503 EPOCH 15 done: loss 0.0301 - lr 0.100000 +2023-03-29 16:52:12,503 BAD EPOCHS (no improvement): 0 +2023-03-29 16:52:12,506 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:52:16,022 epoch 16 - iter 49/493 - loss 0.02885649 - time (sec): 3.52 - samples/sec: 7218.64 - lr: 0.100000 +2023-03-29 16:52:19,583 epoch 16 - iter 98/493 - loss 0.02956793 - time (sec): 7.08 - samples/sec: 7233.33 - lr: 0.100000 +2023-03-29 16:52:22,864 epoch 16 - iter 147/493 - loss 0.02855421 - time (sec): 10.36 - samples/sec: 7311.61 - lr: 0.100000 +2023-03-29 16:52:26,386 epoch 16 - iter 196/493 - loss 0.02881925 - time (sec): 13.88 - samples/sec: 7340.35 - lr: 0.100000 +2023-03-29 16:52:29,973 epoch 16 - iter 245/493 - loss 0.02917363 - time (sec): 17.47 - samples/sec: 7357.81 - lr: 0.100000 +2023-03-29 16:52:33,303 epoch 16 - iter 294/493 - loss 0.02905890 - time (sec): 20.80 - samples/sec: 7415.52 - lr: 0.100000 +2023-03-29 16:52:36,687 epoch 16 - iter 343/493 - loss 0.02902118 - time (sec): 24.18 - samples/sec: 7450.31 - lr: 0.100000 +2023-03-29 16:52:40,244 epoch 16 - iter 392/493 - loss 0.02911782 - time (sec): 27.74 - samples/sec: 7447.17 - lr: 0.100000 +2023-03-29 16:52:43,519 epoch 16 - iter 441/493 - loss 0.02917781 - time (sec): 31.01 - samples/sec: 7460.22 - lr: 0.100000 +2023-03-29 16:52:47,048 epoch 16 - iter 490/493 - loss 0.02902898 - time (sec): 34.54 - samples/sec: 7458.98 - lr: 0.100000 +2023-03-29 16:52:47,253 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:52:47,253 EPOCH 16 done: loss 0.0290 - lr 0.100000 +2023-03-29 16:52:47,253 BAD EPOCHS (no improvement): 0 +2023-03-29 16:52:47,255 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:52:50,689 epoch 17 - iter 49/493 - loss 0.02809275 - time (sec): 3.43 - samples/sec: 7421.70 - lr: 0.100000 +2023-03-29 16:52:53,987 epoch 17 - iter 98/493 - loss 0.02817160 - time (sec): 6.73 - samples/sec: 7476.99 - lr: 0.100000 +2023-03-29 16:52:57,338 epoch 17 - iter 147/493 - loss 0.02799345 - time (sec): 10.08 - samples/sec: 7548.19 - lr: 0.100000 +2023-03-29 16:53:00,763 epoch 17 - iter 196/493 - loss 0.02827564 - time (sec): 13.51 - samples/sec: 7513.88 - lr: 0.100000 +2023-03-29 16:53:04,239 epoch 17 - iter 245/493 - loss 0.02817585 - time (sec): 16.98 - samples/sec: 7503.70 - lr: 0.100000 +2023-03-29 16:53:07,856 epoch 17 - iter 294/493 - loss 0.02844140 - time (sec): 20.60 - samples/sec: 7453.22 - lr: 0.100000 +2023-03-29 16:53:11,147 epoch 17 - iter 343/493 - loss 0.02840434 - time (sec): 23.89 - samples/sec: 7490.65 - lr: 0.100000 +2023-03-29 16:53:14,716 epoch 17 - iter 392/493 - loss 0.02814949 - time (sec): 27.46 - samples/sec: 7492.98 - lr: 0.100000 +2023-03-29 16:53:18,290 epoch 17 - iter 441/493 - loss 0.02821183 - time (sec): 31.03 - samples/sec: 7476.49 - lr: 0.100000 +2023-03-29 16:53:21,733 epoch 17 - iter 490/493 - loss 0.02861115 - time (sec): 34.48 - samples/sec: 7472.44 - lr: 0.100000 +2023-03-29 16:53:21,956 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:53:21,956 EPOCH 17 done: loss 0.0287 - lr 0.100000 +2023-03-29 16:53:21,956 BAD EPOCHS (no improvement): 0 +2023-03-29 16:53:21,959 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:53:25,361 epoch 18 - iter 49/493 - loss 0.02505381 - time (sec): 3.40 - samples/sec: 7421.34 - lr: 0.100000 +2023-03-29 16:53:28,992 epoch 18 - iter 98/493 - loss 0.02566057 - time (sec): 7.03 - samples/sec: 7292.07 - lr: 0.100000 +2023-03-29 16:53:32,582 epoch 18 - iter 147/493 - loss 0.02717920 - time (sec): 10.62 - samples/sec: 7293.06 - lr: 0.100000 +2023-03-29 16:53:36,137 epoch 18 - iter 196/493 - loss 0.02619533 - time (sec): 14.18 - samples/sec: 7291.12 - lr: 0.100000 +2023-03-29 16:53:39,540 epoch 18 - iter 245/493 - loss 0.02697691 - time (sec): 17.58 - samples/sec: 7334.68 - lr: 0.100000 +2023-03-29 16:53:42,916 epoch 18 - iter 294/493 - loss 0.02737061 - time (sec): 20.96 - samples/sec: 7370.69 - lr: 0.100000 +2023-03-29 16:53:46,411 epoch 18 - iter 343/493 - loss 0.02737739 - time (sec): 24.45 - samples/sec: 7381.99 - lr: 0.100000 +2023-03-29 16:53:49,774 epoch 18 - iter 392/493 - loss 0.02733425 - time (sec): 27.82 - samples/sec: 7412.24 - lr: 0.100000 +2023-03-29 16:53:53,175 epoch 18 - iter 441/493 - loss 0.02719115 - time (sec): 31.22 - samples/sec: 7412.58 - lr: 0.100000 +2023-03-29 16:53:56,764 epoch 18 - iter 490/493 - loss 0.02743921 - time (sec): 34.80 - samples/sec: 7397.17 - lr: 0.100000 +2023-03-29 16:53:56,976 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:53:56,976 EPOCH 18 done: loss 0.0275 - lr 0.100000 +2023-03-29 16:53:56,976 BAD EPOCHS (no improvement): 0 +2023-03-29 16:53:56,979 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:54:00,442 epoch 19 - iter 49/493 - loss 0.02522647 - time (sec): 3.46 - samples/sec: 7383.88 - lr: 0.100000 +2023-03-29 16:54:03,946 epoch 19 - iter 98/493 - loss 0.02666554 - time (sec): 6.97 - samples/sec: 7298.43 - lr: 0.100000 +2023-03-29 16:54:07,635 epoch 19 - iter 147/493 - loss 0.02635048 - time (sec): 10.66 - samples/sec: 7248.31 - lr: 0.100000 +2023-03-29 16:54:10,989 epoch 19 - iter 196/493 - loss 0.02605426 - time (sec): 14.01 - samples/sec: 7336.96 - lr: 0.100000 +2023-03-29 16:54:14,426 epoch 19 - iter 245/493 - loss 0.02609494 - time (sec): 17.45 - samples/sec: 7346.52 - lr: 0.100000 +2023-03-29 16:54:17,931 epoch 19 - iter 294/493 - loss 0.02540040 - time (sec): 20.95 - samples/sec: 7366.71 - lr: 0.100000 +2023-03-29 16:54:21,374 epoch 19 - iter 343/493 - loss 0.02600550 - time (sec): 24.39 - samples/sec: 7370.70 - lr: 0.100000 +2023-03-29 16:54:24,781 epoch 19 - iter 392/493 - loss 0.02636907 - time (sec): 27.80 - samples/sec: 7416.99 - lr: 0.100000 +2023-03-29 16:54:28,203 epoch 19 - iter 441/493 - loss 0.02621604 - time (sec): 31.22 - samples/sec: 7431.68 - lr: 0.100000 +2023-03-29 16:54:31,587 epoch 19 - iter 490/493 - loss 0.02622509 - time (sec): 34.61 - samples/sec: 7443.55 - lr: 0.100000 +2023-03-29 16:54:31,803 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:54:31,803 EPOCH 19 done: loss 0.0261 - lr 0.100000 +2023-03-29 16:54:31,803 BAD EPOCHS (no improvement): 0 +2023-03-29 16:54:31,806 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:54:35,299 epoch 20 - iter 49/493 - loss 0.02261473 - time (sec): 3.49 - samples/sec: 7428.57 - lr: 0.100000 +2023-03-29 16:54:38,759 epoch 20 - iter 98/493 - loss 0.02338803 - time (sec): 6.95 - samples/sec: 7473.40 - lr: 0.100000 +2023-03-29 16:54:42,116 epoch 20 - iter 147/493 - loss 0.02413707 - time (sec): 10.31 - samples/sec: 7505.11 - lr: 0.100000 +2023-03-29 16:54:45,539 epoch 20 - iter 196/493 - loss 0.02438812 - time (sec): 13.73 - samples/sec: 7498.12 - lr: 0.100000 +2023-03-29 16:54:48,952 epoch 20 - iter 245/493 - loss 0.02509863 - time (sec): 17.15 - samples/sec: 7449.20 - lr: 0.100000 +2023-03-29 16:54:52,544 epoch 20 - iter 294/493 - loss 0.02548981 - time (sec): 20.74 - samples/sec: 7424.67 - lr: 0.100000 +2023-03-29 16:54:56,087 epoch 20 - iter 343/493 - loss 0.02576187 - time (sec): 24.28 - samples/sec: 7424.90 - lr: 0.100000 +2023-03-29 16:54:59,659 epoch 20 - iter 392/493 - loss 0.02583905 - time (sec): 27.85 - samples/sec: 7383.33 - lr: 0.100000 +2023-03-29 16:55:03,133 epoch 20 - iter 441/493 - loss 0.02555222 - time (sec): 31.33 - samples/sec: 7390.61 - lr: 0.100000 +2023-03-29 16:55:06,579 epoch 20 - iter 490/493 - loss 0.02572386 - time (sec): 34.77 - samples/sec: 7407.18 - lr: 0.100000 +2023-03-29 16:55:06,779 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:55:06,779 EPOCH 20 done: loss 0.0257 - lr 0.100000 +2023-03-29 16:55:06,779 BAD EPOCHS (no improvement): 0 +2023-03-29 16:55:06,782 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:55:10,358 epoch 21 - iter 49/493 - loss 0.02230234 - time (sec): 3.58 - samples/sec: 7170.68 - lr: 0.100000 +2023-03-29 16:55:13,782 epoch 21 - iter 98/493 - loss 0.02296165 - time (sec): 7.00 - samples/sec: 7308.87 - lr: 0.100000 +2023-03-29 16:55:17,342 epoch 21 - iter 147/493 - loss 0.02381138 - time (sec): 10.56 - samples/sec: 7309.12 - lr: 0.100000 +2023-03-29 16:55:20,799 epoch 21 - iter 196/493 - loss 0.02360520 - time (sec): 14.02 - samples/sec: 7354.02 - lr: 0.100000 +2023-03-29 16:55:24,247 epoch 21 - iter 245/493 - loss 0.02404954 - time (sec): 17.46 - samples/sec: 7367.70 - lr: 0.100000 +2023-03-29 16:55:27,625 epoch 21 - iter 294/493 - loss 0.02464552 - time (sec): 20.84 - samples/sec: 7397.59 - lr: 0.100000 +2023-03-29 16:55:30,915 epoch 21 - iter 343/493 - loss 0.02498145 - time (sec): 24.13 - samples/sec: 7445.29 - lr: 0.100000 +2023-03-29 16:55:34,648 epoch 21 - iter 392/493 - loss 0.02466062 - time (sec): 27.87 - samples/sec: 7407.81 - lr: 0.100000 +2023-03-29 16:55:38,090 epoch 21 - iter 441/493 - loss 0.02464145 - time (sec): 31.31 - samples/sec: 7417.13 - lr: 0.100000 +2023-03-29 16:55:41,514 epoch 21 - iter 490/493 - loss 0.02471447 - time (sec): 34.73 - samples/sec: 7419.10 - lr: 0.100000 +2023-03-29 16:55:41,719 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:55:41,719 EPOCH 21 done: loss 0.0247 - lr 0.100000 +2023-03-29 16:55:41,720 BAD EPOCHS (no improvement): 0 +2023-03-29 16:55:41,722 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:55:45,122 epoch 22 - iter 49/493 - loss 0.02427077 - time (sec): 3.40 - samples/sec: 7657.38 - lr: 0.100000 +2023-03-29 16:55:48,633 epoch 22 - iter 98/493 - loss 0.02580996 - time (sec): 6.91 - samples/sec: 7513.27 - lr: 0.100000 +2023-03-29 16:55:51,990 epoch 22 - iter 147/493 - loss 0.02482537 - time (sec): 10.27 - samples/sec: 7497.12 - lr: 0.100000 +2023-03-29 16:55:55,426 epoch 22 - iter 196/493 - loss 0.02461447 - time (sec): 13.70 - samples/sec: 7535.37 - lr: 0.100000 +2023-03-29 16:55:58,951 epoch 22 - iter 245/493 - loss 0.02492944 - time (sec): 17.23 - samples/sec: 7520.11 - lr: 0.100000 +2023-03-29 16:56:02,486 epoch 22 - iter 294/493 - loss 0.02466471 - time (sec): 20.76 - samples/sec: 7473.86 - lr: 0.100000 +2023-03-29 16:56:05,822 epoch 22 - iter 343/493 - loss 0.02423040 - time (sec): 24.10 - samples/sec: 7484.40 - lr: 0.100000 +2023-03-29 16:56:09,396 epoch 22 - iter 392/493 - loss 0.02433423 - time (sec): 27.67 - samples/sec: 7456.88 - lr: 0.100000 +2023-03-29 16:56:12,803 epoch 22 - iter 441/493 - loss 0.02423754 - time (sec): 31.08 - samples/sec: 7438.74 - lr: 0.100000 +2023-03-29 16:56:16,336 epoch 22 - iter 490/493 - loss 0.02434931 - time (sec): 34.61 - samples/sec: 7439.05 - lr: 0.100000 +2023-03-29 16:56:16,578 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:56:16,578 EPOCH 22 done: loss 0.0243 - lr 0.100000 +2023-03-29 16:56:16,578 BAD EPOCHS (no improvement): 0 +2023-03-29 16:56:16,581 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:56:20,162 epoch 23 - iter 49/493 - loss 0.02359272 - time (sec): 3.58 - samples/sec: 7301.46 - lr: 0.100000 +2023-03-29 16:56:23,514 epoch 23 - iter 98/493 - loss 0.02420099 - time (sec): 6.93 - samples/sec: 7350.27 - lr: 0.100000 +2023-03-29 16:56:27,111 epoch 23 - iter 147/493 - loss 0.02390837 - time (sec): 10.53 - samples/sec: 7295.33 - lr: 0.100000 +2023-03-29 16:56:30,803 epoch 23 - iter 196/493 - loss 0.02386080 - time (sec): 14.22 - samples/sec: 7235.51 - lr: 0.100000 +2023-03-29 16:56:34,331 epoch 23 - iter 245/493 - loss 0.02349786 - time (sec): 17.75 - samples/sec: 7240.32 - lr: 0.100000 +2023-03-29 16:56:37,963 epoch 23 - iter 294/493 - loss 0.02318388 - time (sec): 21.38 - samples/sec: 7232.17 - lr: 0.100000 +2023-03-29 16:56:41,545 epoch 23 - iter 343/493 - loss 0.02338028 - time (sec): 24.96 - samples/sec: 7240.44 - lr: 0.100000 +2023-03-29 16:56:44,985 epoch 23 - iter 392/493 - loss 0.02360155 - time (sec): 28.40 - samples/sec: 7266.07 - lr: 0.100000 +2023-03-29 16:56:48,448 epoch 23 - iter 441/493 - loss 0.02397330 - time (sec): 31.87 - samples/sec: 7279.46 - lr: 0.100000 +2023-03-29 16:56:51,903 epoch 23 - iter 490/493 - loss 0.02395066 - time (sec): 35.32 - samples/sec: 7291.49 - lr: 0.100000 +2023-03-29 16:56:52,130 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:56:52,131 EPOCH 23 done: loss 0.0239 - lr 0.100000 +2023-03-29 16:56:52,131 BAD EPOCHS (no improvement): 0 +2023-03-29 16:56:52,133 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:56:55,518 epoch 24 - iter 49/493 - loss 0.02095970 - time (sec): 3.39 - samples/sec: 7656.77 - lr: 0.100000 +2023-03-29 16:56:59,044 epoch 24 - iter 98/493 - loss 0.02328984 - time (sec): 6.91 - samples/sec: 7518.07 - lr: 0.100000 +2023-03-29 16:57:02,592 epoch 24 - iter 147/493 - loss 0.02424203 - time (sec): 10.46 - samples/sec: 7458.15 - lr: 0.100000 +2023-03-29 16:57:06,016 epoch 24 - iter 196/493 - loss 0.02367765 - time (sec): 13.88 - samples/sec: 7490.98 - lr: 0.100000 +2023-03-29 16:57:09,380 epoch 24 - iter 245/493 - loss 0.02314913 - time (sec): 17.25 - samples/sec: 7506.28 - lr: 0.100000 +2023-03-29 16:57:12,843 epoch 24 - iter 294/493 - loss 0.02319669 - time (sec): 20.71 - samples/sec: 7480.45 - lr: 0.100000 +2023-03-29 16:57:16,329 epoch 24 - iter 343/493 - loss 0.02329273 - time (sec): 24.20 - samples/sec: 7457.53 - lr: 0.100000 +2023-03-29 16:57:19,746 epoch 24 - iter 392/493 - loss 0.02327041 - time (sec): 27.61 - samples/sec: 7462.46 - lr: 0.100000 +2023-03-29 16:57:23,072 epoch 24 - iter 441/493 - loss 0.02335046 - time (sec): 30.94 - samples/sec: 7484.59 - lr: 0.100000 +2023-03-29 16:57:26,462 epoch 24 - iter 490/493 - loss 0.02332618 - time (sec): 34.33 - samples/sec: 7498.66 - lr: 0.100000 +2023-03-29 16:57:26,711 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:57:26,711 EPOCH 24 done: loss 0.0233 - lr 0.100000 +2023-03-29 16:57:26,712 BAD EPOCHS (no improvement): 0 +2023-03-29 16:57:26,714 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:57:30,266 epoch 25 - iter 49/493 - loss 0.02248101 - time (sec): 3.55 - samples/sec: 7347.62 - lr: 0.100000 +2023-03-29 16:57:33,724 epoch 25 - iter 98/493 - loss 0.02274761 - time (sec): 7.01 - samples/sec: 7456.50 - lr: 0.100000 +2023-03-29 16:57:37,115 epoch 25 - iter 147/493 - loss 0.02235646 - time (sec): 10.40 - samples/sec: 7508.82 - lr: 0.100000 +2023-03-29 16:57:40,615 epoch 25 - iter 196/493 - loss 0.02197934 - time (sec): 13.90 - samples/sec: 7474.03 - lr: 0.100000 +2023-03-29 16:57:44,057 epoch 25 - iter 245/493 - loss 0.02217488 - time (sec): 17.34 - samples/sec: 7471.17 - lr: 0.100000 +2023-03-29 16:57:47,552 epoch 25 - iter 294/493 - loss 0.02251446 - time (sec): 20.84 - samples/sec: 7443.73 - lr: 0.100000 +2023-03-29 16:57:50,919 epoch 25 - iter 343/493 - loss 0.02266783 - time (sec): 24.21 - samples/sec: 7447.12 - lr: 0.100000 +2023-03-29 16:57:54,388 epoch 25 - iter 392/493 - loss 0.02276777 - time (sec): 27.67 - samples/sec: 7457.66 - lr: 0.100000 +2023-03-29 16:57:57,701 epoch 25 - iter 441/493 - loss 0.02291707 - time (sec): 30.99 - samples/sec: 7493.77 - lr: 0.100000 +2023-03-29 16:58:01,002 epoch 25 - iter 490/493 - loss 0.02290020 - time (sec): 34.29 - samples/sec: 7522.17 - lr: 0.100000 +2023-03-29 16:58:01,154 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:58:01,155 EPOCH 25 done: loss 0.0229 - lr 0.100000 +2023-03-29 16:58:01,155 BAD EPOCHS (no improvement): 0 +2023-03-29 16:58:01,157 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:58:04,610 epoch 26 - iter 49/493 - loss 0.02121337 - time (sec): 3.45 - samples/sec: 7602.00 - lr: 0.100000 +2023-03-29 16:58:08,034 epoch 26 - iter 98/493 - loss 0.02081900 - time (sec): 6.88 - samples/sec: 7537.43 - lr: 0.100000 +2023-03-29 16:58:11,496 epoch 26 - iter 147/493 - loss 0.02158772 - time (sec): 10.34 - samples/sec: 7492.35 - lr: 0.100000 +2023-03-29 16:58:15,045 epoch 26 - iter 196/493 - loss 0.02148317 - time (sec): 13.89 - samples/sec: 7482.44 - lr: 0.100000 +2023-03-29 16:58:18,392 epoch 26 - iter 245/493 - loss 0.02160603 - time (sec): 17.23 - samples/sec: 7487.59 - lr: 0.100000 +2023-03-29 16:58:21,821 epoch 26 - iter 294/493 - loss 0.02170775 - time (sec): 20.66 - samples/sec: 7483.18 - lr: 0.100000 +2023-03-29 16:58:25,264 epoch 26 - iter 343/493 - loss 0.02175861 - time (sec): 24.11 - samples/sec: 7498.01 - lr: 0.100000 +2023-03-29 16:58:28,677 epoch 26 - iter 392/493 - loss 0.02189150 - time (sec): 27.52 - samples/sec: 7496.63 - lr: 0.100000 +2023-03-29 16:58:32,113 epoch 26 - iter 441/493 - loss 0.02204473 - time (sec): 30.96 - samples/sec: 7489.15 - lr: 0.100000 +2023-03-29 16:58:35,573 epoch 26 - iter 490/493 - loss 0.02232022 - time (sec): 34.42 - samples/sec: 7486.86 - lr: 0.100000 +2023-03-29 16:58:35,785 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:58:35,786 EPOCH 26 done: loss 0.0223 - lr 0.100000 +2023-03-29 16:58:35,786 BAD EPOCHS (no improvement): 0 +2023-03-29 16:58:35,789 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:58:39,265 epoch 27 - iter 49/493 - loss 0.01936595 - time (sec): 3.48 - samples/sec: 7545.22 - lr: 0.100000 +2023-03-29 16:58:42,893 epoch 27 - iter 98/493 - loss 0.02046637 - time (sec): 7.10 - samples/sec: 7351.79 - lr: 0.100000 +2023-03-29 16:58:46,341 epoch 27 - iter 147/493 - loss 0.02126493 - time (sec): 10.55 - samples/sec: 7379.64 - lr: 0.100000 +2023-03-29 16:58:49,889 epoch 27 - iter 196/493 - loss 0.02156718 - time (sec): 14.10 - samples/sec: 7382.85 - lr: 0.100000 +2023-03-29 16:58:53,286 epoch 27 - iter 245/493 - loss 0.02159603 - time (sec): 17.50 - samples/sec: 7437.47 - lr: 0.100000 +2023-03-29 16:58:56,638 epoch 27 - iter 294/493 - loss 0.02162616 - time (sec): 20.85 - samples/sec: 7473.92 - lr: 0.100000 +2023-03-29 16:59:00,021 epoch 27 - iter 343/493 - loss 0.02169039 - time (sec): 24.23 - samples/sec: 7472.82 - lr: 0.100000 +2023-03-29 16:59:03,381 epoch 27 - iter 392/493 - loss 0.02196524 - time (sec): 27.59 - samples/sec: 7484.73 - lr: 0.100000 +2023-03-29 16:59:06,783 epoch 27 - iter 441/493 - loss 0.02198872 - time (sec): 30.99 - samples/sec: 7487.22 - lr: 0.100000 +2023-03-29 16:59:10,224 epoch 27 - iter 490/493 - loss 0.02197725 - time (sec): 34.44 - samples/sec: 7486.01 - lr: 0.100000 +2023-03-29 16:59:10,417 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:59:10,417 EPOCH 27 done: loss 0.0220 - lr 0.100000 +2023-03-29 16:59:10,417 BAD EPOCHS (no improvement): 0 +2023-03-29 16:59:10,420 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:59:13,795 epoch 28 - iter 49/493 - loss 0.01817396 - time (sec): 3.37 - samples/sec: 7569.99 - lr: 0.100000 +2023-03-29 16:59:17,035 epoch 28 - iter 98/493 - loss 0.01993294 - time (sec): 6.62 - samples/sec: 7728.02 - lr: 0.100000 +2023-03-29 16:59:20,543 epoch 28 - iter 147/493 - loss 0.02037421 - time (sec): 10.12 - samples/sec: 7620.04 - lr: 0.100000 +2023-03-29 16:59:23,832 epoch 28 - iter 196/493 - loss 0.02027088 - time (sec): 13.41 - samples/sec: 7618.38 - lr: 0.100000 +2023-03-29 16:59:27,228 epoch 28 - iter 245/493 - loss 0.02043651 - time (sec): 16.81 - samples/sec: 7630.34 - lr: 0.100000 +2023-03-29 16:59:30,799 epoch 28 - iter 294/493 - loss 0.02062145 - time (sec): 20.38 - samples/sec: 7603.02 - lr: 0.100000 +2023-03-29 16:59:34,193 epoch 28 - iter 343/493 - loss 0.02057760 - time (sec): 23.77 - samples/sec: 7592.12 - lr: 0.100000 +2023-03-29 16:59:37,670 epoch 28 - iter 392/493 - loss 0.02107826 - time (sec): 27.25 - samples/sec: 7559.59 - lr: 0.100000 +2023-03-29 16:59:41,308 epoch 28 - iter 441/493 - loss 0.02149576 - time (sec): 30.89 - samples/sec: 7519.09 - lr: 0.100000 +2023-03-29 16:59:44,575 epoch 28 - iter 490/493 - loss 0.02140158 - time (sec): 34.15 - samples/sec: 7544.17 - lr: 0.100000 +2023-03-29 16:59:44,756 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:59:44,756 EPOCH 28 done: loss 0.0214 - lr 0.100000 +2023-03-29 16:59:44,756 BAD EPOCHS (no improvement): 0 +2023-03-29 16:59:44,759 ---------------------------------------------------------------------------------------------------- +2023-03-29 16:59:48,463 epoch 29 - iter 49/493 - loss 0.02004433 - time (sec): 3.70 - samples/sec: 7020.39 - lr: 0.100000 +2023-03-29 16:59:51,927 epoch 29 - iter 98/493 - loss 0.02018283 - time (sec): 7.17 - samples/sec: 7248.82 - lr: 0.100000 +2023-03-29 16:59:55,475 epoch 29 - iter 147/493 - loss 0.01976671 - time (sec): 10.72 - samples/sec: 7370.52 - lr: 0.100000 +2023-03-29 16:59:58,896 epoch 29 - iter 196/493 - loss 0.01972188 - time (sec): 14.14 - samples/sec: 7376.56 - lr: 0.100000 +2023-03-29 17:00:02,459 epoch 29 - iter 245/493 - loss 0.02013960 - time (sec): 17.70 - samples/sec: 7345.55 - lr: 0.100000 +2023-03-29 17:00:05,916 epoch 29 - iter 294/493 - loss 0.02049491 - time (sec): 21.16 - samples/sec: 7352.49 - lr: 0.100000 +2023-03-29 17:00:09,470 epoch 29 - iter 343/493 - loss 0.02100287 - time (sec): 24.71 - samples/sec: 7339.05 - lr: 0.100000 +2023-03-29 17:00:13,005 epoch 29 - iter 392/493 - loss 0.02139835 - time (sec): 28.25 - samples/sec: 7328.32 - lr: 0.100000 +2023-03-29 17:00:16,365 epoch 29 - iter 441/493 - loss 0.02136569 - time (sec): 31.61 - samples/sec: 7344.73 - lr: 0.100000 +2023-03-29 17:00:19,731 epoch 29 - iter 490/493 - loss 0.02103539 - time (sec): 34.97 - samples/sec: 7366.77 - lr: 0.100000 +2023-03-29 17:00:19,919 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:00:19,919 EPOCH 29 done: loss 0.0211 - lr 0.100000 +2023-03-29 17:00:19,919 BAD EPOCHS (no improvement): 0 +2023-03-29 17:00:19,922 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:00:23,334 epoch 30 - iter 49/493 - loss 0.02147030 - time (sec): 3.41 - samples/sec: 7513.04 - lr: 0.100000 +2023-03-29 17:00:26,692 epoch 30 - iter 98/493 - loss 0.02071065 - time (sec): 6.77 - samples/sec: 7543.61 - lr: 0.100000 +2023-03-29 17:00:30,244 epoch 30 - iter 147/493 - loss 0.02038991 - time (sec): 10.32 - samples/sec: 7443.01 - lr: 0.100000 +2023-03-29 17:00:33,696 epoch 30 - iter 196/493 - loss 0.01993747 - time (sec): 13.77 - samples/sec: 7465.51 - lr: 0.100000 +2023-03-29 17:00:37,202 epoch 30 - iter 245/493 - loss 0.02010334 - time (sec): 17.28 - samples/sec: 7460.56 - lr: 0.100000 +2023-03-29 17:00:40,707 epoch 30 - iter 294/493 - loss 0.02037618 - time (sec): 20.79 - samples/sec: 7444.31 - lr: 0.100000 +2023-03-29 17:00:44,109 epoch 30 - iter 343/493 - loss 0.02047890 - time (sec): 24.19 - samples/sec: 7448.45 - lr: 0.100000 +2023-03-29 17:00:47,506 epoch 30 - iter 392/493 - loss 0.02095414 - time (sec): 27.58 - samples/sec: 7451.52 - lr: 0.100000 +2023-03-29 17:00:50,851 epoch 30 - iter 441/493 - loss 0.02134298 - time (sec): 30.93 - samples/sec: 7497.46 - lr: 0.100000 +2023-03-29 17:00:54,243 epoch 30 - iter 490/493 - loss 0.02140982 - time (sec): 34.32 - samples/sec: 7504.63 - lr: 0.100000 +2023-03-29 17:00:54,449 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:00:54,449 EPOCH 30 done: loss 0.0214 - lr 0.100000 +2023-03-29 17:00:54,449 BAD EPOCHS (no improvement): 1 +2023-03-29 17:00:54,452 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:00:57,878 epoch 31 - iter 49/493 - loss 0.01921930 - time (sec): 3.43 - samples/sec: 7534.61 - lr: 0.100000 +2023-03-29 17:01:01,238 epoch 31 - iter 98/493 - loss 0.01979540 - time (sec): 6.79 - samples/sec: 7593.91 - lr: 0.100000 +2023-03-29 17:01:04,533 epoch 31 - iter 147/493 - loss 0.02032389 - time (sec): 10.08 - samples/sec: 7615.78 - lr: 0.100000 +2023-03-29 17:01:08,052 epoch 31 - iter 196/493 - loss 0.02106022 - time (sec): 13.60 - samples/sec: 7588.18 - lr: 0.100000 +2023-03-29 17:01:11,341 epoch 31 - iter 245/493 - loss 0.02059598 - time (sec): 16.89 - samples/sec: 7576.95 - lr: 0.100000 +2023-03-29 17:01:14,726 epoch 31 - iter 294/493 - loss 0.02049102 - time (sec): 20.27 - samples/sec: 7599.15 - lr: 0.100000 +2023-03-29 17:01:18,305 epoch 31 - iter 343/493 - loss 0.02002229 - time (sec): 23.85 - samples/sec: 7556.16 - lr: 0.100000 +2023-03-29 17:01:21,704 epoch 31 - iter 392/493 - loss 0.01990785 - time (sec): 27.25 - samples/sec: 7565.72 - lr: 0.100000 +2023-03-29 17:01:25,211 epoch 31 - iter 441/493 - loss 0.01990999 - time (sec): 30.76 - samples/sec: 7552.65 - lr: 0.100000 +2023-03-29 17:01:28,617 epoch 31 - iter 490/493 - loss 0.01977638 - time (sec): 34.17 - samples/sec: 7544.21 - lr: 0.100000 +2023-03-29 17:01:28,792 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:01:28,793 EPOCH 31 done: loss 0.0199 - lr 0.100000 +2023-03-29 17:01:28,793 BAD EPOCHS (no improvement): 0 +2023-03-29 17:01:28,796 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:01:32,196 epoch 32 - iter 49/493 - loss 0.01670713 - time (sec): 3.40 - samples/sec: 7328.94 - lr: 0.100000 +2023-03-29 17:01:35,665 epoch 32 - iter 98/493 - loss 0.01803757 - time (sec): 6.87 - samples/sec: 7377.19 - lr: 0.100000 +2023-03-29 17:01:39,079 epoch 32 - iter 147/493 - loss 0.01853837 - time (sec): 10.28 - samples/sec: 7435.13 - lr: 0.100000 +2023-03-29 17:01:42,619 epoch 32 - iter 196/493 - loss 0.01865148 - time (sec): 13.82 - samples/sec: 7399.52 - lr: 0.100000 +2023-03-29 17:01:46,006 epoch 32 - iter 245/493 - loss 0.01941646 - time (sec): 17.21 - samples/sec: 7447.13 - lr: 0.100000 +2023-03-29 17:01:49,405 epoch 32 - iter 294/493 - loss 0.01942109 - time (sec): 20.61 - samples/sec: 7466.68 - lr: 0.100000 +2023-03-29 17:01:52,741 epoch 32 - iter 343/493 - loss 0.01914671 - time (sec): 23.94 - samples/sec: 7491.61 - lr: 0.100000 +2023-03-29 17:01:56,241 epoch 32 - iter 392/493 - loss 0.01956232 - time (sec): 27.45 - samples/sec: 7484.30 - lr: 0.100000 +2023-03-29 17:01:59,739 epoch 32 - iter 441/493 - loss 0.01963566 - time (sec): 30.94 - samples/sec: 7481.46 - lr: 0.100000 +2023-03-29 17:02:03,255 epoch 32 - iter 490/493 - loss 0.01958624 - time (sec): 34.46 - samples/sec: 7467.47 - lr: 0.100000 +2023-03-29 17:02:03,511 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:02:03,511 EPOCH 32 done: loss 0.0195 - lr 0.100000 +2023-03-29 17:02:03,511 BAD EPOCHS (no improvement): 0 +2023-03-29 17:02:03,515 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:02:09,836 epoch 33 - iter 49/493 - loss 0.01773546 - time (sec): 6.32 - samples/sec: 4065.61 - lr: 0.100000 +2023-03-29 17:02:13,367 epoch 33 - iter 98/493 - loss 0.01758205 - time (sec): 9.85 - samples/sec: 5233.97 - lr: 0.100000 +2023-03-29 17:02:16,801 epoch 33 - iter 147/493 - loss 0.01691064 - time (sec): 13.29 - samples/sec: 5817.72 - lr: 0.100000 +2023-03-29 17:02:20,291 epoch 33 - iter 196/493 - loss 0.01741224 - time (sec): 16.78 - samples/sec: 6144.58 - lr: 0.100000 +2023-03-29 17:02:23,634 epoch 33 - iter 245/493 - loss 0.01742488 - time (sec): 20.12 - samples/sec: 6395.04 - lr: 0.100000 +2023-03-29 17:02:27,006 epoch 33 - iter 294/493 - loss 0.01779106 - time (sec): 23.49 - samples/sec: 6591.64 - lr: 0.100000 +2023-03-29 17:02:30,475 epoch 33 - iter 343/493 - loss 0.01811343 - time (sec): 26.96 - samples/sec: 6699.48 - lr: 0.100000 +2023-03-29 17:02:33,920 epoch 33 - iter 392/493 - loss 0.01867143 - time (sec): 30.41 - samples/sec: 6782.42 - lr: 0.100000 +2023-03-29 17:02:37,339 epoch 33 - iter 441/493 - loss 0.01895394 - time (sec): 33.82 - samples/sec: 6867.85 - lr: 0.100000 +2023-03-29 17:02:40,718 epoch 33 - iter 490/493 - loss 0.01911883 - time (sec): 37.20 - samples/sec: 6924.32 - lr: 0.100000 +2023-03-29 17:02:40,918 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:02:40,918 EPOCH 33 done: loss 0.0191 - lr 0.100000 +2023-03-29 17:02:40,918 BAD EPOCHS (no improvement): 0 +2023-03-29 17:02:40,922 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:02:44,318 epoch 34 - iter 49/493 - loss 0.01734115 - time (sec): 3.40 - samples/sec: 7628.31 - lr: 0.100000 +2023-03-29 17:02:47,604 epoch 34 - iter 98/493 - loss 0.01733570 - time (sec): 6.68 - samples/sec: 7677.96 - lr: 0.100000 +2023-03-29 17:02:51,019 epoch 34 - iter 147/493 - loss 0.01795239 - time (sec): 10.10 - samples/sec: 7644.00 - lr: 0.100000 +2023-03-29 17:02:54,361 epoch 34 - iter 196/493 - loss 0.01844653 - time (sec): 13.44 - samples/sec: 7649.58 - lr: 0.100000 +2023-03-29 17:02:57,812 epoch 34 - iter 245/493 - loss 0.01867821 - time (sec): 16.89 - samples/sec: 7619.66 - lr: 0.100000 +2023-03-29 17:03:01,199 epoch 34 - iter 294/493 - loss 0.01873024 - time (sec): 20.28 - samples/sec: 7593.65 - lr: 0.100000 +2023-03-29 17:03:04,606 epoch 34 - iter 343/493 - loss 0.01869788 - time (sec): 23.68 - samples/sec: 7592.07 - lr: 0.100000 +2023-03-29 17:03:07,923 epoch 34 - iter 392/493 - loss 0.01864921 - time (sec): 27.00 - samples/sec: 7600.98 - lr: 0.100000 +2023-03-29 17:03:11,464 epoch 34 - iter 441/493 - loss 0.01868923 - time (sec): 30.54 - samples/sec: 7581.79 - lr: 0.100000 +2023-03-29 17:03:14,963 epoch 34 - iter 490/493 - loss 0.01919747 - time (sec): 34.04 - samples/sec: 7561.04 - lr: 0.100000 +2023-03-29 17:03:15,264 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:03:15,264 EPOCH 34 done: loss 0.0192 - lr 0.100000 +2023-03-29 17:03:15,264 BAD EPOCHS (no improvement): 1 +2023-03-29 17:03:15,270 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:03:18,716 epoch 35 - iter 49/493 - loss 0.01656590 - time (sec): 3.45 - samples/sec: 7486.19 - lr: 0.100000 +2023-03-29 17:03:22,275 epoch 35 - iter 98/493 - loss 0.01727986 - time (sec): 7.00 - samples/sec: 7454.43 - lr: 0.100000 +2023-03-29 17:03:25,834 epoch 35 - iter 147/493 - loss 0.01749116 - time (sec): 10.56 - samples/sec: 7386.99 - lr: 0.100000 +2023-03-29 17:03:29,340 epoch 35 - iter 196/493 - loss 0.01760123 - time (sec): 14.07 - samples/sec: 7359.82 - lr: 0.100000 +2023-03-29 17:03:32,947 epoch 35 - iter 245/493 - loss 0.01797448 - time (sec): 17.68 - samples/sec: 7344.10 - lr: 0.100000 +2023-03-29 17:03:36,459 epoch 35 - iter 294/493 - loss 0.01793659 - time (sec): 21.19 - samples/sec: 7320.86 - lr: 0.100000 +2023-03-29 17:03:39,860 epoch 35 - iter 343/493 - loss 0.01818851 - time (sec): 24.59 - samples/sec: 7360.13 - lr: 0.100000 +2023-03-29 17:03:43,242 epoch 35 - iter 392/493 - loss 0.01832636 - time (sec): 27.97 - samples/sec: 7378.54 - lr: 0.100000 +2023-03-29 17:03:46,775 epoch 35 - iter 441/493 - loss 0.01858242 - time (sec): 31.50 - samples/sec: 7361.57 - lr: 0.100000 +2023-03-29 17:03:50,179 epoch 35 - iter 490/493 - loss 0.01874364 - time (sec): 34.91 - samples/sec: 7379.04 - lr: 0.100000 +2023-03-29 17:03:50,390 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:03:50,391 EPOCH 35 done: loss 0.0187 - lr 0.100000 +2023-03-29 17:03:50,391 BAD EPOCHS (no improvement): 0 +2023-03-29 17:03:50,394 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:03:53,778 epoch 36 - iter 49/493 - loss 0.01421262 - time (sec): 3.38 - samples/sec: 7337.27 - lr: 0.100000 +2023-03-29 17:03:57,124 epoch 36 - iter 98/493 - loss 0.01543496 - time (sec): 6.73 - samples/sec: 7490.82 - lr: 0.100000 +2023-03-29 17:04:00,583 epoch 36 - iter 147/493 - loss 0.01703673 - time (sec): 10.19 - samples/sec: 7550.41 - lr: 0.100000 +2023-03-29 17:04:03,871 epoch 36 - iter 196/493 - loss 0.01655657 - time (sec): 13.48 - samples/sec: 7605.83 - lr: 0.100000 +2023-03-29 17:04:07,355 epoch 36 - iter 245/493 - loss 0.01745942 - time (sec): 16.96 - samples/sec: 7583.79 - lr: 0.100000 +2023-03-29 17:04:10,887 epoch 36 - iter 294/493 - loss 0.01805801 - time (sec): 20.49 - samples/sec: 7520.81 - lr: 0.100000 +2023-03-29 17:04:14,384 epoch 36 - iter 343/493 - loss 0.01826545 - time (sec): 23.99 - samples/sec: 7496.38 - lr: 0.100000 +2023-03-29 17:04:17,886 epoch 36 - iter 392/493 - loss 0.01839494 - time (sec): 27.49 - samples/sec: 7507.28 - lr: 0.100000 +2023-03-29 17:04:21,345 epoch 36 - iter 441/493 - loss 0.01843839 - time (sec): 30.95 - samples/sec: 7494.31 - lr: 0.100000 +2023-03-29 17:04:24,801 epoch 36 - iter 490/493 - loss 0.01846872 - time (sec): 34.41 - samples/sec: 7485.02 - lr: 0.100000 +2023-03-29 17:04:25,017 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:04:25,017 EPOCH 36 done: loss 0.0184 - lr 0.100000 +2023-03-29 17:04:25,017 BAD EPOCHS (no improvement): 0 +2023-03-29 17:04:25,020 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:04:28,416 epoch 37 - iter 49/493 - loss 0.01785955 - time (sec): 3.40 - samples/sec: 7514.73 - lr: 0.100000 +2023-03-29 17:04:31,669 epoch 37 - iter 98/493 - loss 0.01847271 - time (sec): 6.65 - samples/sec: 7584.10 - lr: 0.100000 +2023-03-29 17:04:35,108 epoch 37 - iter 147/493 - loss 0.01884187 - time (sec): 10.09 - samples/sec: 7578.35 - lr: 0.100000 +2023-03-29 17:04:38,489 epoch 37 - iter 196/493 - loss 0.01874920 - time (sec): 13.47 - samples/sec: 7620.98 - lr: 0.100000 +2023-03-29 17:04:41,905 epoch 37 - iter 245/493 - loss 0.01854140 - time (sec): 16.89 - samples/sec: 7595.70 - lr: 0.100000 +2023-03-29 17:04:45,388 epoch 37 - iter 294/493 - loss 0.01816475 - time (sec): 20.37 - samples/sec: 7557.46 - lr: 0.100000 +2023-03-29 17:04:48,833 epoch 37 - iter 343/493 - loss 0.01818780 - time (sec): 23.81 - samples/sec: 7554.96 - lr: 0.100000 +2023-03-29 17:04:52,327 epoch 37 - iter 392/493 - loss 0.01838789 - time (sec): 27.31 - samples/sec: 7556.49 - lr: 0.100000 +2023-03-29 17:04:55,765 epoch 37 - iter 441/493 - loss 0.01844340 - time (sec): 30.75 - samples/sec: 7537.68 - lr: 0.100000 +2023-03-29 17:04:59,311 epoch 37 - iter 490/493 - loss 0.01886309 - time (sec): 34.29 - samples/sec: 7513.43 - lr: 0.100000 +2023-03-29 17:04:59,553 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:04:59,554 EPOCH 37 done: loss 0.0189 - lr 0.100000 +2023-03-29 17:04:59,554 BAD EPOCHS (no improvement): 1 +2023-03-29 17:04:59,557 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:05:02,868 epoch 38 - iter 49/493 - loss 0.01747937 - time (sec): 3.31 - samples/sec: 7738.36 - lr: 0.100000 +2023-03-29 17:05:06,183 epoch 38 - iter 98/493 - loss 0.01749155 - time (sec): 6.63 - samples/sec: 7712.70 - lr: 0.100000 +2023-03-29 17:05:09,842 epoch 38 - iter 147/493 - loss 0.01740220 - time (sec): 10.28 - samples/sec: 7520.64 - lr: 0.100000 +2023-03-29 17:05:13,358 epoch 38 - iter 196/493 - loss 0.01688770 - time (sec): 13.80 - samples/sec: 7454.68 - lr: 0.100000 +2023-03-29 17:05:16,863 epoch 38 - iter 245/493 - loss 0.01737584 - time (sec): 17.31 - samples/sec: 7448.11 - lr: 0.100000 +2023-03-29 17:05:20,231 epoch 38 - iter 294/493 - loss 0.01739911 - time (sec): 20.67 - samples/sec: 7464.11 - lr: 0.100000 +2023-03-29 17:05:23,501 epoch 38 - iter 343/493 - loss 0.01745142 - time (sec): 23.94 - samples/sec: 7507.98 - lr: 0.100000 +2023-03-29 17:05:26,947 epoch 38 - iter 392/493 - loss 0.01756866 - time (sec): 27.39 - samples/sec: 7505.09 - lr: 0.100000 +2023-03-29 17:05:30,360 epoch 38 - iter 441/493 - loss 0.01756450 - time (sec): 30.80 - samples/sec: 7513.29 - lr: 0.100000 +2023-03-29 17:05:33,771 epoch 38 - iter 490/493 - loss 0.01759899 - time (sec): 34.21 - samples/sec: 7525.44 - lr: 0.100000 +2023-03-29 17:05:33,983 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:05:33,983 EPOCH 38 done: loss 0.0177 - lr 0.100000 +2023-03-29 17:05:33,983 BAD EPOCHS (no improvement): 0 +2023-03-29 17:05:33,987 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:05:37,312 epoch 39 - iter 49/493 - loss 0.01780322 - time (sec): 3.33 - samples/sec: 7463.39 - lr: 0.100000 +2023-03-29 17:05:40,838 epoch 39 - iter 98/493 - loss 0.01709588 - time (sec): 6.85 - samples/sec: 7441.15 - lr: 0.100000 +2023-03-29 17:05:44,367 epoch 39 - iter 147/493 - loss 0.01675546 - time (sec): 10.38 - samples/sec: 7382.39 - lr: 0.100000 +2023-03-29 17:05:47,830 epoch 39 - iter 196/493 - loss 0.01693559 - time (sec): 13.84 - samples/sec: 7394.50 - lr: 0.100000 +2023-03-29 17:05:51,460 epoch 39 - iter 245/493 - loss 0.01699721 - time (sec): 17.47 - samples/sec: 7365.81 - lr: 0.100000 +2023-03-29 17:05:55,143 epoch 39 - iter 294/493 - loss 0.01717201 - time (sec): 21.16 - samples/sec: 7297.92 - lr: 0.100000 +2023-03-29 17:05:58,676 epoch 39 - iter 343/493 - loss 0.01759266 - time (sec): 24.69 - samples/sec: 7317.66 - lr: 0.100000 +2023-03-29 17:06:02,247 epoch 39 - iter 392/493 - loss 0.01771966 - time (sec): 28.26 - samples/sec: 7306.37 - lr: 0.100000 +2023-03-29 17:06:05,776 epoch 39 - iter 441/493 - loss 0.01791377 - time (sec): 31.79 - samples/sec: 7293.79 - lr: 0.100000 +2023-03-29 17:06:09,131 epoch 39 - iter 490/493 - loss 0.01813105 - time (sec): 35.14 - samples/sec: 7328.41 - lr: 0.100000 +2023-03-29 17:06:09,334 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:06:09,334 EPOCH 39 done: loss 0.0181 - lr 0.100000 +2023-03-29 17:06:09,334 BAD EPOCHS (no improvement): 1 +2023-03-29 17:06:09,337 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:06:12,756 epoch 40 - iter 49/493 - loss 0.01830086 - time (sec): 3.42 - samples/sec: 7577.95 - lr: 0.100000 +2023-03-29 17:06:16,173 epoch 40 - iter 98/493 - loss 0.01851355 - time (sec): 6.84 - samples/sec: 7594.57 - lr: 0.100000 +2023-03-29 17:06:19,703 epoch 40 - iter 147/493 - loss 0.01696150 - time (sec): 10.37 - samples/sec: 7516.09 - lr: 0.100000 +2023-03-29 17:06:23,146 epoch 40 - iter 196/493 - loss 0.01668594 - time (sec): 13.81 - samples/sec: 7495.96 - lr: 0.100000 +2023-03-29 17:06:26,689 epoch 40 - iter 245/493 - loss 0.01686581 - time (sec): 17.35 - samples/sec: 7460.42 - lr: 0.100000 +2023-03-29 17:06:30,079 epoch 40 - iter 294/493 - loss 0.01684896 - time (sec): 20.74 - samples/sec: 7472.84 - lr: 0.100000 +2023-03-29 17:06:33,464 epoch 40 - iter 343/493 - loss 0.01693061 - time (sec): 24.13 - samples/sec: 7507.11 - lr: 0.100000 +2023-03-29 17:06:36,930 epoch 40 - iter 392/493 - loss 0.01716048 - time (sec): 27.59 - samples/sec: 7485.28 - lr: 0.100000 +2023-03-29 17:06:40,272 epoch 40 - iter 441/493 - loss 0.01701427 - time (sec): 30.93 - samples/sec: 7497.06 - lr: 0.100000 +2023-03-29 17:06:43,733 epoch 40 - iter 490/493 - loss 0.01710322 - time (sec): 34.40 - samples/sec: 7487.30 - lr: 0.100000 +2023-03-29 17:06:43,938 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:06:43,938 EPOCH 40 done: loss 0.0171 - lr 0.100000 +2023-03-29 17:06:43,939 BAD EPOCHS (no improvement): 0 +2023-03-29 17:06:43,942 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:06:47,471 epoch 41 - iter 49/493 - loss 0.01867754 - time (sec): 3.53 - samples/sec: 7351.89 - lr: 0.100000 +2023-03-29 17:06:50,983 epoch 41 - iter 98/493 - loss 0.01669905 - time (sec): 7.04 - samples/sec: 7336.00 - lr: 0.100000 +2023-03-29 17:06:54,471 epoch 41 - iter 147/493 - loss 0.01580668 - time (sec): 10.53 - samples/sec: 7373.61 - lr: 0.100000 +2023-03-29 17:06:57,875 epoch 41 - iter 196/493 - loss 0.01592062 - time (sec): 13.93 - samples/sec: 7379.45 - lr: 0.100000 +2023-03-29 17:07:01,457 epoch 41 - iter 245/493 - loss 0.01631036 - time (sec): 17.52 - samples/sec: 7304.83 - lr: 0.100000 +2023-03-29 17:07:04,856 epoch 41 - iter 294/493 - loss 0.01668790 - time (sec): 20.91 - samples/sec: 7339.41 - lr: 0.100000 +2023-03-29 17:07:08,292 epoch 41 - iter 343/493 - loss 0.01710882 - time (sec): 24.35 - samples/sec: 7358.00 - lr: 0.100000 +2023-03-29 17:07:11,829 epoch 41 - iter 392/493 - loss 0.01717882 - time (sec): 27.89 - samples/sec: 7372.24 - lr: 0.100000 +2023-03-29 17:07:15,357 epoch 41 - iter 441/493 - loss 0.01727225 - time (sec): 31.42 - samples/sec: 7372.63 - lr: 0.100000 +2023-03-29 17:07:18,925 epoch 41 - iter 490/493 - loss 0.01738310 - time (sec): 34.98 - samples/sec: 7363.71 - lr: 0.100000 +2023-03-29 17:07:19,116 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:07:19,116 EPOCH 41 done: loss 0.0173 - lr 0.100000 +2023-03-29 17:07:19,116 BAD EPOCHS (no improvement): 1 +2023-03-29 17:07:19,119 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:07:22,608 epoch 42 - iter 49/493 - loss 0.01486363 - time (sec): 3.49 - samples/sec: 7269.55 - lr: 0.100000 +2023-03-29 17:07:26,037 epoch 42 - iter 98/493 - loss 0.01657675 - time (sec): 6.92 - samples/sec: 7393.63 - lr: 0.100000 +2023-03-29 17:07:29,447 epoch 42 - iter 147/493 - loss 0.01674186 - time (sec): 10.33 - samples/sec: 7430.30 - lr: 0.100000 +2023-03-29 17:07:33,045 epoch 42 - iter 196/493 - loss 0.01680212 - time (sec): 13.93 - samples/sec: 7382.38 - lr: 0.100000 +2023-03-29 17:07:36,624 epoch 42 - iter 245/493 - loss 0.01735195 - time (sec): 17.50 - samples/sec: 7356.70 - lr: 0.100000 +2023-03-29 17:07:40,050 epoch 42 - iter 294/493 - loss 0.01740284 - time (sec): 20.93 - samples/sec: 7373.11 - lr: 0.100000 +2023-03-29 17:07:43,719 epoch 42 - iter 343/493 - loss 0.01731150 - time (sec): 24.60 - samples/sec: 7324.29 - lr: 0.100000 +2023-03-29 17:07:47,176 epoch 42 - iter 392/493 - loss 0.01747284 - time (sec): 28.06 - samples/sec: 7329.64 - lr: 0.100000 +2023-03-29 17:07:50,692 epoch 42 - iter 441/493 - loss 0.01732007 - time (sec): 31.57 - samples/sec: 7334.41 - lr: 0.100000 +2023-03-29 17:07:54,356 epoch 42 - iter 490/493 - loss 0.01756081 - time (sec): 35.24 - samples/sec: 7309.94 - lr: 0.100000 +2023-03-29 17:07:54,561 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:07:54,561 EPOCH 42 done: loss 0.0176 - lr 0.100000 +2023-03-29 17:07:54,561 BAD EPOCHS (no improvement): 2 +2023-03-29 17:07:54,564 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:07:58,156 epoch 43 - iter 49/493 - loss 0.01346854 - time (sec): 3.59 - samples/sec: 7275.30 - lr: 0.100000 +2023-03-29 17:08:01,672 epoch 43 - iter 98/493 - loss 0.01535669 - time (sec): 7.11 - samples/sec: 7289.49 - lr: 0.100000 +2023-03-29 17:08:05,178 epoch 43 - iter 147/493 - loss 0.01530354 - time (sec): 10.61 - samples/sec: 7363.62 - lr: 0.100000 +2023-03-29 17:08:08,657 epoch 43 - iter 196/493 - loss 0.01612927 - time (sec): 14.09 - samples/sec: 7368.90 - lr: 0.100000 +2023-03-29 17:08:11,998 epoch 43 - iter 245/493 - loss 0.01648459 - time (sec): 17.43 - samples/sec: 7376.62 - lr: 0.100000 +2023-03-29 17:08:15,661 epoch 43 - iter 294/493 - loss 0.01620351 - time (sec): 21.10 - samples/sec: 7318.49 - lr: 0.100000 +2023-03-29 17:08:19,132 epoch 43 - iter 343/493 - loss 0.01615823 - time (sec): 24.57 - samples/sec: 7329.19 - lr: 0.100000 +2023-03-29 17:08:22,617 epoch 43 - iter 392/493 - loss 0.01646610 - time (sec): 28.05 - samples/sec: 7334.92 - lr: 0.100000 +2023-03-29 17:08:26,271 epoch 43 - iter 441/493 - loss 0.01659449 - time (sec): 31.71 - samples/sec: 7312.24 - lr: 0.100000 +2023-03-29 17:08:29,889 epoch 43 - iter 490/493 - loss 0.01682178 - time (sec): 35.33 - samples/sec: 7291.49 - lr: 0.100000 +2023-03-29 17:08:30,120 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:08:30,120 EPOCH 43 done: loss 0.0168 - lr 0.100000 +2023-03-29 17:08:30,120 BAD EPOCHS (no improvement): 0 +2023-03-29 17:08:30,133 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:08:33,653 epoch 44 - iter 49/493 - loss 0.01396551 - time (sec): 3.52 - samples/sec: 7254.02 - lr: 0.100000 +2023-03-29 17:08:36,928 epoch 44 - iter 98/493 - loss 0.01531589 - time (sec): 6.80 - samples/sec: 7522.60 - lr: 0.100000 +2023-03-29 17:08:40,572 epoch 44 - iter 147/493 - loss 0.01637416 - time (sec): 10.44 - samples/sec: 7451.59 - lr: 0.100000 +2023-03-29 17:08:44,243 epoch 44 - iter 196/493 - loss 0.01580264 - time (sec): 14.11 - samples/sec: 7352.49 - lr: 0.100000 +2023-03-29 17:08:47,695 epoch 44 - iter 245/493 - loss 0.01585910 - time (sec): 17.56 - samples/sec: 7297.39 - lr: 0.100000 +2023-03-29 17:08:51,180 epoch 44 - iter 294/493 - loss 0.01616521 - time (sec): 21.05 - samples/sec: 7321.38 - lr: 0.100000 +2023-03-29 17:08:54,659 epoch 44 - iter 343/493 - loss 0.01602245 - time (sec): 24.53 - samples/sec: 7327.82 - lr: 0.100000 +2023-03-29 17:08:58,053 epoch 44 - iter 392/493 - loss 0.01592255 - time (sec): 27.92 - samples/sec: 7354.05 - lr: 0.100000 +2023-03-29 17:09:01,516 epoch 44 - iter 441/493 - loss 0.01603362 - time (sec): 31.38 - samples/sec: 7362.04 - lr: 0.100000 +2023-03-29 17:09:05,240 epoch 44 - iter 490/493 - loss 0.01606192 - time (sec): 35.11 - samples/sec: 7339.68 - lr: 0.100000 +2023-03-29 17:09:05,434 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:09:05,434 EPOCH 44 done: loss 0.0160 - lr 0.100000 +2023-03-29 17:09:05,434 BAD EPOCHS (no improvement): 0 +2023-03-29 17:09:05,437 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:09:09,094 epoch 45 - iter 49/493 - loss 0.01512284 - time (sec): 3.66 - samples/sec: 7270.94 - lr: 0.100000 +2023-03-29 17:09:12,591 epoch 45 - iter 98/493 - loss 0.01586746 - time (sec): 7.15 - samples/sec: 7257.78 - lr: 0.100000 +2023-03-29 17:09:16,026 epoch 45 - iter 147/493 - loss 0.01544188 - time (sec): 10.59 - samples/sec: 7282.31 - lr: 0.100000 +2023-03-29 17:09:19,453 epoch 45 - iter 196/493 - loss 0.01610986 - time (sec): 14.02 - samples/sec: 7331.93 - lr: 0.100000 +2023-03-29 17:09:23,038 epoch 45 - iter 245/493 - loss 0.01588432 - time (sec): 17.60 - samples/sec: 7323.57 - lr: 0.100000 +2023-03-29 17:09:26,600 epoch 45 - iter 294/493 - loss 0.01610278 - time (sec): 21.16 - samples/sec: 7308.80 - lr: 0.100000 +2023-03-29 17:09:29,868 epoch 45 - iter 343/493 - loss 0.01617301 - time (sec): 24.43 - samples/sec: 7362.46 - lr: 0.100000 +2023-03-29 17:09:33,379 epoch 45 - iter 392/493 - loss 0.01632700 - time (sec): 27.94 - samples/sec: 7351.71 - lr: 0.100000 +2023-03-29 17:09:36,945 epoch 45 - iter 441/493 - loss 0.01680040 - time (sec): 31.51 - samples/sec: 7341.96 - lr: 0.100000 +2023-03-29 17:09:40,513 epoch 45 - iter 490/493 - loss 0.01696391 - time (sec): 35.08 - samples/sec: 7343.49 - lr: 0.100000 +2023-03-29 17:09:40,735 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:09:40,735 EPOCH 45 done: loss 0.0170 - lr 0.100000 +2023-03-29 17:09:40,735 BAD EPOCHS (no improvement): 1 +2023-03-29 17:09:40,738 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:09:44,300 epoch 46 - iter 49/493 - loss 0.01467726 - time (sec): 3.56 - samples/sec: 7324.75 - lr: 0.100000 +2023-03-29 17:09:47,742 epoch 46 - iter 98/493 - loss 0.01515751 - time (sec): 7.00 - samples/sec: 7388.86 - lr: 0.100000 +2023-03-29 17:09:51,347 epoch 46 - iter 147/493 - loss 0.01583287 - time (sec): 10.61 - samples/sec: 7364.21 - lr: 0.100000 +2023-03-29 17:09:54,814 epoch 46 - iter 196/493 - loss 0.01586639 - time (sec): 14.08 - samples/sec: 7380.87 - lr: 0.100000 +2023-03-29 17:09:58,222 epoch 46 - iter 245/493 - loss 0.01642692 - time (sec): 17.48 - samples/sec: 7360.54 - lr: 0.100000 +2023-03-29 17:10:01,954 epoch 46 - iter 294/493 - loss 0.01669223 - time (sec): 21.22 - samples/sec: 7323.34 - lr: 0.100000 +2023-03-29 17:10:05,450 epoch 46 - iter 343/493 - loss 0.01656987 - time (sec): 24.71 - samples/sec: 7340.76 - lr: 0.100000 +2023-03-29 17:10:08,759 epoch 46 - iter 392/493 - loss 0.01670286 - time (sec): 28.02 - samples/sec: 7372.90 - lr: 0.100000 +2023-03-29 17:10:12,155 epoch 46 - iter 441/493 - loss 0.01683924 - time (sec): 31.42 - samples/sec: 7387.09 - lr: 0.100000 +2023-03-29 17:10:15,540 epoch 46 - iter 490/493 - loss 0.01687354 - time (sec): 34.80 - samples/sec: 7403.20 - lr: 0.100000 +2023-03-29 17:10:15,755 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:10:15,755 EPOCH 46 done: loss 0.0169 - lr 0.100000 +2023-03-29 17:10:15,755 BAD EPOCHS (no improvement): 2 +2023-03-29 17:10:15,758 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:10:19,258 epoch 47 - iter 49/493 - loss 0.01523513 - time (sec): 3.50 - samples/sec: 7517.34 - lr: 0.100000 +2023-03-29 17:10:22,879 epoch 47 - iter 98/493 - loss 0.01596035 - time (sec): 7.12 - samples/sec: 7296.77 - lr: 0.100000 +2023-03-29 17:10:26,473 epoch 47 - iter 147/493 - loss 0.01680429 - time (sec): 10.71 - samples/sec: 7289.03 - lr: 0.100000 +2023-03-29 17:10:30,109 epoch 47 - iter 196/493 - loss 0.01626073 - time (sec): 14.35 - samples/sec: 7281.34 - lr: 0.100000 +2023-03-29 17:10:33,497 epoch 47 - iter 245/493 - loss 0.01580049 - time (sec): 17.74 - samples/sec: 7277.35 - lr: 0.100000 +2023-03-29 17:10:37,212 epoch 47 - iter 294/493 - loss 0.01578821 - time (sec): 21.45 - samples/sec: 7225.98 - lr: 0.100000 +2023-03-29 17:10:40,710 epoch 47 - iter 343/493 - loss 0.01535653 - time (sec): 24.95 - samples/sec: 7276.39 - lr: 0.100000 +2023-03-29 17:10:44,216 epoch 47 - iter 392/493 - loss 0.01563372 - time (sec): 28.46 - samples/sec: 7267.90 - lr: 0.100000 +2023-03-29 17:10:47,786 epoch 47 - iter 441/493 - loss 0.01555640 - time (sec): 32.03 - samples/sec: 7274.36 - lr: 0.100000 +2023-03-29 17:10:51,090 epoch 47 - iter 490/493 - loss 0.01558427 - time (sec): 35.33 - samples/sec: 7293.56 - lr: 0.100000 +2023-03-29 17:10:51,271 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:10:51,271 EPOCH 47 done: loss 0.0156 - lr 0.100000 +2023-03-29 17:10:51,271 BAD EPOCHS (no improvement): 0 +2023-03-29 17:10:51,274 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:10:54,764 epoch 48 - iter 49/493 - loss 0.01426575 - time (sec): 3.49 - samples/sec: 7580.23 - lr: 0.100000 +2023-03-29 17:10:58,224 epoch 48 - iter 98/493 - loss 0.01373443 - time (sec): 6.95 - samples/sec: 7438.39 - lr: 0.100000 +2023-03-29 17:11:01,806 epoch 48 - iter 147/493 - loss 0.01420001 - time (sec): 10.53 - samples/sec: 7385.08 - lr: 0.100000 +2023-03-29 17:11:05,274 epoch 48 - iter 196/493 - loss 0.01435123 - time (sec): 14.00 - samples/sec: 7406.07 - lr: 0.100000 +2023-03-29 17:11:08,687 epoch 48 - iter 245/493 - loss 0.01508124 - time (sec): 17.41 - samples/sec: 7434.05 - lr: 0.100000 +2023-03-29 17:11:12,079 epoch 48 - iter 294/493 - loss 0.01530754 - time (sec): 20.80 - samples/sec: 7435.97 - lr: 0.100000 +2023-03-29 17:11:15,509 epoch 48 - iter 343/493 - loss 0.01553116 - time (sec): 24.23 - samples/sec: 7429.86 - lr: 0.100000 +2023-03-29 17:11:19,133 epoch 48 - iter 392/493 - loss 0.01572504 - time (sec): 27.86 - samples/sec: 7410.02 - lr: 0.100000 +2023-03-29 17:11:22,654 epoch 48 - iter 441/493 - loss 0.01583564 - time (sec): 31.38 - samples/sec: 7414.97 - lr: 0.100000 +2023-03-29 17:11:25,941 epoch 48 - iter 490/493 - loss 0.01578621 - time (sec): 34.67 - samples/sec: 7435.91 - lr: 0.100000 +2023-03-29 17:11:26,142 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:11:26,142 EPOCH 48 done: loss 0.0158 - lr 0.100000 +2023-03-29 17:11:26,142 BAD EPOCHS (no improvement): 1 +2023-03-29 17:11:26,145 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:11:29,541 epoch 49 - iter 49/493 - loss 0.01388802 - time (sec): 3.40 - samples/sec: 7467.75 - lr: 0.100000 +2023-03-29 17:11:32,922 epoch 49 - iter 98/493 - loss 0.01400908 - time (sec): 6.78 - samples/sec: 7479.04 - lr: 0.100000 +2023-03-29 17:11:36,313 epoch 49 - iter 147/493 - loss 0.01493476 - time (sec): 10.17 - samples/sec: 7519.48 - lr: 0.100000 +2023-03-29 17:11:39,616 epoch 49 - iter 196/493 - loss 0.01474928 - time (sec): 13.47 - samples/sec: 7601.20 - lr: 0.100000 +2023-03-29 17:11:43,028 epoch 49 - iter 245/493 - loss 0.01495729 - time (sec): 16.88 - samples/sec: 7614.56 - lr: 0.100000 +2023-03-29 17:11:46,433 epoch 49 - iter 294/493 - loss 0.01496143 - time (sec): 20.29 - samples/sec: 7607.41 - lr: 0.100000 +2023-03-29 17:11:49,860 epoch 49 - iter 343/493 - loss 0.01536235 - time (sec): 23.71 - samples/sec: 7588.99 - lr: 0.100000 +2023-03-29 17:11:53,438 epoch 49 - iter 392/493 - loss 0.01543578 - time (sec): 27.29 - samples/sec: 7565.70 - lr: 0.100000 +2023-03-29 17:11:56,900 epoch 49 - iter 441/493 - loss 0.01562429 - time (sec): 30.76 - samples/sec: 7548.76 - lr: 0.100000 +2023-03-29 17:12:00,230 epoch 49 - iter 490/493 - loss 0.01585238 - time (sec): 34.08 - samples/sec: 7556.50 - lr: 0.100000 +2023-03-29 17:12:00,444 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:12:00,444 EPOCH 49 done: loss 0.0158 - lr 0.100000 +2023-03-29 17:12:00,444 BAD EPOCHS (no improvement): 2 +2023-03-29 17:12:00,447 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:12:03,836 epoch 50 - iter 49/493 - loss 0.01489813 - time (sec): 3.39 - samples/sec: 7396.68 - lr: 0.100000 +2023-03-29 17:12:07,301 epoch 50 - iter 98/493 - loss 0.01582275 - time (sec): 6.85 - samples/sec: 7443.36 - lr: 0.100000 +2023-03-29 17:12:10,781 epoch 50 - iter 147/493 - loss 0.01563354 - time (sec): 10.33 - samples/sec: 7401.89 - lr: 0.100000 +2023-03-29 17:12:14,268 epoch 50 - iter 196/493 - loss 0.01588996 - time (sec): 13.82 - samples/sec: 7410.19 - lr: 0.100000 +2023-03-29 17:12:17,623 epoch 50 - iter 245/493 - loss 0.01566313 - time (sec): 17.18 - samples/sec: 7454.41 - lr: 0.100000 +2023-03-29 17:12:21,151 epoch 50 - iter 294/493 - loss 0.01582972 - time (sec): 20.70 - samples/sec: 7429.94 - lr: 0.100000 +2023-03-29 17:12:24,891 epoch 50 - iter 343/493 - loss 0.01550919 - time (sec): 24.44 - samples/sec: 7368.52 - lr: 0.100000 +2023-03-29 17:12:28,362 epoch 50 - iter 392/493 - loss 0.01544892 - time (sec): 27.92 - samples/sec: 7361.22 - lr: 0.100000 +2023-03-29 17:12:31,892 epoch 50 - iter 441/493 - loss 0.01551870 - time (sec): 31.45 - samples/sec: 7362.98 - lr: 0.100000 +2023-03-29 17:12:35,314 epoch 50 - iter 490/493 - loss 0.01538672 - time (sec): 34.87 - samples/sec: 7386.56 - lr: 0.100000 +2023-03-29 17:12:35,521 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:12:35,521 EPOCH 50 done: loss 0.0154 - lr 0.100000 +2023-03-29 17:12:35,521 BAD EPOCHS (no improvement): 0 +2023-03-29 17:12:35,523 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:12:39,011 epoch 51 - iter 49/493 - loss 0.01504737 - time (sec): 3.49 - samples/sec: 7373.00 - lr: 0.100000 +2023-03-29 17:12:42,281 epoch 51 - iter 98/493 - loss 0.01582277 - time (sec): 6.76 - samples/sec: 7499.47 - lr: 0.100000 +2023-03-29 17:12:45,704 epoch 51 - iter 147/493 - loss 0.01596518 - time (sec): 10.18 - samples/sec: 7586.79 - lr: 0.100000 +2023-03-29 17:12:49,205 epoch 51 - iter 196/493 - loss 0.01640200 - time (sec): 13.68 - samples/sec: 7560.52 - lr: 0.100000 +2023-03-29 17:12:52,639 epoch 51 - iter 245/493 - loss 0.01607979 - time (sec): 17.12 - samples/sec: 7539.78 - lr: 0.100000 +2023-03-29 17:12:56,135 epoch 51 - iter 294/493 - loss 0.01603384 - time (sec): 20.61 - samples/sec: 7512.51 - lr: 0.100000 +2023-03-29 17:12:59,690 epoch 51 - iter 343/493 - loss 0.01598721 - time (sec): 24.17 - samples/sec: 7448.72 - lr: 0.100000 +2023-03-29 17:13:03,110 epoch 51 - iter 392/493 - loss 0.01597553 - time (sec): 27.59 - samples/sec: 7442.02 - lr: 0.100000 +2023-03-29 17:13:06,698 epoch 51 - iter 441/493 - loss 0.01601232 - time (sec): 31.17 - samples/sec: 7409.08 - lr: 0.100000 +2023-03-29 17:13:10,262 epoch 51 - iter 490/493 - loss 0.01592414 - time (sec): 34.74 - samples/sec: 7405.78 - lr: 0.100000 +2023-03-29 17:13:10,554 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:13:10,554 EPOCH 51 done: loss 0.0159 - lr 0.100000 +2023-03-29 17:13:10,554 BAD EPOCHS (no improvement): 1 +2023-03-29 17:13:10,557 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:13:14,226 epoch 52 - iter 49/493 - loss 0.01157104 - time (sec): 3.67 - samples/sec: 6988.30 - lr: 0.100000 +2023-03-29 17:13:17,678 epoch 52 - iter 98/493 - loss 0.01271535 - time (sec): 7.12 - samples/sec: 7219.43 - lr: 0.100000 +2023-03-29 17:13:21,176 epoch 52 - iter 147/493 - loss 0.01338717 - time (sec): 10.62 - samples/sec: 7221.57 - lr: 0.100000 +2023-03-29 17:13:24,762 epoch 52 - iter 196/493 - loss 0.01385390 - time (sec): 14.21 - samples/sec: 7250.32 - lr: 0.100000 +2023-03-29 17:13:28,346 epoch 52 - iter 245/493 - loss 0.01444630 - time (sec): 17.79 - samples/sec: 7264.74 - lr: 0.100000 +2023-03-29 17:13:31,831 epoch 52 - iter 294/493 - loss 0.01446241 - time (sec): 21.27 - samples/sec: 7279.51 - lr: 0.100000 +2023-03-29 17:13:35,424 epoch 52 - iter 343/493 - loss 0.01459279 - time (sec): 24.87 - samples/sec: 7261.43 - lr: 0.100000 +2023-03-29 17:13:39,010 epoch 52 - iter 392/493 - loss 0.01459994 - time (sec): 28.45 - samples/sec: 7265.59 - lr: 0.100000 +2023-03-29 17:13:42,349 epoch 52 - iter 441/493 - loss 0.01463644 - time (sec): 31.79 - samples/sec: 7291.75 - lr: 0.100000 +2023-03-29 17:13:45,762 epoch 52 - iter 490/493 - loss 0.01509526 - time (sec): 35.20 - samples/sec: 7315.32 - lr: 0.100000 +2023-03-29 17:13:45,963 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:13:45,963 EPOCH 52 done: loss 0.0152 - lr 0.100000 +2023-03-29 17:13:45,963 BAD EPOCHS (no improvement): 0 +2023-03-29 17:13:45,966 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:13:49,648 epoch 53 - iter 49/493 - loss 0.01232584 - time (sec): 3.68 - samples/sec: 7195.24 - lr: 0.100000 +2023-03-29 17:13:53,152 epoch 53 - iter 98/493 - loss 0.01337726 - time (sec): 7.19 - samples/sec: 7282.12 - lr: 0.100000 +2023-03-29 17:13:56,752 epoch 53 - iter 147/493 - loss 0.01417300 - time (sec): 10.79 - samples/sec: 7251.37 - lr: 0.100000 +2023-03-29 17:14:00,229 epoch 53 - iter 196/493 - loss 0.01354577 - time (sec): 14.26 - samples/sec: 7289.05 - lr: 0.100000 +2023-03-29 17:14:03,820 epoch 53 - iter 245/493 - loss 0.01402281 - time (sec): 17.85 - samples/sec: 7256.52 - lr: 0.100000 +2023-03-29 17:14:06,998 epoch 53 - iter 294/493 - loss 0.01411532 - time (sec): 21.03 - samples/sec: 7346.46 - lr: 0.100000 +2023-03-29 17:14:10,500 epoch 53 - iter 343/493 - loss 0.01441897 - time (sec): 24.53 - samples/sec: 7344.16 - lr: 0.100000 +2023-03-29 17:14:13,886 epoch 53 - iter 392/493 - loss 0.01427549 - time (sec): 27.92 - samples/sec: 7376.28 - lr: 0.100000 +2023-03-29 17:14:17,126 epoch 53 - iter 441/493 - loss 0.01451250 - time (sec): 31.16 - samples/sec: 7416.63 - lr: 0.100000 +2023-03-29 17:14:20,659 epoch 53 - iter 490/493 - loss 0.01451116 - time (sec): 34.69 - samples/sec: 7431.49 - lr: 0.100000 +2023-03-29 17:14:20,824 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:14:20,824 EPOCH 53 done: loss 0.0145 - lr 0.100000 +2023-03-29 17:14:20,824 BAD EPOCHS (no improvement): 0 +2023-03-29 17:14:20,827 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:14:27,323 epoch 54 - iter 49/493 - loss 0.01274126 - time (sec): 6.50 - samples/sec: 4015.51 - lr: 0.100000 +2023-03-29 17:14:30,717 epoch 54 - iter 98/493 - loss 0.01311452 - time (sec): 9.89 - samples/sec: 5236.80 - lr: 0.100000 +2023-03-29 17:14:34,067 epoch 54 - iter 147/493 - loss 0.01453920 - time (sec): 13.24 - samples/sec: 5799.34 - lr: 0.100000 +2023-03-29 17:14:37,465 epoch 54 - iter 196/493 - loss 0.01526810 - time (sec): 16.64 - samples/sec: 6151.35 - lr: 0.100000 +2023-03-29 17:14:40,899 epoch 54 - iter 245/493 - loss 0.01525681 - time (sec): 20.07 - samples/sec: 6379.84 - lr: 0.100000 +2023-03-29 17:14:44,293 epoch 54 - iter 294/493 - loss 0.01483662 - time (sec): 23.47 - samples/sec: 6539.74 - lr: 0.100000 +2023-03-29 17:14:47,832 epoch 54 - iter 343/493 - loss 0.01485919 - time (sec): 27.00 - samples/sec: 6649.56 - lr: 0.100000 +2023-03-29 17:14:51,277 epoch 54 - iter 392/493 - loss 0.01481153 - time (sec): 30.45 - samples/sec: 6746.23 - lr: 0.100000 +2023-03-29 17:14:54,807 epoch 54 - iter 441/493 - loss 0.01483988 - time (sec): 33.98 - samples/sec: 6800.71 - lr: 0.100000 +2023-03-29 17:14:58,587 epoch 54 - iter 490/493 - loss 0.01495454 - time (sec): 37.76 - samples/sec: 6820.78 - lr: 0.100000 +2023-03-29 17:14:58,821 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:14:58,821 EPOCH 54 done: loss 0.0149 - lr 0.100000 +2023-03-29 17:14:58,821 BAD EPOCHS (no improvement): 1 +2023-03-29 17:14:58,824 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:15:02,438 epoch 55 - iter 49/493 - loss 0.01231345 - time (sec): 3.61 - samples/sec: 7087.92 - lr: 0.100000 +2023-03-29 17:15:05,946 epoch 55 - iter 98/493 - loss 0.01333611 - time (sec): 7.12 - samples/sec: 7269.53 - lr: 0.100000 +2023-03-29 17:15:09,411 epoch 55 - iter 147/493 - loss 0.01361445 - time (sec): 10.59 - samples/sec: 7281.80 - lr: 0.100000 +2023-03-29 17:15:13,034 epoch 55 - iter 196/493 - loss 0.01408134 - time (sec): 14.21 - samples/sec: 7251.37 - lr: 0.100000 +2023-03-29 17:15:16,574 epoch 55 - iter 245/493 - loss 0.01438197 - time (sec): 17.75 - samples/sec: 7275.99 - lr: 0.100000 +2023-03-29 17:15:19,985 epoch 55 - iter 294/493 - loss 0.01430433 - time (sec): 21.16 - samples/sec: 7292.72 - lr: 0.100000 +2023-03-29 17:15:23,465 epoch 55 - iter 343/493 - loss 0.01458900 - time (sec): 24.64 - samples/sec: 7305.88 - lr: 0.100000 +2023-03-29 17:15:26,999 epoch 55 - iter 392/493 - loss 0.01457322 - time (sec): 28.17 - samples/sec: 7322.37 - lr: 0.100000 +2023-03-29 17:15:30,506 epoch 55 - iter 441/493 - loss 0.01445627 - time (sec): 31.68 - samples/sec: 7329.84 - lr: 0.100000 +2023-03-29 17:15:33,976 epoch 55 - iter 490/493 - loss 0.01437347 - time (sec): 35.15 - samples/sec: 7327.24 - lr: 0.100000 +2023-03-29 17:15:34,193 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:15:34,193 EPOCH 55 done: loss 0.0144 - lr 0.100000 +2023-03-29 17:15:34,193 BAD EPOCHS (no improvement): 0 +2023-03-29 17:15:34,196 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:15:37,666 epoch 56 - iter 49/493 - loss 0.01333028 - time (sec): 3.47 - samples/sec: 7393.28 - lr: 0.100000 +2023-03-29 17:15:41,119 epoch 56 - iter 98/493 - loss 0.01410583 - time (sec): 6.92 - samples/sec: 7476.29 - lr: 0.100000 +2023-03-29 17:15:44,611 epoch 56 - iter 147/493 - loss 0.01424667 - time (sec): 10.42 - samples/sec: 7406.96 - lr: 0.100000 +2023-03-29 17:15:48,118 epoch 56 - iter 196/493 - loss 0.01495167 - time (sec): 13.92 - samples/sec: 7390.75 - lr: 0.100000 +2023-03-29 17:15:51,762 epoch 56 - iter 245/493 - loss 0.01479072 - time (sec): 17.57 - samples/sec: 7335.50 - lr: 0.100000 +2023-03-29 17:15:55,183 epoch 56 - iter 294/493 - loss 0.01461522 - time (sec): 20.99 - samples/sec: 7398.52 - lr: 0.100000 +2023-03-29 17:15:58,585 epoch 56 - iter 343/493 - loss 0.01469628 - time (sec): 24.39 - samples/sec: 7408.50 - lr: 0.100000 +2023-03-29 17:16:02,229 epoch 56 - iter 392/493 - loss 0.01453457 - time (sec): 28.03 - samples/sec: 7376.82 - lr: 0.100000 +2023-03-29 17:16:06,163 epoch 56 - iter 441/493 - loss 0.01462831 - time (sec): 31.97 - samples/sec: 7263.25 - lr: 0.100000 +2023-03-29 17:16:09,549 epoch 56 - iter 490/493 - loss 0.01470445 - time (sec): 35.35 - samples/sec: 7289.39 - lr: 0.100000 +2023-03-29 17:16:09,727 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:16:09,727 EPOCH 56 done: loss 0.0147 - lr 0.100000 +2023-03-29 17:16:09,727 BAD EPOCHS (no improvement): 1 +2023-03-29 17:16:09,730 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:16:13,364 epoch 57 - iter 49/493 - loss 0.01370354 - time (sec): 3.63 - samples/sec: 7164.86 - lr: 0.100000 +2023-03-29 17:16:16,936 epoch 57 - iter 98/493 - loss 0.01383830 - time (sec): 7.21 - samples/sec: 7214.32 - lr: 0.100000 +2023-03-29 17:16:20,294 epoch 57 - iter 147/493 - loss 0.01434544 - time (sec): 10.56 - samples/sec: 7302.54 - lr: 0.100000 +2023-03-29 17:16:23,716 epoch 57 - iter 196/493 - loss 0.01454230 - time (sec): 13.99 - samples/sec: 7332.73 - lr: 0.100000 +2023-03-29 17:16:27,303 epoch 57 - iter 245/493 - loss 0.01405052 - time (sec): 17.57 - samples/sec: 7345.16 - lr: 0.100000 +2023-03-29 17:16:30,711 epoch 57 - iter 294/493 - loss 0.01393116 - time (sec): 20.98 - samples/sec: 7356.20 - lr: 0.100000 +2023-03-29 17:16:34,257 epoch 57 - iter 343/493 - loss 0.01394941 - time (sec): 24.53 - samples/sec: 7356.79 - lr: 0.100000 +2023-03-29 17:16:37,870 epoch 57 - iter 392/493 - loss 0.01406392 - time (sec): 28.14 - samples/sec: 7334.48 - lr: 0.100000 +2023-03-29 17:16:41,258 epoch 57 - iter 441/493 - loss 0.01416258 - time (sec): 31.53 - samples/sec: 7371.77 - lr: 0.100000 +2023-03-29 17:16:44,707 epoch 57 - iter 490/493 - loss 0.01414036 - time (sec): 34.98 - samples/sec: 7361.88 - lr: 0.100000 +2023-03-29 17:16:44,920 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:16:44,920 EPOCH 57 done: loss 0.0142 - lr 0.100000 +2023-03-29 17:16:44,920 BAD EPOCHS (no improvement): 0 +2023-03-29 17:16:44,923 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:16:48,418 epoch 58 - iter 49/493 - loss 0.01618956 - time (sec): 3.49 - samples/sec: 7414.98 - lr: 0.100000 +2023-03-29 17:16:51,868 epoch 58 - iter 98/493 - loss 0.01550140 - time (sec): 6.95 - samples/sec: 7481.45 - lr: 0.100000 +2023-03-29 17:16:55,468 epoch 58 - iter 147/493 - loss 0.01440295 - time (sec): 10.54 - samples/sec: 7367.02 - lr: 0.100000 +2023-03-29 17:16:59,051 epoch 58 - iter 196/493 - loss 0.01425204 - time (sec): 14.13 - samples/sec: 7320.16 - lr: 0.100000 +2023-03-29 17:17:02,536 epoch 58 - iter 245/493 - loss 0.01408594 - time (sec): 17.61 - samples/sec: 7323.14 - lr: 0.100000 +2023-03-29 17:17:06,191 epoch 58 - iter 294/493 - loss 0.01431825 - time (sec): 21.27 - samples/sec: 7327.83 - lr: 0.100000 +2023-03-29 17:17:09,617 epoch 58 - iter 343/493 - loss 0.01430148 - time (sec): 24.69 - samples/sec: 7326.86 - lr: 0.100000 +2023-03-29 17:17:13,254 epoch 58 - iter 392/493 - loss 0.01406795 - time (sec): 28.33 - samples/sec: 7302.85 - lr: 0.100000 +2023-03-29 17:17:16,695 epoch 58 - iter 441/493 - loss 0.01417236 - time (sec): 31.77 - samples/sec: 7306.84 - lr: 0.100000 +2023-03-29 17:17:20,145 epoch 58 - iter 490/493 - loss 0.01412735 - time (sec): 35.22 - samples/sec: 7312.81 - lr: 0.100000 +2023-03-29 17:17:20,378 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:17:20,378 EPOCH 58 done: loss 0.0141 - lr 0.100000 +2023-03-29 17:17:20,378 BAD EPOCHS (no improvement): 0 +2023-03-29 17:17:20,386 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:17:23,875 epoch 59 - iter 49/493 - loss 0.01377288 - time (sec): 3.49 - samples/sec: 7211.38 - lr: 0.100000 +2023-03-29 17:17:27,275 epoch 59 - iter 98/493 - loss 0.01330625 - time (sec): 6.89 - samples/sec: 7309.50 - lr: 0.100000 +2023-03-29 17:17:30,852 epoch 59 - iter 147/493 - loss 0.01386733 - time (sec): 10.47 - samples/sec: 7292.69 - lr: 0.100000 +2023-03-29 17:17:34,329 epoch 59 - iter 196/493 - loss 0.01408587 - time (sec): 13.94 - samples/sec: 7314.80 - lr: 0.100000 +2023-03-29 17:17:37,987 epoch 59 - iter 245/493 - loss 0.01466598 - time (sec): 17.60 - samples/sec: 7230.92 - lr: 0.100000 +2023-03-29 17:17:41,534 epoch 59 - iter 294/493 - loss 0.01429410 - time (sec): 21.15 - samples/sec: 7269.33 - lr: 0.100000 +2023-03-29 17:17:45,015 epoch 59 - iter 343/493 - loss 0.01454364 - time (sec): 24.63 - samples/sec: 7269.88 - lr: 0.100000 +2023-03-29 17:17:48,608 epoch 59 - iter 392/493 - loss 0.01475087 - time (sec): 28.22 - samples/sec: 7257.90 - lr: 0.100000 +2023-03-29 17:17:52,234 epoch 59 - iter 441/493 - loss 0.01465414 - time (sec): 31.85 - samples/sec: 7250.19 - lr: 0.100000 +2023-03-29 17:17:55,885 epoch 59 - iter 490/493 - loss 0.01470073 - time (sec): 35.50 - samples/sec: 7254.77 - lr: 0.100000 +2023-03-29 17:17:56,134 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:17:56,134 EPOCH 59 done: loss 0.0147 - lr 0.100000 +2023-03-29 17:17:56,134 BAD EPOCHS (no improvement): 1 +2023-03-29 17:17:56,146 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:17:59,581 epoch 60 - iter 49/493 - loss 0.01503901 - time (sec): 3.43 - samples/sec: 7267.53 - lr: 0.100000 +2023-03-29 17:18:03,303 epoch 60 - iter 98/493 - loss 0.01396733 - time (sec): 7.16 - samples/sec: 7179.73 - lr: 0.100000 +2023-03-29 17:18:06,892 epoch 60 - iter 147/493 - loss 0.01415840 - time (sec): 10.75 - samples/sec: 7208.88 - lr: 0.100000 +2023-03-29 17:18:10,267 epoch 60 - iter 196/493 - loss 0.01490000 - time (sec): 14.12 - samples/sec: 7306.92 - lr: 0.100000 +2023-03-29 17:18:13,712 epoch 60 - iter 245/493 - loss 0.01452413 - time (sec): 17.57 - samples/sec: 7330.84 - lr: 0.100000 +2023-03-29 17:18:17,154 epoch 60 - iter 294/493 - loss 0.01425252 - time (sec): 21.01 - samples/sec: 7338.44 - lr: 0.100000 +2023-03-29 17:18:20,640 epoch 60 - iter 343/493 - loss 0.01439855 - time (sec): 24.49 - samples/sec: 7344.73 - lr: 0.100000 +2023-03-29 17:18:24,186 epoch 60 - iter 392/493 - loss 0.01426844 - time (sec): 28.04 - samples/sec: 7333.47 - lr: 0.100000 +2023-03-29 17:18:27,755 epoch 60 - iter 441/493 - loss 0.01395254 - time (sec): 31.61 - samples/sec: 7343.02 - lr: 0.100000 +2023-03-29 17:18:31,321 epoch 60 - iter 490/493 - loss 0.01391507 - time (sec): 35.17 - samples/sec: 7324.65 - lr: 0.100000 +2023-03-29 17:18:31,543 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:18:31,543 EPOCH 60 done: loss 0.0140 - lr 0.100000 +2023-03-29 17:18:31,543 BAD EPOCHS (no improvement): 0 +2023-03-29 17:18:31,546 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:18:35,171 epoch 61 - iter 49/493 - loss 0.01249832 - time (sec): 3.62 - samples/sec: 7222.68 - lr: 0.100000 +2023-03-29 17:18:38,757 epoch 61 - iter 98/493 - loss 0.01301925 - time (sec): 7.21 - samples/sec: 7147.14 - lr: 0.100000 +2023-03-29 17:18:42,191 epoch 61 - iter 147/493 - loss 0.01335370 - time (sec): 10.64 - samples/sec: 7191.03 - lr: 0.100000 +2023-03-29 17:18:45,757 epoch 61 - iter 196/493 - loss 0.01356842 - time (sec): 14.21 - samples/sec: 7216.53 - lr: 0.100000 +2023-03-29 17:18:49,281 epoch 61 - iter 245/493 - loss 0.01353358 - time (sec): 17.73 - samples/sec: 7232.75 - lr: 0.100000 +2023-03-29 17:18:52,895 epoch 61 - iter 294/493 - loss 0.01350559 - time (sec): 21.35 - samples/sec: 7206.19 - lr: 0.100000 +2023-03-29 17:18:56,356 epoch 61 - iter 343/493 - loss 0.01330506 - time (sec): 24.81 - samples/sec: 7231.95 - lr: 0.100000 +2023-03-29 17:18:59,875 epoch 61 - iter 392/493 - loss 0.01356860 - time (sec): 28.33 - samples/sec: 7265.07 - lr: 0.100000 +2023-03-29 17:19:03,344 epoch 61 - iter 441/493 - loss 0.01393315 - time (sec): 31.80 - samples/sec: 7278.70 - lr: 0.100000 +2023-03-29 17:19:06,737 epoch 61 - iter 490/493 - loss 0.01404745 - time (sec): 35.19 - samples/sec: 7316.47 - lr: 0.100000 +2023-03-29 17:19:06,955 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:19:06,955 EPOCH 61 done: loss 0.0141 - lr 0.100000 +2023-03-29 17:19:06,955 BAD EPOCHS (no improvement): 1 +2023-03-29 17:19:06,958 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:19:10,421 epoch 62 - iter 49/493 - loss 0.01347008 - time (sec): 3.46 - samples/sec: 7281.19 - lr: 0.100000 +2023-03-29 17:19:13,930 epoch 62 - iter 98/493 - loss 0.01371521 - time (sec): 6.97 - samples/sec: 7362.18 - lr: 0.100000 +2023-03-29 17:19:17,430 epoch 62 - iter 147/493 - loss 0.01392313 - time (sec): 10.47 - samples/sec: 7402.23 - lr: 0.100000 +2023-03-29 17:19:20,820 epoch 62 - iter 196/493 - loss 0.01348139 - time (sec): 13.86 - samples/sec: 7482.85 - lr: 0.100000 +2023-03-29 17:19:24,205 epoch 62 - iter 245/493 - loss 0.01348751 - time (sec): 17.25 - samples/sec: 7461.67 - lr: 0.100000 +2023-03-29 17:19:27,672 epoch 62 - iter 294/493 - loss 0.01354501 - time (sec): 20.71 - samples/sec: 7452.19 - lr: 0.100000 +2023-03-29 17:19:31,240 epoch 62 - iter 343/493 - loss 0.01367531 - time (sec): 24.28 - samples/sec: 7418.46 - lr: 0.100000 +2023-03-29 17:19:34,931 epoch 62 - iter 392/493 - loss 0.01373421 - time (sec): 27.97 - samples/sec: 7363.29 - lr: 0.100000 +2023-03-29 17:19:38,406 epoch 62 - iter 441/493 - loss 0.01388546 - time (sec): 31.45 - samples/sec: 7363.08 - lr: 0.100000 +2023-03-29 17:19:41,793 epoch 62 - iter 490/493 - loss 0.01386271 - time (sec): 34.84 - samples/sec: 7395.62 - lr: 0.100000 +2023-03-29 17:19:42,008 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:19:42,008 EPOCH 62 done: loss 0.0139 - lr 0.100000 +2023-03-29 17:19:42,008 BAD EPOCHS (no improvement): 0 +2023-03-29 17:19:42,011 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:19:45,531 epoch 63 - iter 49/493 - loss 0.01380628 - time (sec): 3.52 - samples/sec: 7353.07 - lr: 0.100000 +2023-03-29 17:19:49,009 epoch 63 - iter 98/493 - loss 0.01336162 - time (sec): 7.00 - samples/sec: 7314.26 - lr: 0.100000 +2023-03-29 17:19:52,700 epoch 63 - iter 147/493 - loss 0.01358568 - time (sec): 10.69 - samples/sec: 7268.56 - lr: 0.100000 +2023-03-29 17:19:56,192 epoch 63 - iter 196/493 - loss 0.01391087 - time (sec): 14.18 - samples/sec: 7339.24 - lr: 0.100000 +2023-03-29 17:19:59,508 epoch 63 - iter 245/493 - loss 0.01394779 - time (sec): 17.50 - samples/sec: 7360.64 - lr: 0.100000 +2023-03-29 17:20:03,040 epoch 63 - iter 294/493 - loss 0.01382026 - time (sec): 21.03 - samples/sec: 7378.82 - lr: 0.100000 +2023-03-29 17:20:06,645 epoch 63 - iter 343/493 - loss 0.01367075 - time (sec): 24.63 - samples/sec: 7334.23 - lr: 0.100000 +2023-03-29 17:20:10,112 epoch 63 - iter 392/493 - loss 0.01370568 - time (sec): 28.10 - samples/sec: 7341.12 - lr: 0.100000 +2023-03-29 17:20:13,476 epoch 63 - iter 441/493 - loss 0.01398788 - time (sec): 31.46 - samples/sec: 7355.34 - lr: 0.100000 +2023-03-29 17:20:17,188 epoch 63 - iter 490/493 - loss 0.01412362 - time (sec): 35.18 - samples/sec: 7323.53 - lr: 0.100000 +2023-03-29 17:20:17,495 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:20:17,495 EPOCH 63 done: loss 0.0141 - lr 0.100000 +2023-03-29 17:20:17,495 BAD EPOCHS (no improvement): 1 +2023-03-29 17:20:17,507 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:20:21,242 epoch 64 - iter 49/493 - loss 0.01181352 - time (sec): 3.74 - samples/sec: 7016.45 - lr: 0.100000 +2023-03-29 17:20:24,810 epoch 64 - iter 98/493 - loss 0.01236484 - time (sec): 7.30 - samples/sec: 7113.45 - lr: 0.100000 +2023-03-29 17:20:28,402 epoch 64 - iter 147/493 - loss 0.01220007 - time (sec): 10.89 - samples/sec: 7104.63 - lr: 0.100000 +2023-03-29 17:20:31,939 epoch 64 - iter 196/493 - loss 0.01250486 - time (sec): 14.43 - samples/sec: 7158.82 - lr: 0.100000 +2023-03-29 17:20:35,614 epoch 64 - iter 245/493 - loss 0.01269158 - time (sec): 18.11 - samples/sec: 7150.88 - lr: 0.100000 +2023-03-29 17:20:39,178 epoch 64 - iter 294/493 - loss 0.01276626 - time (sec): 21.67 - samples/sec: 7171.04 - lr: 0.100000 +2023-03-29 17:20:42,662 epoch 64 - iter 343/493 - loss 0.01288358 - time (sec): 25.15 - samples/sec: 7216.20 - lr: 0.100000 +2023-03-29 17:20:45,983 epoch 64 - iter 392/493 - loss 0.01267778 - time (sec): 28.48 - samples/sec: 7267.96 - lr: 0.100000 +2023-03-29 17:20:49,532 epoch 64 - iter 441/493 - loss 0.01272635 - time (sec): 32.03 - samples/sec: 7259.67 - lr: 0.100000 +2023-03-29 17:20:52,945 epoch 64 - iter 490/493 - loss 0.01282229 - time (sec): 35.44 - samples/sec: 7273.10 - lr: 0.100000 +2023-03-29 17:20:53,133 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:20:53,133 EPOCH 64 done: loss 0.0128 - lr 0.100000 +2023-03-29 17:20:53,133 BAD EPOCHS (no improvement): 0 +2023-03-29 17:20:53,146 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:20:56,767 epoch 65 - iter 49/493 - loss 0.01289008 - time (sec): 3.62 - samples/sec: 7071.46 - lr: 0.100000 +2023-03-29 17:21:00,204 epoch 65 - iter 98/493 - loss 0.01295738 - time (sec): 7.06 - samples/sec: 7222.68 - lr: 0.100000 +2023-03-29 17:21:03,757 epoch 65 - iter 147/493 - loss 0.01383996 - time (sec): 10.61 - samples/sec: 7250.18 - lr: 0.100000 +2023-03-29 17:21:07,261 epoch 65 - iter 196/493 - loss 0.01311985 - time (sec): 14.11 - samples/sec: 7275.79 - lr: 0.100000 +2023-03-29 17:21:10,796 epoch 65 - iter 245/493 - loss 0.01332136 - time (sec): 17.65 - samples/sec: 7277.64 - lr: 0.100000 +2023-03-29 17:21:14,365 epoch 65 - iter 294/493 - loss 0.01329845 - time (sec): 21.22 - samples/sec: 7289.78 - lr: 0.100000 +2023-03-29 17:21:17,863 epoch 65 - iter 343/493 - loss 0.01329281 - time (sec): 24.72 - samples/sec: 7300.47 - lr: 0.100000 +2023-03-29 17:21:21,499 epoch 65 - iter 392/493 - loss 0.01344102 - time (sec): 28.35 - samples/sec: 7271.27 - lr: 0.100000 +2023-03-29 17:21:25,108 epoch 65 - iter 441/493 - loss 0.01343916 - time (sec): 31.96 - samples/sec: 7249.00 - lr: 0.100000 +2023-03-29 17:21:28,612 epoch 65 - iter 490/493 - loss 0.01367235 - time (sec): 35.47 - samples/sec: 7263.28 - lr: 0.100000 +2023-03-29 17:21:28,837 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:21:28,837 EPOCH 65 done: loss 0.0136 - lr 0.100000 +2023-03-29 17:21:28,837 BAD EPOCHS (no improvement): 1 +2023-03-29 17:21:28,840 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:21:32,413 epoch 66 - iter 49/493 - loss 0.01304500 - time (sec): 3.57 - samples/sec: 7303.52 - lr: 0.100000 +2023-03-29 17:21:35,815 epoch 66 - iter 98/493 - loss 0.01305723 - time (sec): 6.98 - samples/sec: 7457.14 - lr: 0.100000 +2023-03-29 17:21:39,224 epoch 66 - iter 147/493 - loss 0.01325008 - time (sec): 10.38 - samples/sec: 7450.67 - lr: 0.100000 +2023-03-29 17:21:42,739 epoch 66 - iter 196/493 - loss 0.01299578 - time (sec): 13.90 - samples/sec: 7404.83 - lr: 0.100000 +2023-03-29 17:21:46,271 epoch 66 - iter 245/493 - loss 0.01303427 - time (sec): 17.43 - samples/sec: 7385.38 - lr: 0.100000 +2023-03-29 17:21:49,708 epoch 66 - iter 294/493 - loss 0.01337153 - time (sec): 20.87 - samples/sec: 7395.20 - lr: 0.100000 +2023-03-29 17:21:53,184 epoch 66 - iter 343/493 - loss 0.01343721 - time (sec): 24.34 - samples/sec: 7412.15 - lr: 0.100000 +2023-03-29 17:21:56,527 epoch 66 - iter 392/493 - loss 0.01337333 - time (sec): 27.69 - samples/sec: 7420.45 - lr: 0.100000 +2023-03-29 17:21:59,944 epoch 66 - iter 441/493 - loss 0.01357385 - time (sec): 31.10 - samples/sec: 7430.71 - lr: 0.100000 +2023-03-29 17:22:03,381 epoch 66 - iter 490/493 - loss 0.01388323 - time (sec): 34.54 - samples/sec: 7460.54 - lr: 0.100000 +2023-03-29 17:22:03,563 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:22:03,563 EPOCH 66 done: loss 0.0139 - lr 0.100000 +2023-03-29 17:22:03,563 BAD EPOCHS (no improvement): 2 +2023-03-29 17:22:03,566 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:22:06,943 epoch 67 - iter 49/493 - loss 0.01114057 - time (sec): 3.38 - samples/sec: 7645.56 - lr: 0.100000 +2023-03-29 17:22:10,328 epoch 67 - iter 98/493 - loss 0.01239925 - time (sec): 6.76 - samples/sec: 7632.21 - lr: 0.100000 +2023-03-29 17:22:13,617 epoch 67 - iter 147/493 - loss 0.01175981 - time (sec): 10.05 - samples/sec: 7635.40 - lr: 0.100000 +2023-03-29 17:22:17,075 epoch 67 - iter 196/493 - loss 0.01204963 - time (sec): 13.51 - samples/sec: 7587.78 - lr: 0.100000 +2023-03-29 17:22:20,334 epoch 67 - iter 245/493 - loss 0.01210831 - time (sec): 16.77 - samples/sec: 7635.00 - lr: 0.100000 +2023-03-29 17:22:23,641 epoch 67 - iter 294/493 - loss 0.01254705 - time (sec): 20.07 - samples/sec: 7654.92 - lr: 0.100000 +2023-03-29 17:22:27,147 epoch 67 - iter 343/493 - loss 0.01288148 - time (sec): 23.58 - samples/sec: 7619.76 - lr: 0.100000 +2023-03-29 17:22:30,620 epoch 67 - iter 392/493 - loss 0.01301038 - time (sec): 27.05 - samples/sec: 7598.98 - lr: 0.100000 +2023-03-29 17:22:34,152 epoch 67 - iter 441/493 - loss 0.01319562 - time (sec): 30.59 - samples/sec: 7572.64 - lr: 0.100000 +2023-03-29 17:22:37,715 epoch 67 - iter 490/493 - loss 0.01319560 - time (sec): 34.15 - samples/sec: 7544.13 - lr: 0.100000 +2023-03-29 17:22:37,923 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:22:37,923 EPOCH 67 done: loss 0.0132 - lr 0.100000 +2023-03-29 17:22:37,923 BAD EPOCHS (no improvement): 3 +2023-03-29 17:22:37,926 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:22:41,499 epoch 68 - iter 49/493 - loss 0.01013715 - time (sec): 3.57 - samples/sec: 7250.98 - lr: 0.100000 +2023-03-29 17:22:44,766 epoch 68 - iter 98/493 - loss 0.01095767 - time (sec): 6.84 - samples/sec: 7509.90 - lr: 0.100000 +2023-03-29 17:22:48,175 epoch 68 - iter 147/493 - loss 0.01186890 - time (sec): 10.25 - samples/sec: 7559.05 - lr: 0.100000 +2023-03-29 17:22:51,512 epoch 68 - iter 196/493 - loss 0.01211961 - time (sec): 13.59 - samples/sec: 7561.57 - lr: 0.100000 +2023-03-29 17:22:54,785 epoch 68 - iter 245/493 - loss 0.01266951 - time (sec): 16.86 - samples/sec: 7589.12 - lr: 0.100000 +2023-03-29 17:22:58,145 epoch 68 - iter 294/493 - loss 0.01270952 - time (sec): 20.22 - samples/sec: 7591.24 - lr: 0.100000 +2023-03-29 17:23:01,498 epoch 68 - iter 343/493 - loss 0.01315991 - time (sec): 23.57 - samples/sec: 7603.24 - lr: 0.100000 +2023-03-29 17:23:04,980 epoch 68 - iter 392/493 - loss 0.01328441 - time (sec): 27.05 - samples/sec: 7583.58 - lr: 0.100000 +2023-03-29 17:23:08,405 epoch 68 - iter 441/493 - loss 0.01355643 - time (sec): 30.48 - samples/sec: 7579.13 - lr: 0.100000 +2023-03-29 17:23:11,948 epoch 68 - iter 490/493 - loss 0.01352761 - time (sec): 34.02 - samples/sec: 7569.81 - lr: 0.100000 +2023-03-29 17:23:12,144 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:23:12,145 EPOCH 68 done: loss 0.0135 - lr 0.100000 +2023-03-29 17:23:12,145 Epoch 68: reducing learning rate of group 0 to 5.0000e-02. +2023-03-29 17:23:12,145 BAD EPOCHS (no improvement): 4 +2023-03-29 17:23:12,148 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:23:15,497 epoch 69 - iter 49/493 - loss 0.01171368 - time (sec): 3.35 - samples/sec: 7622.08 - lr: 0.050000 +2023-03-29 17:23:18,799 epoch 69 - iter 98/493 - loss 0.01117632 - time (sec): 6.65 - samples/sec: 7592.76 - lr: 0.050000 +2023-03-29 17:23:22,192 epoch 69 - iter 147/493 - loss 0.01098222 - time (sec): 10.04 - samples/sec: 7596.17 - lr: 0.050000 +2023-03-29 17:23:25,634 epoch 69 - iter 196/493 - loss 0.01094257 - time (sec): 13.49 - samples/sec: 7627.80 - lr: 0.050000 +2023-03-29 17:23:29,021 epoch 69 - iter 245/493 - loss 0.01131774 - time (sec): 16.87 - samples/sec: 7605.78 - lr: 0.050000 +2023-03-29 17:23:32,517 epoch 69 - iter 294/493 - loss 0.01116370 - time (sec): 20.37 - samples/sec: 7540.97 - lr: 0.050000 +2023-03-29 17:23:35,829 epoch 69 - iter 343/493 - loss 0.01131542 - time (sec): 23.68 - samples/sec: 7586.10 - lr: 0.050000 +2023-03-29 17:23:39,254 epoch 69 - iter 392/493 - loss 0.01132121 - time (sec): 27.11 - samples/sec: 7591.85 - lr: 0.050000 +2023-03-29 17:23:42,670 epoch 69 - iter 441/493 - loss 0.01158834 - time (sec): 30.52 - samples/sec: 7580.55 - lr: 0.050000 +2023-03-29 17:23:46,105 epoch 69 - iter 490/493 - loss 0.01148656 - time (sec): 33.96 - samples/sec: 7583.37 - lr: 0.050000 +2023-03-29 17:23:46,363 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:23:46,364 EPOCH 69 done: loss 0.0115 - lr 0.050000 +2023-03-29 17:23:46,364 BAD EPOCHS (no improvement): 0 +2023-03-29 17:23:46,367 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:23:49,932 epoch 70 - iter 49/493 - loss 0.01105996 - time (sec): 3.57 - samples/sec: 7492.74 - lr: 0.050000 +2023-03-29 17:23:53,230 epoch 70 - iter 98/493 - loss 0.01113480 - time (sec): 6.86 - samples/sec: 7609.16 - lr: 0.050000 +2023-03-29 17:23:56,722 epoch 70 - iter 147/493 - loss 0.01170958 - time (sec): 10.36 - samples/sec: 7534.25 - lr: 0.050000 +2023-03-29 17:24:00,321 epoch 70 - iter 196/493 - loss 0.01134969 - time (sec): 13.95 - samples/sec: 7483.63 - lr: 0.050000 +2023-03-29 17:24:03,762 epoch 70 - iter 245/493 - loss 0.01156641 - time (sec): 17.40 - samples/sec: 7439.13 - lr: 0.050000 +2023-03-29 17:24:07,055 epoch 70 - iter 294/493 - loss 0.01133544 - time (sec): 20.69 - samples/sec: 7470.67 - lr: 0.050000 +2023-03-29 17:24:10,645 epoch 70 - iter 343/493 - loss 0.01128159 - time (sec): 24.28 - samples/sec: 7438.67 - lr: 0.050000 +2023-03-29 17:24:14,225 epoch 70 - iter 392/493 - loss 0.01111996 - time (sec): 27.86 - samples/sec: 7434.02 - lr: 0.050000 +2023-03-29 17:24:17,608 epoch 70 - iter 441/493 - loss 0.01093840 - time (sec): 31.24 - samples/sec: 7435.53 - lr: 0.050000 +2023-03-29 17:24:21,059 epoch 70 - iter 490/493 - loss 0.01092195 - time (sec): 34.69 - samples/sec: 7427.28 - lr: 0.050000 +2023-03-29 17:24:21,293 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:24:21,293 EPOCH 70 done: loss 0.0109 - lr 0.050000 +2023-03-29 17:24:21,293 BAD EPOCHS (no improvement): 0 +2023-03-29 17:24:21,296 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:24:24,867 epoch 71 - iter 49/493 - loss 0.01226585 - time (sec): 3.57 - samples/sec: 7188.35 - lr: 0.050000 +2023-03-29 17:24:28,318 epoch 71 - iter 98/493 - loss 0.01132077 - time (sec): 7.02 - samples/sec: 7289.37 - lr: 0.050000 +2023-03-29 17:24:31,838 epoch 71 - iter 147/493 - loss 0.01092955 - time (sec): 10.54 - samples/sec: 7239.33 - lr: 0.050000 +2023-03-29 17:24:35,410 epoch 71 - iter 196/493 - loss 0.01112133 - time (sec): 14.11 - samples/sec: 7285.46 - lr: 0.050000 +2023-03-29 17:24:38,779 epoch 71 - iter 245/493 - loss 0.01070353 - time (sec): 17.48 - samples/sec: 7330.41 - lr: 0.050000 +2023-03-29 17:24:42,277 epoch 71 - iter 294/493 - loss 0.01074123 - time (sec): 20.98 - samples/sec: 7380.12 - lr: 0.050000 +2023-03-29 17:24:45,728 epoch 71 - iter 343/493 - loss 0.01092731 - time (sec): 24.43 - samples/sec: 7399.83 - lr: 0.050000 +2023-03-29 17:24:49,002 epoch 71 - iter 392/493 - loss 0.01083803 - time (sec): 27.71 - samples/sec: 7431.33 - lr: 0.050000 +2023-03-29 17:24:52,365 epoch 71 - iter 441/493 - loss 0.01102854 - time (sec): 31.07 - samples/sec: 7464.33 - lr: 0.050000 +2023-03-29 17:24:55,768 epoch 71 - iter 490/493 - loss 0.01079234 - time (sec): 34.47 - samples/sec: 7472.74 - lr: 0.050000 +2023-03-29 17:24:55,976 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:24:55,976 EPOCH 71 done: loss 0.0108 - lr 0.050000 +2023-03-29 17:24:55,976 BAD EPOCHS (no improvement): 0 +2023-03-29 17:24:55,979 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:24:59,364 epoch 72 - iter 49/493 - loss 0.01048003 - time (sec): 3.39 - samples/sec: 7639.49 - lr: 0.050000 +2023-03-29 17:25:02,802 epoch 72 - iter 98/493 - loss 0.01081559 - time (sec): 6.82 - samples/sec: 7595.59 - lr: 0.050000 +2023-03-29 17:25:06,180 epoch 72 - iter 147/493 - loss 0.01120801 - time (sec): 10.20 - samples/sec: 7618.84 - lr: 0.050000 +2023-03-29 17:25:09,799 epoch 72 - iter 196/493 - loss 0.01138571 - time (sec): 13.82 - samples/sec: 7474.17 - lr: 0.050000 +2023-03-29 17:25:13,288 epoch 72 - iter 245/493 - loss 0.01129584 - time (sec): 17.31 - samples/sec: 7420.36 - lr: 0.050000 +2023-03-29 17:25:16,781 epoch 72 - iter 294/493 - loss 0.01122859 - time (sec): 20.80 - samples/sec: 7417.37 - lr: 0.050000 +2023-03-29 17:25:20,284 epoch 72 - iter 343/493 - loss 0.01136076 - time (sec): 24.31 - samples/sec: 7406.42 - lr: 0.050000 +2023-03-29 17:25:23,758 epoch 72 - iter 392/493 - loss 0.01114565 - time (sec): 27.78 - samples/sec: 7409.50 - lr: 0.050000 +2023-03-29 17:25:27,385 epoch 72 - iter 441/493 - loss 0.01097188 - time (sec): 31.41 - samples/sec: 7365.87 - lr: 0.050000 +2023-03-29 17:25:30,896 epoch 72 - iter 490/493 - loss 0.01097012 - time (sec): 34.92 - samples/sec: 7379.41 - lr: 0.050000 +2023-03-29 17:25:31,094 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:25:31,094 EPOCH 72 done: loss 0.0110 - lr 0.050000 +2023-03-29 17:25:31,094 BAD EPOCHS (no improvement): 1 +2023-03-29 17:25:31,097 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:25:34,663 epoch 73 - iter 49/493 - loss 0.01061080 - time (sec): 3.57 - samples/sec: 7324.84 - lr: 0.050000 +2023-03-29 17:25:38,148 epoch 73 - iter 98/493 - loss 0.01112468 - time (sec): 7.05 - samples/sec: 7387.56 - lr: 0.050000 +2023-03-29 17:25:41,604 epoch 73 - iter 147/493 - loss 0.01064969 - time (sec): 10.51 - samples/sec: 7336.15 - lr: 0.050000 +2023-03-29 17:25:44,977 epoch 73 - iter 196/493 - loss 0.01092566 - time (sec): 13.88 - samples/sec: 7415.77 - lr: 0.050000 +2023-03-29 17:25:48,368 epoch 73 - iter 245/493 - loss 0.01064025 - time (sec): 17.27 - samples/sec: 7434.77 - lr: 0.050000 +2023-03-29 17:25:51,748 epoch 73 - iter 294/493 - loss 0.01078392 - time (sec): 20.65 - samples/sec: 7425.55 - lr: 0.050000 +2023-03-29 17:25:55,142 epoch 73 - iter 343/493 - loss 0.01097633 - time (sec): 24.05 - samples/sec: 7461.26 - lr: 0.050000 +2023-03-29 17:25:58,764 epoch 73 - iter 392/493 - loss 0.01081272 - time (sec): 27.67 - samples/sec: 7451.43 - lr: 0.050000 +2023-03-29 17:26:02,035 epoch 73 - iter 441/493 - loss 0.01068652 - time (sec): 30.94 - samples/sec: 7480.04 - lr: 0.050000 +2023-03-29 17:26:05,426 epoch 73 - iter 490/493 - loss 0.01072536 - time (sec): 34.33 - samples/sec: 7498.69 - lr: 0.050000 +2023-03-29 17:26:05,647 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:26:05,647 EPOCH 73 done: loss 0.0107 - lr 0.050000 +2023-03-29 17:26:05,647 BAD EPOCHS (no improvement): 0 +2023-03-29 17:26:05,650 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:26:08,966 epoch 74 - iter 49/493 - loss 0.01202913 - time (sec): 3.32 - samples/sec: 7576.87 - lr: 0.050000 +2023-03-29 17:26:12,345 epoch 74 - iter 98/493 - loss 0.01058554 - time (sec): 6.69 - samples/sec: 7621.67 - lr: 0.050000 +2023-03-29 17:26:15,724 epoch 74 - iter 147/493 - loss 0.00976941 - time (sec): 10.07 - samples/sec: 7618.16 - lr: 0.050000 +2023-03-29 17:26:19,161 epoch 74 - iter 196/493 - loss 0.00996838 - time (sec): 13.51 - samples/sec: 7608.96 - lr: 0.050000 +2023-03-29 17:26:22,600 epoch 74 - iter 245/493 - loss 0.00990701 - time (sec): 16.95 - samples/sec: 7574.92 - lr: 0.050000 +2023-03-29 17:26:26,042 epoch 74 - iter 294/493 - loss 0.00981314 - time (sec): 20.39 - samples/sec: 7590.99 - lr: 0.050000 +2023-03-29 17:26:29,505 epoch 74 - iter 343/493 - loss 0.01015396 - time (sec): 23.85 - samples/sec: 7581.50 - lr: 0.050000 +2023-03-29 17:26:32,922 epoch 74 - iter 392/493 - loss 0.01034269 - time (sec): 27.27 - samples/sec: 7573.68 - lr: 0.050000 +2023-03-29 17:26:36,248 epoch 74 - iter 441/493 - loss 0.01033233 - time (sec): 30.60 - samples/sec: 7569.14 - lr: 0.050000 +2023-03-29 17:26:39,728 epoch 74 - iter 490/493 - loss 0.01023915 - time (sec): 34.08 - samples/sec: 7556.70 - lr: 0.050000 +2023-03-29 17:26:39,950 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:26:39,950 EPOCH 74 done: loss 0.0102 - lr 0.050000 +2023-03-29 17:26:39,950 BAD EPOCHS (no improvement): 0 +2023-03-29 17:26:39,953 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:26:43,307 epoch 75 - iter 49/493 - loss 0.00885348 - time (sec): 3.35 - samples/sec: 7494.50 - lr: 0.050000 +2023-03-29 17:26:46,767 epoch 75 - iter 98/493 - loss 0.00988912 - time (sec): 6.81 - samples/sec: 7513.70 - lr: 0.050000 +2023-03-29 17:26:50,131 epoch 75 - iter 147/493 - loss 0.00927253 - time (sec): 10.18 - samples/sec: 7618.39 - lr: 0.050000 +2023-03-29 17:26:53,450 epoch 75 - iter 196/493 - loss 0.00963817 - time (sec): 13.50 - samples/sec: 7628.57 - lr: 0.050000 +2023-03-29 17:26:56,853 epoch 75 - iter 245/493 - loss 0.00945055 - time (sec): 16.90 - samples/sec: 7606.94 - lr: 0.050000 +2023-03-29 17:27:00,302 epoch 75 - iter 294/493 - loss 0.00925766 - time (sec): 20.35 - samples/sec: 7568.98 - lr: 0.050000 +2023-03-29 17:27:06,603 epoch 75 - iter 343/493 - loss 0.00920292 - time (sec): 26.65 - samples/sec: 6740.72 - lr: 0.050000 +2023-03-29 17:27:10,060 epoch 75 - iter 392/493 - loss 0.00910148 - time (sec): 30.11 - samples/sec: 6834.98 - lr: 0.050000 +2023-03-29 17:27:13,535 epoch 75 - iter 441/493 - loss 0.00940079 - time (sec): 33.58 - samples/sec: 6913.37 - lr: 0.050000 +2023-03-29 17:27:16,847 epoch 75 - iter 490/493 - loss 0.00953565 - time (sec): 36.89 - samples/sec: 6978.41 - lr: 0.050000 +2023-03-29 17:27:17,107 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:27:17,108 EPOCH 75 done: loss 0.0095 - lr 0.050000 +2023-03-29 17:27:17,108 BAD EPOCHS (no improvement): 0 +2023-03-29 17:27:17,111 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:27:20,568 epoch 76 - iter 49/493 - loss 0.00981784 - time (sec): 3.46 - samples/sec: 7362.12 - lr: 0.050000 +2023-03-29 17:27:24,117 epoch 76 - iter 98/493 - loss 0.01066915 - time (sec): 7.01 - samples/sec: 7379.81 - lr: 0.050000 +2023-03-29 17:27:27,512 epoch 76 - iter 147/493 - loss 0.01098721 - time (sec): 10.40 - samples/sec: 7394.50 - lr: 0.050000 +2023-03-29 17:27:31,106 epoch 76 - iter 196/493 - loss 0.01039730 - time (sec): 14.00 - samples/sec: 7387.07 - lr: 0.050000 +2023-03-29 17:27:34,442 epoch 76 - iter 245/493 - loss 0.01030536 - time (sec): 17.33 - samples/sec: 7424.82 - lr: 0.050000 +2023-03-29 17:27:37,794 epoch 76 - iter 294/493 - loss 0.01025668 - time (sec): 20.68 - samples/sec: 7467.47 - lr: 0.050000 +2023-03-29 17:27:41,073 epoch 76 - iter 343/493 - loss 0.01048481 - time (sec): 23.96 - samples/sec: 7506.74 - lr: 0.050000 +2023-03-29 17:27:44,653 epoch 76 - iter 392/493 - loss 0.01019815 - time (sec): 27.54 - samples/sec: 7486.25 - lr: 0.050000 +2023-03-29 17:27:48,014 epoch 76 - iter 441/493 - loss 0.01018646 - time (sec): 30.90 - samples/sec: 7514.59 - lr: 0.050000 +2023-03-29 17:27:51,307 epoch 76 - iter 490/493 - loss 0.01012295 - time (sec): 34.20 - samples/sec: 7536.74 - lr: 0.050000 +2023-03-29 17:27:51,505 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:27:51,505 EPOCH 76 done: loss 0.0101 - lr 0.050000 +2023-03-29 17:27:51,505 BAD EPOCHS (no improvement): 1 +2023-03-29 17:27:51,508 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:27:54,747 epoch 77 - iter 49/493 - loss 0.00828988 - time (sec): 3.24 - samples/sec: 7803.56 - lr: 0.050000 +2023-03-29 17:27:58,121 epoch 77 - iter 98/493 - loss 0.00979376 - time (sec): 6.61 - samples/sec: 7672.96 - lr: 0.050000 +2023-03-29 17:28:01,728 epoch 77 - iter 147/493 - loss 0.00967213 - time (sec): 10.22 - samples/sec: 7594.07 - lr: 0.050000 +2023-03-29 17:28:05,051 epoch 77 - iter 196/493 - loss 0.00943330 - time (sec): 13.54 - samples/sec: 7601.21 - lr: 0.050000 +2023-03-29 17:28:08,476 epoch 77 - iter 245/493 - loss 0.00940306 - time (sec): 16.97 - samples/sec: 7562.10 - lr: 0.050000 +2023-03-29 17:28:11,959 epoch 77 - iter 294/493 - loss 0.00942384 - time (sec): 20.45 - samples/sec: 7538.00 - lr: 0.050000 +2023-03-29 17:28:15,487 epoch 77 - iter 343/493 - loss 0.00921174 - time (sec): 23.98 - samples/sec: 7521.36 - lr: 0.050000 +2023-03-29 17:28:18,941 epoch 77 - iter 392/493 - loss 0.00924901 - time (sec): 27.43 - samples/sec: 7522.48 - lr: 0.050000 +2023-03-29 17:28:22,389 epoch 77 - iter 441/493 - loss 0.00909774 - time (sec): 30.88 - samples/sec: 7514.47 - lr: 0.050000 +2023-03-29 17:28:25,706 epoch 77 - iter 490/493 - loss 0.00927596 - time (sec): 34.20 - samples/sec: 7531.27 - lr: 0.050000 +2023-03-29 17:28:25,920 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:28:25,920 EPOCH 77 done: loss 0.0093 - lr 0.050000 +2023-03-29 17:28:25,920 BAD EPOCHS (no improvement): 0 +2023-03-29 17:28:25,923 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:28:29,316 epoch 78 - iter 49/493 - loss 0.01051722 - time (sec): 3.39 - samples/sec: 7613.50 - lr: 0.050000 +2023-03-29 17:28:32,790 epoch 78 - iter 98/493 - loss 0.00926310 - time (sec): 6.87 - samples/sec: 7610.89 - lr: 0.050000 +2023-03-29 17:28:36,206 epoch 78 - iter 147/493 - loss 0.00921288 - time (sec): 10.28 - samples/sec: 7586.14 - lr: 0.050000 +2023-03-29 17:28:39,631 epoch 78 - iter 196/493 - loss 0.00933609 - time (sec): 13.71 - samples/sec: 7595.57 - lr: 0.050000 +2023-03-29 17:28:43,005 epoch 78 - iter 245/493 - loss 0.00927300 - time (sec): 17.08 - samples/sec: 7565.38 - lr: 0.050000 +2023-03-29 17:28:46,356 epoch 78 - iter 294/493 - loss 0.00943744 - time (sec): 20.43 - samples/sec: 7565.25 - lr: 0.050000 +2023-03-29 17:28:49,748 epoch 78 - iter 343/493 - loss 0.00939066 - time (sec): 23.82 - samples/sec: 7572.99 - lr: 0.050000 +2023-03-29 17:28:53,229 epoch 78 - iter 392/493 - loss 0.00942446 - time (sec): 27.31 - samples/sec: 7542.32 - lr: 0.050000 +2023-03-29 17:28:56,551 epoch 78 - iter 441/493 - loss 0.00962718 - time (sec): 30.63 - samples/sec: 7560.15 - lr: 0.050000 +2023-03-29 17:29:00,053 epoch 78 - iter 490/493 - loss 0.00963655 - time (sec): 34.13 - samples/sec: 7548.98 - lr: 0.050000 +2023-03-29 17:29:00,258 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:29:00,258 EPOCH 78 done: loss 0.0096 - lr 0.050000 +2023-03-29 17:29:00,258 BAD EPOCHS (no improvement): 1 +2023-03-29 17:29:00,262 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:29:03,767 epoch 79 - iter 49/493 - loss 0.01055823 - time (sec): 3.51 - samples/sec: 7529.80 - lr: 0.050000 +2023-03-29 17:29:07,219 epoch 79 - iter 98/493 - loss 0.00952825 - time (sec): 6.96 - samples/sec: 7490.31 - lr: 0.050000 +2023-03-29 17:29:10,590 epoch 79 - iter 147/493 - loss 0.00905265 - time (sec): 10.33 - samples/sec: 7533.85 - lr: 0.050000 +2023-03-29 17:29:13,923 epoch 79 - iter 196/493 - loss 0.00910520 - time (sec): 13.66 - samples/sec: 7536.71 - lr: 0.050000 +2023-03-29 17:29:17,404 epoch 79 - iter 245/493 - loss 0.00966195 - time (sec): 17.14 - samples/sec: 7536.00 - lr: 0.050000 +2023-03-29 17:29:20,718 epoch 79 - iter 294/493 - loss 0.00972959 - time (sec): 20.46 - samples/sec: 7568.25 - lr: 0.050000 +2023-03-29 17:29:24,267 epoch 79 - iter 343/493 - loss 0.01010607 - time (sec): 24.01 - samples/sec: 7555.83 - lr: 0.050000 +2023-03-29 17:29:27,765 epoch 79 - iter 392/493 - loss 0.00988854 - time (sec): 27.50 - samples/sec: 7515.13 - lr: 0.050000 +2023-03-29 17:29:31,125 epoch 79 - iter 441/493 - loss 0.00975348 - time (sec): 30.86 - samples/sec: 7527.60 - lr: 0.050000 +2023-03-29 17:29:34,560 epoch 79 - iter 490/493 - loss 0.00982827 - time (sec): 34.30 - samples/sec: 7504.35 - lr: 0.050000 +2023-03-29 17:29:34,806 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:29:34,806 EPOCH 79 done: loss 0.0098 - lr 0.050000 +2023-03-29 17:29:34,806 BAD EPOCHS (no improvement): 2 +2023-03-29 17:29:34,809 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:29:38,302 epoch 80 - iter 49/493 - loss 0.00955727 - time (sec): 3.49 - samples/sec: 7391.98 - lr: 0.050000 +2023-03-29 17:29:41,748 epoch 80 - iter 98/493 - loss 0.01010763 - time (sec): 6.94 - samples/sec: 7374.58 - lr: 0.050000 +2023-03-29 17:29:45,301 epoch 80 - iter 147/493 - loss 0.00991690 - time (sec): 10.49 - samples/sec: 7383.10 - lr: 0.050000 +2023-03-29 17:29:48,822 epoch 80 - iter 196/493 - loss 0.00964989 - time (sec): 14.01 - samples/sec: 7381.68 - lr: 0.050000 +2023-03-29 17:29:52,540 epoch 80 - iter 245/493 - loss 0.00940646 - time (sec): 17.73 - samples/sec: 7325.79 - lr: 0.050000 +2023-03-29 17:29:56,155 epoch 80 - iter 294/493 - loss 0.00957563 - time (sec): 21.35 - samples/sec: 7290.71 - lr: 0.050000 +2023-03-29 17:29:59,472 epoch 80 - iter 343/493 - loss 0.00952503 - time (sec): 24.66 - samples/sec: 7333.49 - lr: 0.050000 +2023-03-29 17:30:02,934 epoch 80 - iter 392/493 - loss 0.00958252 - time (sec): 28.12 - samples/sec: 7347.70 - lr: 0.050000 +2023-03-29 17:30:06,349 epoch 80 - iter 441/493 - loss 0.00952980 - time (sec): 31.54 - samples/sec: 7346.34 - lr: 0.050000 +2023-03-29 17:30:09,834 epoch 80 - iter 490/493 - loss 0.00942324 - time (sec): 35.02 - samples/sec: 7354.60 - lr: 0.050000 +2023-03-29 17:30:10,030 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:30:10,031 EPOCH 80 done: loss 0.0094 - lr 0.050000 +2023-03-29 17:30:10,031 BAD EPOCHS (no improvement): 3 +2023-03-29 17:30:10,033 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:30:13,598 epoch 81 - iter 49/493 - loss 0.01002106 - time (sec): 3.56 - samples/sec: 7190.54 - lr: 0.050000 +2023-03-29 17:30:17,103 epoch 81 - iter 98/493 - loss 0.00985517 - time (sec): 7.07 - samples/sec: 7204.94 - lr: 0.050000 +2023-03-29 17:30:20,529 epoch 81 - iter 147/493 - loss 0.01044884 - time (sec): 10.50 - samples/sec: 7318.60 - lr: 0.050000 +2023-03-29 17:30:24,062 epoch 81 - iter 196/493 - loss 0.00955628 - time (sec): 14.03 - samples/sec: 7262.02 - lr: 0.050000 +2023-03-29 17:30:27,549 epoch 81 - iter 245/493 - loss 0.00979656 - time (sec): 17.52 - samples/sec: 7298.53 - lr: 0.050000 +2023-03-29 17:30:31,098 epoch 81 - iter 294/493 - loss 0.00971134 - time (sec): 21.06 - samples/sec: 7324.09 - lr: 0.050000 +2023-03-29 17:30:34,526 epoch 81 - iter 343/493 - loss 0.00960326 - time (sec): 24.49 - samples/sec: 7352.22 - lr: 0.050000 +2023-03-29 17:30:38,139 epoch 81 - iter 392/493 - loss 0.00971190 - time (sec): 28.11 - samples/sec: 7329.36 - lr: 0.050000 +2023-03-29 17:30:41,417 epoch 81 - iter 441/493 - loss 0.00965209 - time (sec): 31.38 - samples/sec: 7364.74 - lr: 0.050000 +2023-03-29 17:30:44,986 epoch 81 - iter 490/493 - loss 0.00996203 - time (sec): 34.95 - samples/sec: 7370.03 - lr: 0.050000 +2023-03-29 17:30:45,209 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:30:45,209 EPOCH 81 done: loss 0.0100 - lr 0.050000 +2023-03-29 17:30:45,210 Epoch 81: reducing learning rate of group 0 to 2.5000e-02. +2023-03-29 17:30:45,210 BAD EPOCHS (no improvement): 4 +2023-03-29 17:30:45,213 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:30:48,752 epoch 82 - iter 49/493 - loss 0.01074600 - time (sec): 3.54 - samples/sec: 7203.20 - lr: 0.025000 +2023-03-29 17:30:52,210 epoch 82 - iter 98/493 - loss 0.01073206 - time (sec): 7.00 - samples/sec: 7330.66 - lr: 0.025000 +2023-03-29 17:30:55,832 epoch 82 - iter 147/493 - loss 0.00974743 - time (sec): 10.62 - samples/sec: 7243.69 - lr: 0.025000 +2023-03-29 17:30:59,220 epoch 82 - iter 196/493 - loss 0.00909511 - time (sec): 14.01 - samples/sec: 7344.79 - lr: 0.025000 +2023-03-29 17:31:02,647 epoch 82 - iter 245/493 - loss 0.00898577 - time (sec): 17.43 - samples/sec: 7372.98 - lr: 0.025000 +2023-03-29 17:31:06,045 epoch 82 - iter 294/493 - loss 0.00890555 - time (sec): 20.83 - samples/sec: 7407.49 - lr: 0.025000 +2023-03-29 17:31:09,501 epoch 82 - iter 343/493 - loss 0.00886367 - time (sec): 24.29 - samples/sec: 7432.85 - lr: 0.025000 +2023-03-29 17:31:12,807 epoch 82 - iter 392/493 - loss 0.00886122 - time (sec): 27.59 - samples/sec: 7431.87 - lr: 0.025000 +2023-03-29 17:31:16,265 epoch 82 - iter 441/493 - loss 0.00891728 - time (sec): 31.05 - samples/sec: 7441.66 - lr: 0.025000 +2023-03-29 17:31:19,651 epoch 82 - iter 490/493 - loss 0.00882848 - time (sec): 34.44 - samples/sec: 7479.92 - lr: 0.025000 +2023-03-29 17:31:19,872 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:31:19,872 EPOCH 82 done: loss 0.0088 - lr 0.025000 +2023-03-29 17:31:19,872 BAD EPOCHS (no improvement): 0 +2023-03-29 17:31:19,875 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:31:23,528 epoch 83 - iter 49/493 - loss 0.00639402 - time (sec): 3.65 - samples/sec: 7304.73 - lr: 0.025000 +2023-03-29 17:31:26,864 epoch 83 - iter 98/493 - loss 0.00685855 - time (sec): 6.99 - samples/sec: 7496.75 - lr: 0.025000 +2023-03-29 17:31:30,176 epoch 83 - iter 147/493 - loss 0.00743186 - time (sec): 10.30 - samples/sec: 7575.61 - lr: 0.025000 +2023-03-29 17:31:33,646 epoch 83 - iter 196/493 - loss 0.00746254 - time (sec): 13.77 - samples/sec: 7520.50 - lr: 0.025000 +2023-03-29 17:31:37,019 epoch 83 - iter 245/493 - loss 0.00747551 - time (sec): 17.14 - samples/sec: 7537.19 - lr: 0.025000 +2023-03-29 17:31:40,315 epoch 83 - iter 294/493 - loss 0.00751471 - time (sec): 20.44 - samples/sec: 7580.86 - lr: 0.025000 +2023-03-29 17:31:43,676 epoch 83 - iter 343/493 - loss 0.00753261 - time (sec): 23.80 - samples/sec: 7586.15 - lr: 0.025000 +2023-03-29 17:31:47,046 epoch 83 - iter 392/493 - loss 0.00766587 - time (sec): 27.17 - samples/sec: 7572.96 - lr: 0.025000 +2023-03-29 17:31:50,532 epoch 83 - iter 441/493 - loss 0.00777515 - time (sec): 30.66 - samples/sec: 7577.36 - lr: 0.025000 +2023-03-29 17:31:53,781 epoch 83 - iter 490/493 - loss 0.00768110 - time (sec): 33.91 - samples/sec: 7590.31 - lr: 0.025000 +2023-03-29 17:31:54,060 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:31:54,060 EPOCH 83 done: loss 0.0077 - lr 0.025000 +2023-03-29 17:31:54,060 BAD EPOCHS (no improvement): 0 +2023-03-29 17:31:54,063 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:31:57,669 epoch 84 - iter 49/493 - loss 0.00951597 - time (sec): 3.61 - samples/sec: 7237.85 - lr: 0.025000 +2023-03-29 17:32:00,895 epoch 84 - iter 98/493 - loss 0.00926416 - time (sec): 6.83 - samples/sec: 7455.17 - lr: 0.025000 +2023-03-29 17:32:04,371 epoch 84 - iter 147/493 - loss 0.00867070 - time (sec): 10.31 - samples/sec: 7485.51 - lr: 0.025000 +2023-03-29 17:32:07,664 epoch 84 - iter 196/493 - loss 0.00837038 - time (sec): 13.60 - samples/sec: 7546.98 - lr: 0.025000 +2023-03-29 17:32:11,078 epoch 84 - iter 245/493 - loss 0.00822513 - time (sec): 17.01 - samples/sec: 7585.11 - lr: 0.025000 +2023-03-29 17:32:14,627 epoch 84 - iter 294/493 - loss 0.00807168 - time (sec): 20.56 - samples/sec: 7556.60 - lr: 0.025000 +2023-03-29 17:32:18,000 epoch 84 - iter 343/493 - loss 0.00805656 - time (sec): 23.94 - samples/sec: 7570.48 - lr: 0.025000 +2023-03-29 17:32:21,290 epoch 84 - iter 392/493 - loss 0.00813457 - time (sec): 27.23 - samples/sec: 7578.98 - lr: 0.025000 +2023-03-29 17:32:24,768 epoch 84 - iter 441/493 - loss 0.00821600 - time (sec): 30.70 - samples/sec: 7549.98 - lr: 0.025000 +2023-03-29 17:32:28,215 epoch 84 - iter 490/493 - loss 0.00825681 - time (sec): 34.15 - samples/sec: 7544.04 - lr: 0.025000 +2023-03-29 17:32:28,449 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:32:28,449 EPOCH 84 done: loss 0.0083 - lr 0.025000 +2023-03-29 17:32:28,449 BAD EPOCHS (no improvement): 1 +2023-03-29 17:32:28,452 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:32:31,875 epoch 85 - iter 49/493 - loss 0.00888830 - time (sec): 3.42 - samples/sec: 7448.75 - lr: 0.025000 +2023-03-29 17:32:35,427 epoch 85 - iter 98/493 - loss 0.00945619 - time (sec): 6.97 - samples/sec: 7417.30 - lr: 0.025000 +2023-03-29 17:32:38,822 epoch 85 - iter 147/493 - loss 0.00933311 - time (sec): 10.37 - samples/sec: 7457.31 - lr: 0.025000 +2023-03-29 17:32:42,259 epoch 85 - iter 196/493 - loss 0.00915426 - time (sec): 13.81 - samples/sec: 7462.61 - lr: 0.025000 +2023-03-29 17:32:45,781 epoch 85 - iter 245/493 - loss 0.00873924 - time (sec): 17.33 - samples/sec: 7391.70 - lr: 0.025000 +2023-03-29 17:32:49,309 epoch 85 - iter 294/493 - loss 0.00852341 - time (sec): 20.86 - samples/sec: 7371.96 - lr: 0.025000 +2023-03-29 17:32:52,710 epoch 85 - iter 343/493 - loss 0.00870791 - time (sec): 24.26 - samples/sec: 7368.48 - lr: 0.025000 +2023-03-29 17:32:56,234 epoch 85 - iter 392/493 - loss 0.00879625 - time (sec): 27.78 - samples/sec: 7370.33 - lr: 0.025000 +2023-03-29 17:32:59,843 epoch 85 - iter 441/493 - loss 0.00868990 - time (sec): 31.39 - samples/sec: 7364.22 - lr: 0.025000 +2023-03-29 17:33:03,313 epoch 85 - iter 490/493 - loss 0.00839087 - time (sec): 34.86 - samples/sec: 7388.63 - lr: 0.025000 +2023-03-29 17:33:03,515 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:33:03,515 EPOCH 85 done: loss 0.0084 - lr 0.025000 +2023-03-29 17:33:03,515 BAD EPOCHS (no improvement): 2 +2023-03-29 17:33:03,518 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:33:07,132 epoch 86 - iter 49/493 - loss 0.00743107 - time (sec): 3.61 - samples/sec: 7513.78 - lr: 0.025000 +2023-03-29 17:33:10,538 epoch 86 - iter 98/493 - loss 0.00884617 - time (sec): 7.02 - samples/sec: 7496.21 - lr: 0.025000 +2023-03-29 17:33:13,991 epoch 86 - iter 147/493 - loss 0.00891430 - time (sec): 10.47 - samples/sec: 7533.97 - lr: 0.025000 +2023-03-29 17:33:17,506 epoch 86 - iter 196/493 - loss 0.00853555 - time (sec): 13.99 - samples/sec: 7459.50 - lr: 0.025000 +2023-03-29 17:33:21,165 epoch 86 - iter 245/493 - loss 0.00839808 - time (sec): 17.65 - samples/sec: 7380.52 - lr: 0.025000 +2023-03-29 17:33:24,527 epoch 86 - iter 294/493 - loss 0.00839447 - time (sec): 21.01 - samples/sec: 7414.71 - lr: 0.025000 +2023-03-29 17:33:27,885 epoch 86 - iter 343/493 - loss 0.00837283 - time (sec): 24.37 - samples/sec: 7429.72 - lr: 0.025000 +2023-03-29 17:33:31,296 epoch 86 - iter 392/493 - loss 0.00822468 - time (sec): 27.78 - samples/sec: 7433.07 - lr: 0.025000 +2023-03-29 17:33:34,816 epoch 86 - iter 441/493 - loss 0.00846475 - time (sec): 31.30 - samples/sec: 7418.93 - lr: 0.025000 +2023-03-29 17:33:38,189 epoch 86 - iter 490/493 - loss 0.00841567 - time (sec): 34.67 - samples/sec: 7427.59 - lr: 0.025000 +2023-03-29 17:33:38,422 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:33:38,422 EPOCH 86 done: loss 0.0084 - lr 0.025000 +2023-03-29 17:33:38,423 BAD EPOCHS (no improvement): 3 +2023-03-29 17:33:38,425 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:33:41,896 epoch 87 - iter 49/493 - loss 0.00822418 - time (sec): 3.47 - samples/sec: 7274.30 - lr: 0.025000 +2023-03-29 17:33:45,457 epoch 87 - iter 98/493 - loss 0.00821659 - time (sec): 7.03 - samples/sec: 7376.07 - lr: 0.025000 +2023-03-29 17:33:49,114 epoch 87 - iter 147/493 - loss 0.00783945 - time (sec): 10.69 - samples/sec: 7315.62 - lr: 0.025000 +2023-03-29 17:33:52,550 epoch 87 - iter 196/493 - loss 0.00788863 - time (sec): 14.12 - samples/sec: 7303.96 - lr: 0.025000 +2023-03-29 17:33:55,930 epoch 87 - iter 245/493 - loss 0.00772906 - time (sec): 17.50 - samples/sec: 7371.81 - lr: 0.025000 +2023-03-29 17:33:59,572 epoch 87 - iter 294/493 - loss 0.00772945 - time (sec): 21.15 - samples/sec: 7372.27 - lr: 0.025000 +2023-03-29 17:34:02,882 epoch 87 - iter 343/493 - loss 0.00749599 - time (sec): 24.46 - samples/sec: 7414.29 - lr: 0.025000 +2023-03-29 17:34:06,200 epoch 87 - iter 392/493 - loss 0.00785828 - time (sec): 27.78 - samples/sec: 7427.03 - lr: 0.025000 +2023-03-29 17:34:09,528 epoch 87 - iter 441/493 - loss 0.00807089 - time (sec): 31.10 - samples/sec: 7451.79 - lr: 0.025000 +2023-03-29 17:34:12,858 epoch 87 - iter 490/493 - loss 0.00790619 - time (sec): 34.43 - samples/sec: 7475.50 - lr: 0.025000 +2023-03-29 17:34:13,084 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:34:13,084 EPOCH 87 done: loss 0.0079 - lr 0.025000 +2023-03-29 17:34:13,084 Epoch 87: reducing learning rate of group 0 to 1.2500e-02. +2023-03-29 17:34:13,084 BAD EPOCHS (no improvement): 4 +2023-03-29 17:34:13,090 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:34:16,475 epoch 88 - iter 49/493 - loss 0.00717920 - time (sec): 3.38 - samples/sec: 7689.05 - lr: 0.012500 +2023-03-29 17:34:19,796 epoch 88 - iter 98/493 - loss 0.00781184 - time (sec): 6.70 - samples/sec: 7717.25 - lr: 0.012500 +2023-03-29 17:34:23,165 epoch 88 - iter 147/493 - loss 0.00803943 - time (sec): 10.07 - samples/sec: 7681.66 - lr: 0.012500 +2023-03-29 17:34:26,634 epoch 88 - iter 196/493 - loss 0.00794215 - time (sec): 13.54 - samples/sec: 7614.91 - lr: 0.012500 +2023-03-29 17:34:29,961 epoch 88 - iter 245/493 - loss 0.00814575 - time (sec): 16.87 - samples/sec: 7624.74 - lr: 0.012500 +2023-03-29 17:34:33,218 epoch 88 - iter 294/493 - loss 0.00772997 - time (sec): 20.13 - samples/sec: 7654.91 - lr: 0.012500 +2023-03-29 17:34:36,569 epoch 88 - iter 343/493 - loss 0.00787626 - time (sec): 23.48 - samples/sec: 7660.19 - lr: 0.012500 +2023-03-29 17:34:39,956 epoch 88 - iter 392/493 - loss 0.00776030 - time (sec): 26.87 - samples/sec: 7651.91 - lr: 0.012500 +2023-03-29 17:34:43,461 epoch 88 - iter 441/493 - loss 0.00782617 - time (sec): 30.37 - samples/sec: 7614.89 - lr: 0.012500 +2023-03-29 17:34:46,957 epoch 88 - iter 490/493 - loss 0.00787161 - time (sec): 33.87 - samples/sec: 7602.74 - lr: 0.012500 +2023-03-29 17:34:47,166 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:34:47,166 EPOCH 88 done: loss 0.0079 - lr 0.012500 +2023-03-29 17:34:47,166 BAD EPOCHS (no improvement): 1 +2023-03-29 17:34:47,169 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:34:50,428 epoch 89 - iter 49/493 - loss 0.00688935 - time (sec): 3.26 - samples/sec: 7831.22 - lr: 0.012500 +2023-03-29 17:34:53,895 epoch 89 - iter 98/493 - loss 0.00681574 - time (sec): 6.73 - samples/sec: 7615.01 - lr: 0.012500 +2023-03-29 17:34:57,293 epoch 89 - iter 147/493 - loss 0.00701717 - time (sec): 10.12 - samples/sec: 7604.71 - lr: 0.012500 +2023-03-29 17:35:00,545 epoch 89 - iter 196/493 - loss 0.00719824 - time (sec): 13.38 - samples/sec: 7656.21 - lr: 0.012500 +2023-03-29 17:35:04,063 epoch 89 - iter 245/493 - loss 0.00718949 - time (sec): 16.89 - samples/sec: 7606.75 - lr: 0.012500 +2023-03-29 17:35:07,423 epoch 89 - iter 294/493 - loss 0.00732995 - time (sec): 20.25 - samples/sec: 7635.07 - lr: 0.012500 +2023-03-29 17:35:10,960 epoch 89 - iter 343/493 - loss 0.00750596 - time (sec): 23.79 - samples/sec: 7589.27 - lr: 0.012500 +2023-03-29 17:35:14,267 epoch 89 - iter 392/493 - loss 0.00764029 - time (sec): 27.10 - samples/sec: 7592.73 - lr: 0.012500 +2023-03-29 17:35:17,512 epoch 89 - iter 441/493 - loss 0.00756291 - time (sec): 30.34 - samples/sec: 7621.12 - lr: 0.012500 +2023-03-29 17:35:21,031 epoch 89 - iter 490/493 - loss 0.00762677 - time (sec): 33.86 - samples/sec: 7599.67 - lr: 0.012500 +2023-03-29 17:35:21,268 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:35:21,268 EPOCH 89 done: loss 0.0077 - lr 0.012500 +2023-03-29 17:35:21,268 BAD EPOCHS (no improvement): 0 +2023-03-29 17:35:21,271 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:35:24,740 epoch 90 - iter 49/493 - loss 0.00774234 - time (sec): 3.47 - samples/sec: 7417.02 - lr: 0.012500 +2023-03-29 17:35:28,111 epoch 90 - iter 98/493 - loss 0.00727610 - time (sec): 6.84 - samples/sec: 7453.36 - lr: 0.012500 +2023-03-29 17:35:31,568 epoch 90 - iter 147/493 - loss 0.00725228 - time (sec): 10.30 - samples/sec: 7539.86 - lr: 0.012500 +2023-03-29 17:35:34,926 epoch 90 - iter 196/493 - loss 0.00755444 - time (sec): 13.66 - samples/sec: 7567.09 - lr: 0.012500 +2023-03-29 17:35:38,230 epoch 90 - iter 245/493 - loss 0.00749687 - time (sec): 16.96 - samples/sec: 7602.55 - lr: 0.012500 +2023-03-29 17:35:41,589 epoch 90 - iter 294/493 - loss 0.00755391 - time (sec): 20.32 - samples/sec: 7609.74 - lr: 0.012500 +2023-03-29 17:35:44,967 epoch 90 - iter 343/493 - loss 0.00738970 - time (sec): 23.70 - samples/sec: 7610.29 - lr: 0.012500 +2023-03-29 17:35:48,479 epoch 90 - iter 392/493 - loss 0.00733041 - time (sec): 27.21 - samples/sec: 7596.38 - lr: 0.012500 +2023-03-29 17:35:51,896 epoch 90 - iter 441/493 - loss 0.00743191 - time (sec): 30.62 - samples/sec: 7581.72 - lr: 0.012500 +2023-03-29 17:35:55,233 epoch 90 - iter 490/493 - loss 0.00752115 - time (sec): 33.96 - samples/sec: 7583.58 - lr: 0.012500 +2023-03-29 17:35:55,432 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:35:55,433 EPOCH 90 done: loss 0.0075 - lr 0.012500 +2023-03-29 17:35:55,433 BAD EPOCHS (no improvement): 0 +2023-03-29 17:35:55,436 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:35:59,068 epoch 91 - iter 49/493 - loss 0.00747239 - time (sec): 3.63 - samples/sec: 7191.34 - lr: 0.012500 +2023-03-29 17:36:02,542 epoch 91 - iter 98/493 - loss 0.00753983 - time (sec): 7.11 - samples/sec: 7309.90 - lr: 0.012500 +2023-03-29 17:36:05,998 epoch 91 - iter 147/493 - loss 0.00735989 - time (sec): 10.56 - samples/sec: 7355.56 - lr: 0.012500 +2023-03-29 17:36:09,424 epoch 91 - iter 196/493 - loss 0.00738180 - time (sec): 13.99 - samples/sec: 7389.14 - lr: 0.012500 +2023-03-29 17:36:12,933 epoch 91 - iter 245/493 - loss 0.00760846 - time (sec): 17.50 - samples/sec: 7409.76 - lr: 0.012500 +2023-03-29 17:36:16,423 epoch 91 - iter 294/493 - loss 0.00762934 - time (sec): 20.99 - samples/sec: 7415.50 - lr: 0.012500 +2023-03-29 17:36:19,828 epoch 91 - iter 343/493 - loss 0.00748198 - time (sec): 24.39 - samples/sec: 7423.25 - lr: 0.012500 +2023-03-29 17:36:23,222 epoch 91 - iter 392/493 - loss 0.00756791 - time (sec): 27.79 - samples/sec: 7445.41 - lr: 0.012500 +2023-03-29 17:36:26,662 epoch 91 - iter 441/493 - loss 0.00773975 - time (sec): 31.23 - samples/sec: 7441.74 - lr: 0.012500 +2023-03-29 17:36:30,062 epoch 91 - iter 490/493 - loss 0.00756086 - time (sec): 34.63 - samples/sec: 7443.45 - lr: 0.012500 +2023-03-29 17:36:30,250 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:36:30,250 EPOCH 91 done: loss 0.0076 - lr 0.012500 +2023-03-29 17:36:30,250 BAD EPOCHS (no improvement): 1 +2023-03-29 17:36:30,254 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:36:33,754 epoch 92 - iter 49/493 - loss 0.00778161 - time (sec): 3.50 - samples/sec: 7409.61 - lr: 0.012500 +2023-03-29 17:36:37,234 epoch 92 - iter 98/493 - loss 0.00729927 - time (sec): 6.98 - samples/sec: 7361.59 - lr: 0.012500 +2023-03-29 17:36:40,720 epoch 92 - iter 147/493 - loss 0.00701721 - time (sec): 10.47 - samples/sec: 7352.86 - lr: 0.012500 +2023-03-29 17:36:44,333 epoch 92 - iter 196/493 - loss 0.00720800 - time (sec): 14.08 - samples/sec: 7300.57 - lr: 0.012500 +2023-03-29 17:36:47,871 epoch 92 - iter 245/493 - loss 0.00683350 - time (sec): 17.62 - samples/sec: 7318.69 - lr: 0.012500 +2023-03-29 17:36:51,272 epoch 92 - iter 294/493 - loss 0.00692472 - time (sec): 21.02 - samples/sec: 7326.94 - lr: 0.012500 +2023-03-29 17:36:54,894 epoch 92 - iter 343/493 - loss 0.00686000 - time (sec): 24.64 - samples/sec: 7323.88 - lr: 0.012500 +2023-03-29 17:36:58,339 epoch 92 - iter 392/493 - loss 0.00686942 - time (sec): 28.09 - samples/sec: 7353.28 - lr: 0.012500 +2023-03-29 17:37:01,813 epoch 92 - iter 441/493 - loss 0.00694407 - time (sec): 31.56 - samples/sec: 7365.29 - lr: 0.012500 +2023-03-29 17:37:05,262 epoch 92 - iter 490/493 - loss 0.00699090 - time (sec): 35.01 - samples/sec: 7364.37 - lr: 0.012500 +2023-03-29 17:37:05,432 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:37:05,432 EPOCH 92 done: loss 0.0070 - lr 0.012500 +2023-03-29 17:37:05,432 BAD EPOCHS (no improvement): 0 +2023-03-29 17:37:05,435 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:37:09,032 epoch 93 - iter 49/493 - loss 0.00755886 - time (sec): 3.60 - samples/sec: 7279.21 - lr: 0.012500 +2023-03-29 17:37:12,458 epoch 93 - iter 98/493 - loss 0.00737342 - time (sec): 7.02 - samples/sec: 7416.34 - lr: 0.012500 +2023-03-29 17:37:15,866 epoch 93 - iter 147/493 - loss 0.00675790 - time (sec): 10.43 - samples/sec: 7428.82 - lr: 0.012500 +2023-03-29 17:37:19,283 epoch 93 - iter 196/493 - loss 0.00696906 - time (sec): 13.85 - samples/sec: 7442.13 - lr: 0.012500 +2023-03-29 17:37:22,760 epoch 93 - iter 245/493 - loss 0.00702522 - time (sec): 17.33 - samples/sec: 7443.06 - lr: 0.012500 +2023-03-29 17:37:26,319 epoch 93 - iter 294/493 - loss 0.00717816 - time (sec): 20.88 - samples/sec: 7392.16 - lr: 0.012500 +2023-03-29 17:37:29,840 epoch 93 - iter 343/493 - loss 0.00700690 - time (sec): 24.41 - samples/sec: 7389.55 - lr: 0.012500 +2023-03-29 17:37:33,300 epoch 93 - iter 392/493 - loss 0.00705466 - time (sec): 27.86 - samples/sec: 7397.06 - lr: 0.012500 +2023-03-29 17:37:36,925 epoch 93 - iter 441/493 - loss 0.00706977 - time (sec): 31.49 - samples/sec: 7361.43 - lr: 0.012500 +2023-03-29 17:37:40,550 epoch 93 - iter 490/493 - loss 0.00711711 - time (sec): 35.11 - samples/sec: 7339.96 - lr: 0.012500 +2023-03-29 17:37:40,748 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:37:40,748 EPOCH 93 done: loss 0.0071 - lr 0.012500 +2023-03-29 17:37:40,748 BAD EPOCHS (no improvement): 1 +2023-03-29 17:37:40,751 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:37:44,500 epoch 94 - iter 49/493 - loss 0.00637227 - time (sec): 3.75 - samples/sec: 7038.20 - lr: 0.012500 +2023-03-29 17:37:47,898 epoch 94 - iter 98/493 - loss 0.00691832 - time (sec): 7.15 - samples/sec: 7224.41 - lr: 0.012500 +2023-03-29 17:37:51,490 epoch 94 - iter 147/493 - loss 0.00703549 - time (sec): 10.74 - samples/sec: 7287.98 - lr: 0.012500 +2023-03-29 17:37:54,995 epoch 94 - iter 196/493 - loss 0.00698354 - time (sec): 14.24 - samples/sec: 7337.39 - lr: 0.012500 +2023-03-29 17:37:58,298 epoch 94 - iter 245/493 - loss 0.00693494 - time (sec): 17.55 - samples/sec: 7382.33 - lr: 0.012500 +2023-03-29 17:38:01,639 epoch 94 - iter 294/493 - loss 0.00696120 - time (sec): 20.89 - samples/sec: 7421.69 - lr: 0.012500 +2023-03-29 17:38:05,159 epoch 94 - iter 343/493 - loss 0.00712158 - time (sec): 24.41 - samples/sec: 7419.47 - lr: 0.012500 +2023-03-29 17:38:08,564 epoch 94 - iter 392/493 - loss 0.00712961 - time (sec): 27.81 - samples/sec: 7438.78 - lr: 0.012500 +2023-03-29 17:38:11,886 epoch 94 - iter 441/493 - loss 0.00733870 - time (sec): 31.13 - samples/sec: 7460.17 - lr: 0.012500 +2023-03-29 17:38:15,313 epoch 94 - iter 490/493 - loss 0.00732635 - time (sec): 34.56 - samples/sec: 7454.42 - lr: 0.012500 +2023-03-29 17:38:15,515 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:38:15,515 EPOCH 94 done: loss 0.0073 - lr 0.012500 +2023-03-29 17:38:15,515 BAD EPOCHS (no improvement): 2 +2023-03-29 17:38:15,518 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:38:18,890 epoch 95 - iter 49/493 - loss 0.00643454 - time (sec): 3.37 - samples/sec: 7805.73 - lr: 0.012500 +2023-03-29 17:38:22,315 epoch 95 - iter 98/493 - loss 0.00585888 - time (sec): 6.80 - samples/sec: 7631.48 - lr: 0.012500 +2023-03-29 17:38:25,733 epoch 95 - iter 147/493 - loss 0.00632071 - time (sec): 10.21 - samples/sec: 7586.67 - lr: 0.012500 +2023-03-29 17:38:29,105 epoch 95 - iter 196/493 - loss 0.00626598 - time (sec): 13.59 - samples/sec: 7593.42 - lr: 0.012500 +2023-03-29 17:38:32,614 epoch 95 - iter 245/493 - loss 0.00616908 - time (sec): 17.10 - samples/sec: 7550.33 - lr: 0.012500 +2023-03-29 17:38:35,903 epoch 95 - iter 294/493 - loss 0.00641856 - time (sec): 20.38 - samples/sec: 7574.88 - lr: 0.012500 +2023-03-29 17:38:39,322 epoch 95 - iter 343/493 - loss 0.00646827 - time (sec): 23.80 - samples/sec: 7567.71 - lr: 0.012500 +2023-03-29 17:38:42,675 epoch 95 - iter 392/493 - loss 0.00657234 - time (sec): 27.16 - samples/sec: 7579.78 - lr: 0.012500 +2023-03-29 17:38:46,017 epoch 95 - iter 441/493 - loss 0.00679228 - time (sec): 30.50 - samples/sec: 7591.70 - lr: 0.012500 +2023-03-29 17:38:49,406 epoch 95 - iter 490/493 - loss 0.00655373 - time (sec): 33.89 - samples/sec: 7605.25 - lr: 0.012500 +2023-03-29 17:38:49,613 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:38:49,613 EPOCH 95 done: loss 0.0065 - lr 0.012500 +2023-03-29 17:38:49,613 BAD EPOCHS (no improvement): 0 +2023-03-29 17:38:49,616 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:38:52,972 epoch 96 - iter 49/493 - loss 0.00591867 - time (sec): 3.36 - samples/sec: 7797.66 - lr: 0.012500 +2023-03-29 17:38:56,413 epoch 96 - iter 98/493 - loss 0.00642648 - time (sec): 6.80 - samples/sec: 7694.51 - lr: 0.012500 +2023-03-29 17:38:59,923 epoch 96 - iter 147/493 - loss 0.00631591 - time (sec): 10.31 - samples/sec: 7549.90 - lr: 0.012500 +2023-03-29 17:39:03,391 epoch 96 - iter 196/493 - loss 0.00636280 - time (sec): 13.78 - samples/sec: 7544.03 - lr: 0.012500 +2023-03-29 17:39:06,799 epoch 96 - iter 245/493 - loss 0.00663686 - time (sec): 17.18 - samples/sec: 7565.57 - lr: 0.012500 +2023-03-29 17:39:10,104 epoch 96 - iter 294/493 - loss 0.00669715 - time (sec): 20.49 - samples/sec: 7582.58 - lr: 0.012500 +2023-03-29 17:39:13,616 epoch 96 - iter 343/493 - loss 0.00671731 - time (sec): 24.00 - samples/sec: 7518.54 - lr: 0.012500 +2023-03-29 17:39:19,911 epoch 96 - iter 392/493 - loss 0.00686078 - time (sec): 30.30 - samples/sec: 6804.79 - lr: 0.012500 +2023-03-29 17:39:23,222 epoch 96 - iter 441/493 - loss 0.00683092 - time (sec): 33.61 - samples/sec: 6895.97 - lr: 0.012500 +2023-03-29 17:39:26,674 epoch 96 - iter 490/493 - loss 0.00672148 - time (sec): 37.06 - samples/sec: 6949.59 - lr: 0.012500 +2023-03-29 17:39:26,870 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:39:26,870 EPOCH 96 done: loss 0.0067 - lr 0.012500 +2023-03-29 17:39:26,870 BAD EPOCHS (no improvement): 1 +2023-03-29 17:39:26,873 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:39:30,409 epoch 97 - iter 49/493 - loss 0.00732336 - time (sec): 3.54 - samples/sec: 7387.14 - lr: 0.012500 +2023-03-29 17:39:33,791 epoch 97 - iter 98/493 - loss 0.00626166 - time (sec): 6.92 - samples/sec: 7451.67 - lr: 0.012500 +2023-03-29 17:39:37,128 epoch 97 - iter 147/493 - loss 0.00669875 - time (sec): 10.26 - samples/sec: 7522.30 - lr: 0.012500 +2023-03-29 17:39:40,480 epoch 97 - iter 196/493 - loss 0.00652041 - time (sec): 13.61 - samples/sec: 7525.05 - lr: 0.012500 +2023-03-29 17:39:43,787 epoch 97 - iter 245/493 - loss 0.00648784 - time (sec): 16.91 - samples/sec: 7566.76 - lr: 0.012500 +2023-03-29 17:39:47,356 epoch 97 - iter 294/493 - loss 0.00683404 - time (sec): 20.48 - samples/sec: 7535.02 - lr: 0.012500 +2023-03-29 17:39:50,780 epoch 97 - iter 343/493 - loss 0.00680856 - time (sec): 23.91 - samples/sec: 7535.76 - lr: 0.012500 +2023-03-29 17:39:54,114 epoch 97 - iter 392/493 - loss 0.00681470 - time (sec): 27.24 - samples/sec: 7536.12 - lr: 0.012500 +2023-03-29 17:39:57,598 epoch 97 - iter 441/493 - loss 0.00685807 - time (sec): 30.73 - samples/sec: 7529.57 - lr: 0.012500 +2023-03-29 17:40:00,966 epoch 97 - iter 490/493 - loss 0.00684843 - time (sec): 34.09 - samples/sec: 7557.47 - lr: 0.012500 +2023-03-29 17:40:01,159 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:40:01,159 EPOCH 97 done: loss 0.0068 - lr 0.012500 +2023-03-29 17:40:01,159 BAD EPOCHS (no improvement): 2 +2023-03-29 17:40:01,162 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:40:04,588 epoch 98 - iter 49/493 - loss 0.00736130 - time (sec): 3.43 - samples/sec: 7580.80 - lr: 0.012500 +2023-03-29 17:40:08,102 epoch 98 - iter 98/493 - loss 0.00625809 - time (sec): 6.94 - samples/sec: 7532.20 - lr: 0.012500 +2023-03-29 17:40:11,482 epoch 98 - iter 147/493 - loss 0.00647096 - time (sec): 10.32 - samples/sec: 7605.97 - lr: 0.012500 +2023-03-29 17:40:14,763 epoch 98 - iter 196/493 - loss 0.00628648 - time (sec): 13.60 - samples/sec: 7601.24 - lr: 0.012500 +2023-03-29 17:40:18,086 epoch 98 - iter 245/493 - loss 0.00633511 - time (sec): 16.92 - samples/sec: 7593.51 - lr: 0.012500 +2023-03-29 17:40:21,649 epoch 98 - iter 294/493 - loss 0.00634420 - time (sec): 20.49 - samples/sec: 7568.09 - lr: 0.012500 +2023-03-29 17:40:24,971 epoch 98 - iter 343/493 - loss 0.00642238 - time (sec): 23.81 - samples/sec: 7601.82 - lr: 0.012500 +2023-03-29 17:40:28,428 epoch 98 - iter 392/493 - loss 0.00632552 - time (sec): 27.27 - samples/sec: 7563.43 - lr: 0.012500 +2023-03-29 17:40:31,709 epoch 98 - iter 441/493 - loss 0.00655439 - time (sec): 30.55 - samples/sec: 7577.74 - lr: 0.012500 +2023-03-29 17:40:35,101 epoch 98 - iter 490/493 - loss 0.00670011 - time (sec): 33.94 - samples/sec: 7585.75 - lr: 0.012500 +2023-03-29 17:40:35,327 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:40:35,327 EPOCH 98 done: loss 0.0067 - lr 0.012500 +2023-03-29 17:40:35,327 BAD EPOCHS (no improvement): 3 +2023-03-29 17:40:35,330 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:40:38,615 epoch 99 - iter 49/493 - loss 0.00763632 - time (sec): 3.28 - samples/sec: 7642.33 - lr: 0.012500 +2023-03-29 17:40:42,080 epoch 99 - iter 98/493 - loss 0.00661340 - time (sec): 6.75 - samples/sec: 7513.07 - lr: 0.012500 +2023-03-29 17:40:45,702 epoch 99 - iter 147/493 - loss 0.00703313 - time (sec): 10.37 - samples/sec: 7395.55 - lr: 0.012500 +2023-03-29 17:40:49,403 epoch 99 - iter 196/493 - loss 0.00703327 - time (sec): 14.07 - samples/sec: 7293.92 - lr: 0.012500 +2023-03-29 17:40:52,885 epoch 99 - iter 245/493 - loss 0.00735015 - time (sec): 17.55 - samples/sec: 7306.54 - lr: 0.012500 +2023-03-29 17:40:56,423 epoch 99 - iter 294/493 - loss 0.00725869 - time (sec): 21.09 - samples/sec: 7344.87 - lr: 0.012500 +2023-03-29 17:40:59,998 epoch 99 - iter 343/493 - loss 0.00718158 - time (sec): 24.67 - samples/sec: 7329.30 - lr: 0.012500 +2023-03-29 17:41:03,467 epoch 99 - iter 392/493 - loss 0.00709454 - time (sec): 28.14 - samples/sec: 7342.38 - lr: 0.012500 +2023-03-29 17:41:06,937 epoch 99 - iter 441/493 - loss 0.00705312 - time (sec): 31.61 - samples/sec: 7337.12 - lr: 0.012500 +2023-03-29 17:41:10,338 epoch 99 - iter 490/493 - loss 0.00702137 - time (sec): 35.01 - samples/sec: 7356.27 - lr: 0.012500 +2023-03-29 17:41:10,543 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:41:10,543 EPOCH 99 done: loss 0.0070 - lr 0.012500 +2023-03-29 17:41:10,543 Epoch 99: reducing learning rate of group 0 to 6.2500e-03. +2023-03-29 17:41:10,543 BAD EPOCHS (no improvement): 4 +2023-03-29 17:41:10,546 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:41:13,927 epoch 100 - iter 49/493 - loss 0.00781292 - time (sec): 3.38 - samples/sec: 7607.63 - lr: 0.006250 +2023-03-29 17:41:17,251 epoch 100 - iter 98/493 - loss 0.00777990 - time (sec): 6.70 - samples/sec: 7608.20 - lr: 0.006250 +2023-03-29 17:41:20,575 epoch 100 - iter 147/493 - loss 0.00752571 - time (sec): 10.03 - samples/sec: 7707.53 - lr: 0.006250 +2023-03-29 17:41:24,078 epoch 100 - iter 196/493 - loss 0.00775018 - time (sec): 13.53 - samples/sec: 7643.09 - lr: 0.006250 +2023-03-29 17:41:27,397 epoch 100 - iter 245/493 - loss 0.00773860 - time (sec): 16.85 - samples/sec: 7627.85 - lr: 0.006250 +2023-03-29 17:41:30,892 epoch 100 - iter 294/493 - loss 0.00752868 - time (sec): 20.35 - samples/sec: 7599.70 - lr: 0.006250 +2023-03-29 17:41:34,240 epoch 100 - iter 343/493 - loss 0.00736977 - time (sec): 23.69 - samples/sec: 7613.83 - lr: 0.006250 +2023-03-29 17:41:37,594 epoch 100 - iter 392/493 - loss 0.00737501 - time (sec): 27.05 - samples/sec: 7608.49 - lr: 0.006250 +2023-03-29 17:41:40,951 epoch 100 - iter 441/493 - loss 0.00748740 - time (sec): 30.41 - samples/sec: 7617.68 - lr: 0.006250 +2023-03-29 17:41:44,542 epoch 100 - iter 490/493 - loss 0.00726519 - time (sec): 34.00 - samples/sec: 7577.19 - lr: 0.006250 +2023-03-29 17:41:44,738 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:41:44,738 EPOCH 100 done: loss 0.0072 - lr 0.006250 +2023-03-29 17:41:44,738 BAD EPOCHS (no improvement): 1 +2023-03-29 17:41:44,741 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:41:48,117 epoch 101 - iter 49/493 - loss 0.00679042 - time (sec): 3.38 - samples/sec: 7505.27 - lr: 0.006250 +2023-03-29 17:41:51,564 epoch 101 - iter 98/493 - loss 0.00668759 - time (sec): 6.82 - samples/sec: 7456.05 - lr: 0.006250 +2023-03-29 17:41:54,839 epoch 101 - iter 147/493 - loss 0.00682418 - time (sec): 10.10 - samples/sec: 7551.41 - lr: 0.006250 +2023-03-29 17:41:58,130 epoch 101 - iter 196/493 - loss 0.00665905 - time (sec): 13.39 - samples/sec: 7590.33 - lr: 0.006250 +2023-03-29 17:42:01,523 epoch 101 - iter 245/493 - loss 0.00699336 - time (sec): 16.78 - samples/sec: 7592.93 - lr: 0.006250 +2023-03-29 17:42:04,963 epoch 101 - iter 294/493 - loss 0.00727522 - time (sec): 20.22 - samples/sec: 7561.06 - lr: 0.006250 +2023-03-29 17:42:08,654 epoch 101 - iter 343/493 - loss 0.00720216 - time (sec): 23.91 - samples/sec: 7520.32 - lr: 0.006250 +2023-03-29 17:42:12,046 epoch 101 - iter 392/493 - loss 0.00722994 - time (sec): 27.31 - samples/sec: 7532.23 - lr: 0.006250 +2023-03-29 17:42:15,428 epoch 101 - iter 441/493 - loss 0.00715049 - time (sec): 30.69 - samples/sec: 7540.97 - lr: 0.006250 +2023-03-29 17:42:18,860 epoch 101 - iter 490/493 - loss 0.00703315 - time (sec): 34.12 - samples/sec: 7550.95 - lr: 0.006250 +2023-03-29 17:42:19,064 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:42:19,064 EPOCH 101 done: loss 0.0070 - lr 0.006250 +2023-03-29 17:42:19,064 BAD EPOCHS (no improvement): 2 +2023-03-29 17:42:19,067 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:42:22,621 epoch 102 - iter 49/493 - loss 0.00564790 - time (sec): 3.55 - samples/sec: 7258.22 - lr: 0.006250 +2023-03-29 17:42:26,096 epoch 102 - iter 98/493 - loss 0.00634264 - time (sec): 7.03 - samples/sec: 7367.86 - lr: 0.006250 +2023-03-29 17:42:29,523 epoch 102 - iter 147/493 - loss 0.00656381 - time (sec): 10.46 - samples/sec: 7406.53 - lr: 0.006250 +2023-03-29 17:42:32,891 epoch 102 - iter 196/493 - loss 0.00663508 - time (sec): 13.82 - samples/sec: 7467.36 - lr: 0.006250 +2023-03-29 17:42:36,296 epoch 102 - iter 245/493 - loss 0.00681001 - time (sec): 17.23 - samples/sec: 7486.78 - lr: 0.006250 +2023-03-29 17:42:39,679 epoch 102 - iter 294/493 - loss 0.00688534 - time (sec): 20.61 - samples/sec: 7488.36 - lr: 0.006250 +2023-03-29 17:42:43,074 epoch 102 - iter 343/493 - loss 0.00688321 - time (sec): 24.01 - samples/sec: 7517.16 - lr: 0.006250 +2023-03-29 17:42:46,504 epoch 102 - iter 392/493 - loss 0.00687005 - time (sec): 27.44 - samples/sec: 7526.23 - lr: 0.006250 +2023-03-29 17:42:49,861 epoch 102 - iter 441/493 - loss 0.00684483 - time (sec): 30.79 - samples/sec: 7550.09 - lr: 0.006250 +2023-03-29 17:42:53,137 epoch 102 - iter 490/493 - loss 0.00687019 - time (sec): 34.07 - samples/sec: 7562.41 - lr: 0.006250 +2023-03-29 17:42:53,336 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:42:53,336 EPOCH 102 done: loss 0.0069 - lr 0.006250 +2023-03-29 17:42:53,336 BAD EPOCHS (no improvement): 3 +2023-03-29 17:42:53,339 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:42:56,817 epoch 103 - iter 49/493 - loss 0.00625346 - time (sec): 3.48 - samples/sec: 7386.06 - lr: 0.006250 +2023-03-29 17:43:00,238 epoch 103 - iter 98/493 - loss 0.00672863 - time (sec): 6.90 - samples/sec: 7507.57 - lr: 0.006250 +2023-03-29 17:43:03,653 epoch 103 - iter 147/493 - loss 0.00688897 - time (sec): 10.31 - samples/sec: 7559.68 - lr: 0.006250 +2023-03-29 17:43:07,032 epoch 103 - iter 196/493 - loss 0.00645936 - time (sec): 13.69 - samples/sec: 7584.93 - lr: 0.006250 +2023-03-29 17:43:10,430 epoch 103 - iter 245/493 - loss 0.00644862 - time (sec): 17.09 - samples/sec: 7590.17 - lr: 0.006250 +2023-03-29 17:43:13,817 epoch 103 - iter 294/493 - loss 0.00656614 - time (sec): 20.48 - samples/sec: 7574.17 - lr: 0.006250 +2023-03-29 17:43:17,296 epoch 103 - iter 343/493 - loss 0.00661927 - time (sec): 23.96 - samples/sec: 7535.85 - lr: 0.006250 +2023-03-29 17:43:20,637 epoch 103 - iter 392/493 - loss 0.00652321 - time (sec): 27.30 - samples/sec: 7568.08 - lr: 0.006250 +2023-03-29 17:43:24,021 epoch 103 - iter 441/493 - loss 0.00646239 - time (sec): 30.68 - samples/sec: 7572.40 - lr: 0.006250 +2023-03-29 17:43:27,432 epoch 103 - iter 490/493 - loss 0.00645975 - time (sec): 34.09 - samples/sec: 7558.57 - lr: 0.006250 +2023-03-29 17:43:27,637 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:43:27,637 EPOCH 103 done: loss 0.0065 - lr 0.006250 +2023-03-29 17:43:27,637 BAD EPOCHS (no improvement): 0 +2023-03-29 17:43:27,656 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:43:31,159 epoch 104 - iter 49/493 - loss 0.00688949 - time (sec): 3.50 - samples/sec: 7648.84 - lr: 0.006250 +2023-03-29 17:43:34,477 epoch 104 - iter 98/493 - loss 0.00658225 - time (sec): 6.82 - samples/sec: 7678.01 - lr: 0.006250 +2023-03-29 17:43:37,926 epoch 104 - iter 147/493 - loss 0.00654253 - time (sec): 10.27 - samples/sec: 7611.14 - lr: 0.006250 +2023-03-29 17:43:41,239 epoch 104 - iter 196/493 - loss 0.00637756 - time (sec): 13.58 - samples/sec: 7662.54 - lr: 0.006250 +2023-03-29 17:43:44,755 epoch 104 - iter 245/493 - loss 0.00617179 - time (sec): 17.10 - samples/sec: 7625.36 - lr: 0.006250 +2023-03-29 17:43:48,133 epoch 104 - iter 294/493 - loss 0.00634876 - time (sec): 20.48 - samples/sec: 7622.77 - lr: 0.006250 +2023-03-29 17:43:51,441 epoch 104 - iter 343/493 - loss 0.00645310 - time (sec): 23.78 - samples/sec: 7605.03 - lr: 0.006250 +2023-03-29 17:43:55,032 epoch 104 - iter 392/493 - loss 0.00649483 - time (sec): 27.38 - samples/sec: 7568.48 - lr: 0.006250 +2023-03-29 17:43:58,369 epoch 104 - iter 441/493 - loss 0.00658586 - time (sec): 30.71 - samples/sec: 7568.96 - lr: 0.006250 +2023-03-29 17:44:01,866 epoch 104 - iter 490/493 - loss 0.00669526 - time (sec): 34.21 - samples/sec: 7530.22 - lr: 0.006250 +2023-03-29 17:44:02,051 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:44:02,051 EPOCH 104 done: loss 0.0067 - lr 0.006250 +2023-03-29 17:44:02,051 BAD EPOCHS (no improvement): 1 +2023-03-29 17:44:02,054 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:44:05,424 epoch 105 - iter 49/493 - loss 0.00696216 - time (sec): 3.37 - samples/sec: 7654.03 - lr: 0.006250 +2023-03-29 17:44:09,056 epoch 105 - iter 98/493 - loss 0.00709603 - time (sec): 7.00 - samples/sec: 7450.78 - lr: 0.006250 +2023-03-29 17:44:12,620 epoch 105 - iter 147/493 - loss 0.00660560 - time (sec): 10.57 - samples/sec: 7405.96 - lr: 0.006250 +2023-03-29 17:44:16,055 epoch 105 - iter 196/493 - loss 0.00611341 - time (sec): 14.00 - samples/sec: 7409.07 - lr: 0.006250 +2023-03-29 17:44:19,462 epoch 105 - iter 245/493 - loss 0.00586705 - time (sec): 17.41 - samples/sec: 7469.39 - lr: 0.006250 +2023-03-29 17:44:22,753 epoch 105 - iter 294/493 - loss 0.00594734 - time (sec): 20.70 - samples/sec: 7496.14 - lr: 0.006250 +2023-03-29 17:44:26,096 epoch 105 - iter 343/493 - loss 0.00600638 - time (sec): 24.04 - samples/sec: 7519.25 - lr: 0.006250 +2023-03-29 17:44:29,429 epoch 105 - iter 392/493 - loss 0.00596648 - time (sec): 27.37 - samples/sec: 7520.20 - lr: 0.006250 +2023-03-29 17:44:32,834 epoch 105 - iter 441/493 - loss 0.00586112 - time (sec): 30.78 - samples/sec: 7534.23 - lr: 0.006250 +2023-03-29 17:44:36,246 epoch 105 - iter 490/493 - loss 0.00580261 - time (sec): 34.19 - samples/sec: 7536.27 - lr: 0.006250 +2023-03-29 17:44:36,455 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:44:36,455 EPOCH 105 done: loss 0.0058 - lr 0.006250 +2023-03-29 17:44:36,455 BAD EPOCHS (no improvement): 0 +2023-03-29 17:44:36,462 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:44:39,961 epoch 106 - iter 49/493 - loss 0.00639123 - time (sec): 3.50 - samples/sec: 7328.57 - lr: 0.006250 +2023-03-29 17:44:43,429 epoch 106 - iter 98/493 - loss 0.00581449 - time (sec): 6.97 - samples/sec: 7450.81 - lr: 0.006250 +2023-03-29 17:44:47,041 epoch 106 - iter 147/493 - loss 0.00613041 - time (sec): 10.58 - samples/sec: 7381.59 - lr: 0.006250 +2023-03-29 17:44:50,467 epoch 106 - iter 196/493 - loss 0.00628508 - time (sec): 14.01 - samples/sec: 7400.46 - lr: 0.006250 +2023-03-29 17:44:53,841 epoch 106 - iter 245/493 - loss 0.00630604 - time (sec): 17.38 - samples/sec: 7463.03 - lr: 0.006250 +2023-03-29 17:44:57,226 epoch 106 - iter 294/493 - loss 0.00642721 - time (sec): 20.76 - samples/sec: 7504.85 - lr: 0.006250 +2023-03-29 17:45:00,660 epoch 106 - iter 343/493 - loss 0.00650604 - time (sec): 24.20 - samples/sec: 7514.05 - lr: 0.006250 +2023-03-29 17:45:03,893 epoch 106 - iter 392/493 - loss 0.00668340 - time (sec): 27.43 - samples/sec: 7534.06 - lr: 0.006250 +2023-03-29 17:45:07,228 epoch 106 - iter 441/493 - loss 0.00675751 - time (sec): 30.77 - samples/sec: 7547.52 - lr: 0.006250 +2023-03-29 17:45:10,578 epoch 106 - iter 490/493 - loss 0.00669822 - time (sec): 34.12 - samples/sec: 7558.91 - lr: 0.006250 +2023-03-29 17:45:10,773 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:45:10,773 EPOCH 106 done: loss 0.0067 - lr 0.006250 +2023-03-29 17:45:10,773 BAD EPOCHS (no improvement): 1 +2023-03-29 17:45:10,776 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:45:14,139 epoch 107 - iter 49/493 - loss 0.00683930 - time (sec): 3.36 - samples/sec: 7631.58 - lr: 0.006250 +2023-03-29 17:45:17,494 epoch 107 - iter 98/493 - loss 0.00682668 - time (sec): 6.72 - samples/sec: 7693.71 - lr: 0.006250 +2023-03-29 17:45:20,828 epoch 107 - iter 147/493 - loss 0.00676924 - time (sec): 10.05 - samples/sec: 7682.21 - lr: 0.006250 +2023-03-29 17:45:24,233 epoch 107 - iter 196/493 - loss 0.00671740 - time (sec): 13.46 - samples/sec: 7635.77 - lr: 0.006250 +2023-03-29 17:45:27,820 epoch 107 - iter 245/493 - loss 0.00693082 - time (sec): 17.04 - samples/sec: 7577.00 - lr: 0.006250 +2023-03-29 17:45:31,295 epoch 107 - iter 294/493 - loss 0.00670085 - time (sec): 20.52 - samples/sec: 7548.87 - lr: 0.006250 +2023-03-29 17:45:34,614 epoch 107 - iter 343/493 - loss 0.00668710 - time (sec): 23.84 - samples/sec: 7554.80 - lr: 0.006250 +2023-03-29 17:45:38,192 epoch 107 - iter 392/493 - loss 0.00660513 - time (sec): 27.42 - samples/sec: 7530.21 - lr: 0.006250 +2023-03-29 17:45:41,677 epoch 107 - iter 441/493 - loss 0.00659416 - time (sec): 30.90 - samples/sec: 7528.22 - lr: 0.006250 +2023-03-29 17:45:44,879 epoch 107 - iter 490/493 - loss 0.00662348 - time (sec): 34.10 - samples/sec: 7555.36 - lr: 0.006250 +2023-03-29 17:45:45,080 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:45:45,080 EPOCH 107 done: loss 0.0067 - lr 0.006250 +2023-03-29 17:45:45,080 BAD EPOCHS (no improvement): 2 +2023-03-29 17:45:45,083 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:45:48,625 epoch 108 - iter 49/493 - loss 0.00551575 - time (sec): 3.54 - samples/sec: 7268.45 - lr: 0.006250 +2023-03-29 17:45:52,057 epoch 108 - iter 98/493 - loss 0.00552690 - time (sec): 6.97 - samples/sec: 7405.47 - lr: 0.006250 +2023-03-29 17:45:55,471 epoch 108 - iter 147/493 - loss 0.00592047 - time (sec): 10.39 - samples/sec: 7434.61 - lr: 0.006250 +2023-03-29 17:45:58,895 epoch 108 - iter 196/493 - loss 0.00594017 - time (sec): 13.81 - samples/sec: 7480.84 - lr: 0.006250 +2023-03-29 17:46:02,244 epoch 108 - iter 245/493 - loss 0.00604263 - time (sec): 17.16 - samples/sec: 7457.55 - lr: 0.006250 +2023-03-29 17:46:05,872 epoch 108 - iter 294/493 - loss 0.00612733 - time (sec): 20.79 - samples/sec: 7416.79 - lr: 0.006250 +2023-03-29 17:46:09,225 epoch 108 - iter 343/493 - loss 0.00608618 - time (sec): 24.14 - samples/sec: 7465.94 - lr: 0.006250 +2023-03-29 17:46:12,592 epoch 108 - iter 392/493 - loss 0.00601520 - time (sec): 27.51 - samples/sec: 7510.39 - lr: 0.006250 +2023-03-29 17:46:16,006 epoch 108 - iter 441/493 - loss 0.00618919 - time (sec): 30.92 - samples/sec: 7517.98 - lr: 0.006250 +2023-03-29 17:46:19,255 epoch 108 - iter 490/493 - loss 0.00612462 - time (sec): 34.17 - samples/sec: 7538.09 - lr: 0.006250 +2023-03-29 17:46:19,471 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:46:19,471 EPOCH 108 done: loss 0.0061 - lr 0.006250 +2023-03-29 17:46:19,471 BAD EPOCHS (no improvement): 3 +2023-03-29 17:46:19,474 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:46:22,824 epoch 109 - iter 49/493 - loss 0.00903710 - time (sec): 3.35 - samples/sec: 7635.08 - lr: 0.006250 +2023-03-29 17:46:26,242 epoch 109 - iter 98/493 - loss 0.00814505 - time (sec): 6.77 - samples/sec: 7515.80 - lr: 0.006250 +2023-03-29 17:46:29,666 epoch 109 - iter 147/493 - loss 0.00746926 - time (sec): 10.19 - samples/sec: 7508.80 - lr: 0.006250 +2023-03-29 17:46:33,062 epoch 109 - iter 196/493 - loss 0.00725585 - time (sec): 13.59 - samples/sec: 7571.22 - lr: 0.006250 +2023-03-29 17:46:36,536 epoch 109 - iter 245/493 - loss 0.00703958 - time (sec): 17.06 - samples/sec: 7558.56 - lr: 0.006250 +2023-03-29 17:46:39,840 epoch 109 - iter 294/493 - loss 0.00688267 - time (sec): 20.37 - samples/sec: 7582.88 - lr: 0.006250 +2023-03-29 17:46:43,203 epoch 109 - iter 343/493 - loss 0.00681259 - time (sec): 23.73 - samples/sec: 7590.04 - lr: 0.006250 +2023-03-29 17:46:46,658 epoch 109 - iter 392/493 - loss 0.00674094 - time (sec): 27.18 - samples/sec: 7576.79 - lr: 0.006250 +2023-03-29 17:46:49,968 epoch 109 - iter 441/493 - loss 0.00661662 - time (sec): 30.49 - samples/sec: 7592.64 - lr: 0.006250 +2023-03-29 17:46:53,484 epoch 109 - iter 490/493 - loss 0.00661883 - time (sec): 34.01 - samples/sec: 7574.34 - lr: 0.006250 +2023-03-29 17:46:53,684 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:46:53,684 EPOCH 109 done: loss 0.0066 - lr 0.006250 +2023-03-29 17:46:53,684 Epoch 109: reducing learning rate of group 0 to 3.1250e-03. +2023-03-29 17:46:53,684 BAD EPOCHS (no improvement): 4 +2023-03-29 17:46:53,686 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:46:57,129 epoch 110 - iter 49/493 - loss 0.00797808 - time (sec): 3.44 - samples/sec: 7578.80 - lr: 0.003125 +2023-03-29 17:47:00,647 epoch 110 - iter 98/493 - loss 0.00788657 - time (sec): 6.96 - samples/sec: 7490.44 - lr: 0.003125 +2023-03-29 17:47:04,036 epoch 110 - iter 147/493 - loss 0.00761853 - time (sec): 10.35 - samples/sec: 7520.12 - lr: 0.003125 +2023-03-29 17:47:07,485 epoch 110 - iter 196/493 - loss 0.00719395 - time (sec): 13.80 - samples/sec: 7469.20 - lr: 0.003125 +2023-03-29 17:47:10,802 epoch 110 - iter 245/493 - loss 0.00706682 - time (sec): 17.12 - samples/sec: 7486.76 - lr: 0.003125 +2023-03-29 17:47:14,192 epoch 110 - iter 294/493 - loss 0.00706757 - time (sec): 20.50 - samples/sec: 7515.01 - lr: 0.003125 +2023-03-29 17:47:17,627 epoch 110 - iter 343/493 - loss 0.00680669 - time (sec): 23.94 - samples/sec: 7554.11 - lr: 0.003125 +2023-03-29 17:47:20,987 epoch 110 - iter 392/493 - loss 0.00669291 - time (sec): 27.30 - samples/sec: 7566.27 - lr: 0.003125 +2023-03-29 17:47:24,443 epoch 110 - iter 441/493 - loss 0.00663679 - time (sec): 30.76 - samples/sec: 7547.51 - lr: 0.003125 +2023-03-29 17:47:27,836 epoch 110 - iter 490/493 - loss 0.00666335 - time (sec): 34.15 - samples/sec: 7540.72 - lr: 0.003125 +2023-03-29 17:47:28,047 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:47:28,047 EPOCH 110 done: loss 0.0066 - lr 0.003125 +2023-03-29 17:47:28,047 BAD EPOCHS (no improvement): 1 +2023-03-29 17:47:28,050 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:47:31,485 epoch 111 - iter 49/493 - loss 0.00607921 - time (sec): 3.43 - samples/sec: 7504.04 - lr: 0.003125 +2023-03-29 17:47:34,908 epoch 111 - iter 98/493 - loss 0.00554559 - time (sec): 6.86 - samples/sec: 7510.30 - lr: 0.003125 +2023-03-29 17:47:38,226 epoch 111 - iter 147/493 - loss 0.00606643 - time (sec): 10.18 - samples/sec: 7616.09 - lr: 0.003125 +2023-03-29 17:47:41,519 epoch 111 - iter 196/493 - loss 0.00581492 - time (sec): 13.47 - samples/sec: 7650.82 - lr: 0.003125 +2023-03-29 17:47:44,811 epoch 111 - iter 245/493 - loss 0.00604291 - time (sec): 16.76 - samples/sec: 7677.78 - lr: 0.003125 +2023-03-29 17:47:48,389 epoch 111 - iter 294/493 - loss 0.00605158 - time (sec): 20.34 - samples/sec: 7612.18 - lr: 0.003125 +2023-03-29 17:47:51,867 epoch 111 - iter 343/493 - loss 0.00601472 - time (sec): 23.82 - samples/sec: 7589.31 - lr: 0.003125 +2023-03-29 17:47:55,228 epoch 111 - iter 392/493 - loss 0.00616816 - time (sec): 27.18 - samples/sec: 7569.76 - lr: 0.003125 +2023-03-29 17:47:58,691 epoch 111 - iter 441/493 - loss 0.00619059 - time (sec): 30.64 - samples/sec: 7570.77 - lr: 0.003125 +2023-03-29 17:48:02,035 epoch 111 - iter 490/493 - loss 0.00625418 - time (sec): 33.98 - samples/sec: 7585.11 - lr: 0.003125 +2023-03-29 17:48:02,211 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:48:02,211 EPOCH 111 done: loss 0.0063 - lr 0.003125 +2023-03-29 17:48:02,211 BAD EPOCHS (no improvement): 2 +2023-03-29 17:48:02,214 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:48:05,702 epoch 112 - iter 49/493 - loss 0.00570778 - time (sec): 3.49 - samples/sec: 7461.05 - lr: 0.003125 +2023-03-29 17:48:09,138 epoch 112 - iter 98/493 - loss 0.00638859 - time (sec): 6.92 - samples/sec: 7504.59 - lr: 0.003125 +2023-03-29 17:48:12,464 epoch 112 - iter 147/493 - loss 0.00623389 - time (sec): 10.25 - samples/sec: 7561.92 - lr: 0.003125 +2023-03-29 17:48:15,822 epoch 112 - iter 196/493 - loss 0.00631565 - time (sec): 13.61 - samples/sec: 7559.53 - lr: 0.003125 +2023-03-29 17:48:19,318 epoch 112 - iter 245/493 - loss 0.00637721 - time (sec): 17.10 - samples/sec: 7541.73 - lr: 0.003125 +2023-03-29 17:48:22,610 epoch 112 - iter 294/493 - loss 0.00647482 - time (sec): 20.40 - samples/sec: 7562.90 - lr: 0.003125 +2023-03-29 17:48:26,213 epoch 112 - iter 343/493 - loss 0.00629836 - time (sec): 24.00 - samples/sec: 7537.45 - lr: 0.003125 +2023-03-29 17:48:29,518 epoch 112 - iter 392/493 - loss 0.00636500 - time (sec): 27.30 - samples/sec: 7569.61 - lr: 0.003125 +2023-03-29 17:48:32,832 epoch 112 - iter 441/493 - loss 0.00630345 - time (sec): 30.62 - samples/sec: 7565.54 - lr: 0.003125 +2023-03-29 17:48:36,184 epoch 112 - iter 490/493 - loss 0.00622378 - time (sec): 33.97 - samples/sec: 7576.11 - lr: 0.003125 +2023-03-29 17:48:36,407 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:48:36,407 EPOCH 112 done: loss 0.0062 - lr 0.003125 +2023-03-29 17:48:36,407 BAD EPOCHS (no improvement): 3 +2023-03-29 17:48:36,409 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:48:39,983 epoch 113 - iter 49/493 - loss 0.00663710 - time (sec): 3.57 - samples/sec: 7271.01 - lr: 0.003125 +2023-03-29 17:48:43,368 epoch 113 - iter 98/493 - loss 0.00679455 - time (sec): 6.96 - samples/sec: 7408.44 - lr: 0.003125 +2023-03-29 17:48:46,864 epoch 113 - iter 147/493 - loss 0.00653552 - time (sec): 10.45 - samples/sec: 7411.12 - lr: 0.003125 +2023-03-29 17:48:50,278 epoch 113 - iter 196/493 - loss 0.00639593 - time (sec): 13.87 - samples/sec: 7445.78 - lr: 0.003125 +2023-03-29 17:48:53,720 epoch 113 - iter 245/493 - loss 0.00661250 - time (sec): 17.31 - samples/sec: 7425.43 - lr: 0.003125 +2023-03-29 17:48:57,394 epoch 113 - iter 294/493 - loss 0.00678804 - time (sec): 20.98 - samples/sec: 7384.44 - lr: 0.003125 +2023-03-29 17:49:00,931 epoch 113 - iter 343/493 - loss 0.00691133 - time (sec): 24.52 - samples/sec: 7365.59 - lr: 0.003125 +2023-03-29 17:49:04,345 epoch 113 - iter 392/493 - loss 0.00679528 - time (sec): 27.94 - samples/sec: 7376.35 - lr: 0.003125 +2023-03-29 17:49:07,816 epoch 113 - iter 441/493 - loss 0.00687754 - time (sec): 31.41 - samples/sec: 7380.89 - lr: 0.003125 +2023-03-29 17:49:11,464 epoch 113 - iter 490/493 - loss 0.00661288 - time (sec): 35.06 - samples/sec: 7347.13 - lr: 0.003125 +2023-03-29 17:49:11,666 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:49:11,666 EPOCH 113 done: loss 0.0066 - lr 0.003125 +2023-03-29 17:49:11,666 Epoch 113: reducing learning rate of group 0 to 1.5625e-03. +2023-03-29 17:49:11,666 BAD EPOCHS (no improvement): 4 +2023-03-29 17:49:11,669 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:49:15,144 epoch 114 - iter 49/493 - loss 0.00582178 - time (sec): 3.47 - samples/sec: 7446.87 - lr: 0.001563 +2023-03-29 17:49:18,605 epoch 114 - iter 98/493 - loss 0.00568014 - time (sec): 6.94 - samples/sec: 7419.33 - lr: 0.001563 +2023-03-29 17:49:22,077 epoch 114 - iter 147/493 - loss 0.00645996 - time (sec): 10.41 - samples/sec: 7433.19 - lr: 0.001563 +2023-03-29 17:49:25,684 epoch 114 - iter 196/493 - loss 0.00657209 - time (sec): 14.01 - samples/sec: 7330.94 - lr: 0.001563 +2023-03-29 17:49:29,159 epoch 114 - iter 245/493 - loss 0.00649124 - time (sec): 17.49 - samples/sec: 7354.09 - lr: 0.001563 +2023-03-29 17:49:32,724 epoch 114 - iter 294/493 - loss 0.00619404 - time (sec): 21.05 - samples/sec: 7348.35 - lr: 0.001563 +2023-03-29 17:49:36,268 epoch 114 - iter 343/493 - loss 0.00629866 - time (sec): 24.60 - samples/sec: 7323.60 - lr: 0.001563 +2023-03-29 17:49:39,668 epoch 114 - iter 392/493 - loss 0.00642217 - time (sec): 28.00 - samples/sec: 7353.46 - lr: 0.001563 +2023-03-29 17:49:43,217 epoch 114 - iter 441/493 - loss 0.00643458 - time (sec): 31.55 - samples/sec: 7354.00 - lr: 0.001563 +2023-03-29 17:49:46,671 epoch 114 - iter 490/493 - loss 0.00646185 - time (sec): 35.00 - samples/sec: 7360.80 - lr: 0.001563 +2023-03-29 17:49:46,871 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:49:46,872 EPOCH 114 done: loss 0.0064 - lr 0.001563 +2023-03-29 17:49:46,872 BAD EPOCHS (no improvement): 1 +2023-03-29 17:49:46,874 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:49:50,486 epoch 115 - iter 49/493 - loss 0.00507041 - time (sec): 3.61 - samples/sec: 7260.80 - lr: 0.001563 +2023-03-29 17:49:53,929 epoch 115 - iter 98/493 - loss 0.00574398 - time (sec): 7.05 - samples/sec: 7327.51 - lr: 0.001563 +2023-03-29 17:49:57,433 epoch 115 - iter 147/493 - loss 0.00604956 - time (sec): 10.56 - samples/sec: 7371.63 - lr: 0.001563 +2023-03-29 17:50:01,133 epoch 115 - iter 196/493 - loss 0.00613802 - time (sec): 14.26 - samples/sec: 7294.70 - lr: 0.001563 +2023-03-29 17:50:04,578 epoch 115 - iter 245/493 - loss 0.00621049 - time (sec): 17.70 - samples/sec: 7318.98 - lr: 0.001563 +2023-03-29 17:50:08,025 epoch 115 - iter 294/493 - loss 0.00645544 - time (sec): 21.15 - samples/sec: 7347.54 - lr: 0.001563 +2023-03-29 17:50:11,550 epoch 115 - iter 343/493 - loss 0.00667081 - time (sec): 24.68 - samples/sec: 7346.36 - lr: 0.001563 +2023-03-29 17:50:14,993 epoch 115 - iter 392/493 - loss 0.00666151 - time (sec): 28.12 - samples/sec: 7356.19 - lr: 0.001563 +2023-03-29 17:50:18,534 epoch 115 - iter 441/493 - loss 0.00665130 - time (sec): 31.66 - samples/sec: 7358.85 - lr: 0.001563 +2023-03-29 17:50:21,883 epoch 115 - iter 490/493 - loss 0.00649272 - time (sec): 35.01 - samples/sec: 7359.94 - lr: 0.001563 +2023-03-29 17:50:22,081 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:50:22,081 EPOCH 115 done: loss 0.0065 - lr 0.001563 +2023-03-29 17:50:22,081 BAD EPOCHS (no improvement): 2 +2023-03-29 17:50:22,084 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:50:25,578 epoch 116 - iter 49/493 - loss 0.00628401 - time (sec): 3.49 - samples/sec: 7506.81 - lr: 0.001563 +2023-03-29 17:50:29,035 epoch 116 - iter 98/493 - loss 0.00559306 - time (sec): 6.95 - samples/sec: 7504.01 - lr: 0.001563 +2023-03-29 17:50:32,553 epoch 116 - iter 147/493 - loss 0.00625377 - time (sec): 10.47 - samples/sec: 7452.97 - lr: 0.001563 +2023-03-29 17:50:35,882 epoch 116 - iter 196/493 - loss 0.00592304 - time (sec): 13.80 - samples/sec: 7517.16 - lr: 0.001563 +2023-03-29 17:50:39,297 epoch 116 - iter 245/493 - loss 0.00590425 - time (sec): 17.21 - samples/sec: 7523.15 - lr: 0.001563 +2023-03-29 17:50:42,685 epoch 116 - iter 294/493 - loss 0.00576106 - time (sec): 20.60 - samples/sec: 7535.89 - lr: 0.001563 +2023-03-29 17:50:46,147 epoch 116 - iter 343/493 - loss 0.00582314 - time (sec): 24.06 - samples/sec: 7493.23 - lr: 0.001563 +2023-03-29 17:50:49,452 epoch 116 - iter 392/493 - loss 0.00596749 - time (sec): 27.37 - samples/sec: 7518.31 - lr: 0.001563 +2023-03-29 17:50:52,898 epoch 116 - iter 441/493 - loss 0.00600771 - time (sec): 30.81 - samples/sec: 7511.51 - lr: 0.001563 +2023-03-29 17:50:56,294 epoch 116 - iter 490/493 - loss 0.00596664 - time (sec): 34.21 - samples/sec: 7525.35 - lr: 0.001563 +2023-03-29 17:50:56,507 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:50:56,507 EPOCH 116 done: loss 0.0060 - lr 0.001563 +2023-03-29 17:50:56,507 BAD EPOCHS (no improvement): 3 +2023-03-29 17:50:56,510 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:50:59,914 epoch 117 - iter 49/493 - loss 0.00556065 - time (sec): 3.40 - samples/sec: 7544.28 - lr: 0.001563 +2023-03-29 17:51:03,329 epoch 117 - iter 98/493 - loss 0.00649514 - time (sec): 6.82 - samples/sec: 7579.51 - lr: 0.001563 +2023-03-29 17:51:06,676 epoch 117 - iter 147/493 - loss 0.00642426 - time (sec): 10.17 - samples/sec: 7553.38 - lr: 0.001563 +2023-03-29 17:51:10,071 epoch 117 - iter 196/493 - loss 0.00675116 - time (sec): 13.56 - samples/sec: 7585.11 - lr: 0.001563 +2023-03-29 17:51:13,545 epoch 117 - iter 245/493 - loss 0.00669259 - time (sec): 17.04 - samples/sec: 7596.62 - lr: 0.001563 +2023-03-29 17:51:16,865 epoch 117 - iter 294/493 - loss 0.00665603 - time (sec): 20.36 - samples/sec: 7585.05 - lr: 0.001563 +2023-03-29 17:51:20,395 epoch 117 - iter 343/493 - loss 0.00675382 - time (sec): 23.89 - samples/sec: 7553.47 - lr: 0.001563 +2023-03-29 17:51:23,823 epoch 117 - iter 392/493 - loss 0.00670269 - time (sec): 27.31 - samples/sec: 7534.44 - lr: 0.001563 +2023-03-29 17:51:27,112 epoch 117 - iter 441/493 - loss 0.00659943 - time (sec): 30.60 - samples/sec: 7560.58 - lr: 0.001563 +2023-03-29 17:51:33,536 epoch 117 - iter 490/493 - loss 0.00678322 - time (sec): 37.03 - samples/sec: 6956.63 - lr: 0.001563 +2023-03-29 17:51:33,731 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:51:33,732 EPOCH 117 done: loss 0.0068 - lr 0.001563 +2023-03-29 17:51:33,732 Epoch 117: reducing learning rate of group 0 to 7.8125e-04. +2023-03-29 17:51:33,732 BAD EPOCHS (no improvement): 4 +2023-03-29 17:51:33,734 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:51:37,327 epoch 118 - iter 49/493 - loss 0.00658638 - time (sec): 3.59 - samples/sec: 7364.27 - lr: 0.000781 +2023-03-29 17:51:40,893 epoch 118 - iter 98/493 - loss 0.00652703 - time (sec): 7.16 - samples/sec: 7281.79 - lr: 0.000781 +2023-03-29 17:51:44,404 epoch 118 - iter 147/493 - loss 0.00668505 - time (sec): 10.67 - samples/sec: 7256.93 - lr: 0.000781 +2023-03-29 17:51:47,830 epoch 118 - iter 196/493 - loss 0.00658835 - time (sec): 14.10 - samples/sec: 7319.76 - lr: 0.000781 +2023-03-29 17:51:51,383 epoch 118 - iter 245/493 - loss 0.00644215 - time (sec): 17.65 - samples/sec: 7301.99 - lr: 0.000781 +2023-03-29 17:51:54,956 epoch 118 - iter 294/493 - loss 0.00652385 - time (sec): 21.22 - samples/sec: 7321.91 - lr: 0.000781 +2023-03-29 17:51:58,365 epoch 118 - iter 343/493 - loss 0.00654024 - time (sec): 24.63 - samples/sec: 7341.06 - lr: 0.000781 +2023-03-29 17:52:01,784 epoch 118 - iter 392/493 - loss 0.00647899 - time (sec): 28.05 - samples/sec: 7356.38 - lr: 0.000781 +2023-03-29 17:52:05,158 epoch 118 - iter 441/493 - loss 0.00650460 - time (sec): 31.42 - samples/sec: 7376.41 - lr: 0.000781 +2023-03-29 17:52:08,687 epoch 118 - iter 490/493 - loss 0.00667973 - time (sec): 34.95 - samples/sec: 7369.45 - lr: 0.000781 +2023-03-29 17:52:08,887 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:52:08,887 EPOCH 118 done: loss 0.0067 - lr 0.000781 +2023-03-29 17:52:08,888 BAD EPOCHS (no improvement): 1 +2023-03-29 17:52:08,890 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:52:12,419 epoch 119 - iter 49/493 - loss 0.00608181 - time (sec): 3.53 - samples/sec: 7257.05 - lr: 0.000781 +2023-03-29 17:52:16,256 epoch 119 - iter 98/493 - loss 0.00601208 - time (sec): 7.37 - samples/sec: 7146.06 - lr: 0.000781 +2023-03-29 17:52:19,748 epoch 119 - iter 147/493 - loss 0.00548327 - time (sec): 10.86 - samples/sec: 7198.80 - lr: 0.000781 +2023-03-29 17:52:23,111 epoch 119 - iter 196/493 - loss 0.00564948 - time (sec): 14.22 - samples/sec: 7294.38 - lr: 0.000781 +2023-03-29 17:52:26,511 epoch 119 - iter 245/493 - loss 0.00584250 - time (sec): 17.62 - samples/sec: 7330.89 - lr: 0.000781 +2023-03-29 17:52:29,881 epoch 119 - iter 294/493 - loss 0.00591830 - time (sec): 20.99 - samples/sec: 7366.79 - lr: 0.000781 +2023-03-29 17:52:33,421 epoch 119 - iter 343/493 - loss 0.00591154 - time (sec): 24.53 - samples/sec: 7364.12 - lr: 0.000781 +2023-03-29 17:52:36,821 epoch 119 - iter 392/493 - loss 0.00590758 - time (sec): 27.93 - samples/sec: 7383.71 - lr: 0.000781 +2023-03-29 17:52:40,260 epoch 119 - iter 441/493 - loss 0.00592919 - time (sec): 31.37 - samples/sec: 7396.53 - lr: 0.000781 +2023-03-29 17:52:43,596 epoch 119 - iter 490/493 - loss 0.00607027 - time (sec): 34.71 - samples/sec: 7421.29 - lr: 0.000781 +2023-03-29 17:52:43,796 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:52:43,796 EPOCH 119 done: loss 0.0061 - lr 0.000781 +2023-03-29 17:52:43,796 BAD EPOCHS (no improvement): 2 +2023-03-29 17:52:43,799 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:52:47,054 epoch 120 - iter 49/493 - loss 0.00638801 - time (sec): 3.26 - samples/sec: 7779.34 - lr: 0.000781 +2023-03-29 17:52:50,431 epoch 120 - iter 98/493 - loss 0.00652179 - time (sec): 6.63 - samples/sec: 7675.93 - lr: 0.000781 +2023-03-29 17:52:53,913 epoch 120 - iter 147/493 - loss 0.00667454 - time (sec): 10.11 - samples/sec: 7604.93 - lr: 0.000781 +2023-03-29 17:52:57,357 epoch 120 - iter 196/493 - loss 0.00686319 - time (sec): 13.56 - samples/sec: 7552.15 - lr: 0.000781 +2023-03-29 17:53:00,807 epoch 120 - iter 245/493 - loss 0.00669489 - time (sec): 17.01 - samples/sec: 7573.54 - lr: 0.000781 +2023-03-29 17:53:04,276 epoch 120 - iter 294/493 - loss 0.00652595 - time (sec): 20.48 - samples/sec: 7595.73 - lr: 0.000781 +2023-03-29 17:53:07,618 epoch 120 - iter 343/493 - loss 0.00638514 - time (sec): 23.82 - samples/sec: 7570.84 - lr: 0.000781 +2023-03-29 17:53:10,932 epoch 120 - iter 392/493 - loss 0.00630731 - time (sec): 27.13 - samples/sec: 7610.17 - lr: 0.000781 +2023-03-29 17:53:14,360 epoch 120 - iter 441/493 - loss 0.00614567 - time (sec): 30.56 - samples/sec: 7602.69 - lr: 0.000781 +2023-03-29 17:53:17,709 epoch 120 - iter 490/493 - loss 0.00608156 - time (sec): 33.91 - samples/sec: 7596.26 - lr: 0.000781 +2023-03-29 17:53:17,913 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:53:17,913 EPOCH 120 done: loss 0.0061 - lr 0.000781 +2023-03-29 17:53:17,913 BAD EPOCHS (no improvement): 3 +2023-03-29 17:53:17,916 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:53:21,507 epoch 121 - iter 49/493 - loss 0.00710549 - time (sec): 3.59 - samples/sec: 7375.04 - lr: 0.000781 +2023-03-29 17:53:24,793 epoch 121 - iter 98/493 - loss 0.00692539 - time (sec): 6.88 - samples/sec: 7482.88 - lr: 0.000781 +2023-03-29 17:53:28,111 epoch 121 - iter 147/493 - loss 0.00682256 - time (sec): 10.19 - samples/sec: 7556.39 - lr: 0.000781 +2023-03-29 17:53:31,517 epoch 121 - iter 196/493 - loss 0.00661373 - time (sec): 13.60 - samples/sec: 7543.69 - lr: 0.000781 +2023-03-29 17:53:34,915 epoch 121 - iter 245/493 - loss 0.00632979 - time (sec): 17.00 - samples/sec: 7559.63 - lr: 0.000781 +2023-03-29 17:53:38,474 epoch 121 - iter 294/493 - loss 0.00626038 - time (sec): 20.56 - samples/sec: 7544.41 - lr: 0.000781 +2023-03-29 17:53:41,893 epoch 121 - iter 343/493 - loss 0.00611005 - time (sec): 23.98 - samples/sec: 7534.68 - lr: 0.000781 +2023-03-29 17:53:45,366 epoch 121 - iter 392/493 - loss 0.00608508 - time (sec): 27.45 - samples/sec: 7537.61 - lr: 0.000781 +2023-03-29 17:53:48,668 epoch 121 - iter 441/493 - loss 0.00613797 - time (sec): 30.75 - samples/sec: 7558.66 - lr: 0.000781 +2023-03-29 17:53:52,012 epoch 121 - iter 490/493 - loss 0.00612733 - time (sec): 34.10 - samples/sec: 7555.54 - lr: 0.000781 +2023-03-29 17:53:52,223 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:53:52,223 EPOCH 121 done: loss 0.0061 - lr 0.000781 +2023-03-29 17:53:52,223 Epoch 121: reducing learning rate of group 0 to 3.9063e-04. +2023-03-29 17:53:52,223 BAD EPOCHS (no improvement): 4 +2023-03-29 17:53:52,226 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:53:55,489 epoch 122 - iter 49/493 - loss 0.00684342 - time (sec): 3.26 - samples/sec: 7798.87 - lr: 0.000391 +2023-03-29 17:53:58,851 epoch 122 - iter 98/493 - loss 0.00644594 - time (sec): 6.62 - samples/sec: 7630.21 - lr: 0.000391 +2023-03-29 17:54:02,201 epoch 122 - iter 147/493 - loss 0.00663640 - time (sec): 9.97 - samples/sec: 7642.93 - lr: 0.000391 +2023-03-29 17:54:05,502 epoch 122 - iter 196/493 - loss 0.00632482 - time (sec): 13.28 - samples/sec: 7670.34 - lr: 0.000391 +2023-03-29 17:54:08,944 epoch 122 - iter 245/493 - loss 0.00611891 - time (sec): 16.72 - samples/sec: 7655.80 - lr: 0.000391 +2023-03-29 17:54:12,525 epoch 122 - iter 294/493 - loss 0.00601900 - time (sec): 20.30 - samples/sec: 7561.93 - lr: 0.000391 +2023-03-29 17:54:15,910 epoch 122 - iter 343/493 - loss 0.00610750 - time (sec): 23.68 - samples/sec: 7581.99 - lr: 0.000391 +2023-03-29 17:54:19,343 epoch 122 - iter 392/493 - loss 0.00604042 - time (sec): 27.12 - samples/sec: 7580.58 - lr: 0.000391 +2023-03-29 17:54:22,802 epoch 122 - iter 441/493 - loss 0.00615812 - time (sec): 30.58 - samples/sec: 7596.56 - lr: 0.000391 +2023-03-29 17:54:26,211 epoch 122 - iter 490/493 - loss 0.00622035 - time (sec): 33.99 - samples/sec: 7580.78 - lr: 0.000391 +2023-03-29 17:54:26,412 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:54:26,412 EPOCH 122 done: loss 0.0062 - lr 0.000391 +2023-03-29 17:54:26,413 BAD EPOCHS (no improvement): 1 +2023-03-29 17:54:26,415 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:54:29,660 epoch 123 - iter 49/493 - loss 0.00617172 - time (sec): 3.25 - samples/sec: 7676.88 - lr: 0.000391 +2023-03-29 17:54:33,060 epoch 123 - iter 98/493 - loss 0.00567255 - time (sec): 6.65 - samples/sec: 7670.11 - lr: 0.000391 +2023-03-29 17:54:36,441 epoch 123 - iter 147/493 - loss 0.00669341 - time (sec): 10.03 - samples/sec: 7639.61 - lr: 0.000391 +2023-03-29 17:54:39,889 epoch 123 - iter 196/493 - loss 0.00641510 - time (sec): 13.47 - samples/sec: 7646.20 - lr: 0.000391 +2023-03-29 17:54:43,354 epoch 123 - iter 245/493 - loss 0.00608828 - time (sec): 16.94 - samples/sec: 7597.34 - lr: 0.000391 +2023-03-29 17:54:46,604 epoch 123 - iter 294/493 - loss 0.00589168 - time (sec): 20.19 - samples/sec: 7612.71 - lr: 0.000391 +2023-03-29 17:54:50,123 epoch 123 - iter 343/493 - loss 0.00597445 - time (sec): 23.71 - samples/sec: 7592.08 - lr: 0.000391 +2023-03-29 17:54:53,561 epoch 123 - iter 392/493 - loss 0.00588624 - time (sec): 27.15 - samples/sec: 7588.63 - lr: 0.000391 +2023-03-29 17:54:56,930 epoch 123 - iter 441/493 - loss 0.00583986 - time (sec): 30.52 - samples/sec: 7589.08 - lr: 0.000391 +2023-03-29 17:55:00,352 epoch 123 - iter 490/493 - loss 0.00599199 - time (sec): 33.94 - samples/sec: 7589.98 - lr: 0.000391 +2023-03-29 17:55:00,547 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:55:00,547 EPOCH 123 done: loss 0.0060 - lr 0.000391 +2023-03-29 17:55:00,547 BAD EPOCHS (no improvement): 2 +2023-03-29 17:55:00,553 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:55:04,116 epoch 124 - iter 49/493 - loss 0.00551931 - time (sec): 3.56 - samples/sec: 7324.41 - lr: 0.000391 +2023-03-29 17:55:07,617 epoch 124 - iter 98/493 - loss 0.00591350 - time (sec): 7.06 - samples/sec: 7347.75 - lr: 0.000391 +2023-03-29 17:55:10,979 epoch 124 - iter 147/493 - loss 0.00640294 - time (sec): 10.43 - samples/sec: 7441.71 - lr: 0.000391 +2023-03-29 17:55:14,538 epoch 124 - iter 196/493 - loss 0.00633526 - time (sec): 13.98 - samples/sec: 7363.55 - lr: 0.000391 +2023-03-29 17:55:17,923 epoch 124 - iter 245/493 - loss 0.00638028 - time (sec): 17.37 - samples/sec: 7414.25 - lr: 0.000391 +2023-03-29 17:55:21,355 epoch 124 - iter 294/493 - loss 0.00638010 - time (sec): 20.80 - samples/sec: 7423.24 - lr: 0.000391 +2023-03-29 17:55:24,843 epoch 124 - iter 343/493 - loss 0.00640306 - time (sec): 24.29 - samples/sec: 7398.28 - lr: 0.000391 +2023-03-29 17:55:28,432 epoch 124 - iter 392/493 - loss 0.00635066 - time (sec): 27.88 - samples/sec: 7370.61 - lr: 0.000391 +2023-03-29 17:55:31,896 epoch 124 - iter 441/493 - loss 0.00645959 - time (sec): 31.34 - samples/sec: 7379.77 - lr: 0.000391 +2023-03-29 17:55:35,330 epoch 124 - iter 490/493 - loss 0.00650392 - time (sec): 34.78 - samples/sec: 7405.20 - lr: 0.000391 +2023-03-29 17:55:35,527 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:55:35,528 EPOCH 124 done: loss 0.0065 - lr 0.000391 +2023-03-29 17:55:35,528 BAD EPOCHS (no improvement): 3 +2023-03-29 17:55:35,530 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:55:38,957 epoch 125 - iter 49/493 - loss 0.00658978 - time (sec): 3.43 - samples/sec: 7302.63 - lr: 0.000391 +2023-03-29 17:55:42,569 epoch 125 - iter 98/493 - loss 0.00604369 - time (sec): 7.04 - samples/sec: 7352.72 - lr: 0.000391 +2023-03-29 17:55:45,996 epoch 125 - iter 147/493 - loss 0.00564770 - time (sec): 10.47 - samples/sec: 7436.05 - lr: 0.000391 +2023-03-29 17:55:49,590 epoch 125 - iter 196/493 - loss 0.00609854 - time (sec): 14.06 - samples/sec: 7366.06 - lr: 0.000391 +2023-03-29 17:55:52,947 epoch 125 - iter 245/493 - loss 0.00647855 - time (sec): 17.42 - samples/sec: 7402.15 - lr: 0.000391 +2023-03-29 17:55:56,587 epoch 125 - iter 294/493 - loss 0.00668196 - time (sec): 21.06 - samples/sec: 7371.10 - lr: 0.000391 +2023-03-29 17:56:00,011 epoch 125 - iter 343/493 - loss 0.00675026 - time (sec): 24.48 - samples/sec: 7370.68 - lr: 0.000391 +2023-03-29 17:56:03,432 epoch 125 - iter 392/493 - loss 0.00679369 - time (sec): 27.90 - samples/sec: 7386.65 - lr: 0.000391 +2023-03-29 17:56:06,883 epoch 125 - iter 441/493 - loss 0.00666613 - time (sec): 31.35 - samples/sec: 7401.87 - lr: 0.000391 +2023-03-29 17:56:10,189 epoch 125 - iter 490/493 - loss 0.00672782 - time (sec): 34.66 - samples/sec: 7433.46 - lr: 0.000391 +2023-03-29 17:56:10,386 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:56:10,386 EPOCH 125 done: loss 0.0067 - lr 0.000391 +2023-03-29 17:56:10,386 Epoch 125: reducing learning rate of group 0 to 1.9531e-04. +2023-03-29 17:56:10,386 BAD EPOCHS (no improvement): 4 +2023-03-29 17:56:10,389 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:56:13,825 epoch 126 - iter 49/493 - loss 0.00677817 - time (sec): 3.44 - samples/sec: 7556.68 - lr: 0.000195 +2023-03-29 17:56:17,210 epoch 126 - iter 98/493 - loss 0.00613157 - time (sec): 6.82 - samples/sec: 7564.58 - lr: 0.000195 +2023-03-29 17:56:20,576 epoch 126 - iter 147/493 - loss 0.00616837 - time (sec): 10.19 - samples/sec: 7638.47 - lr: 0.000195 +2023-03-29 17:56:23,824 epoch 126 - iter 196/493 - loss 0.00596208 - time (sec): 13.43 - samples/sec: 7676.03 - lr: 0.000195 +2023-03-29 17:56:27,454 epoch 126 - iter 245/493 - loss 0.00597387 - time (sec): 17.06 - samples/sec: 7579.73 - lr: 0.000195 +2023-03-29 17:56:30,986 epoch 126 - iter 294/493 - loss 0.00612076 - time (sec): 20.60 - samples/sec: 7529.77 - lr: 0.000195 +2023-03-29 17:56:34,370 epoch 126 - iter 343/493 - loss 0.00623216 - time (sec): 23.98 - samples/sec: 7545.42 - lr: 0.000195 +2023-03-29 17:56:37,690 epoch 126 - iter 392/493 - loss 0.00608157 - time (sec): 27.30 - samples/sec: 7558.87 - lr: 0.000195 +2023-03-29 17:56:41,217 epoch 126 - iter 441/493 - loss 0.00609667 - time (sec): 30.83 - samples/sec: 7526.10 - lr: 0.000195 +2023-03-29 17:56:44,820 epoch 126 - iter 490/493 - loss 0.00597955 - time (sec): 34.43 - samples/sec: 7480.24 - lr: 0.000195 +2023-03-29 17:56:45,039 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:56:45,039 EPOCH 126 done: loss 0.0060 - lr 0.000195 +2023-03-29 17:56:45,040 BAD EPOCHS (no improvement): 1 +2023-03-29 17:56:45,042 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:56:48,635 epoch 127 - iter 49/493 - loss 0.00792995 - time (sec): 3.59 - samples/sec: 7159.51 - lr: 0.000195 +2023-03-29 17:56:52,093 epoch 127 - iter 98/493 - loss 0.00637629 - time (sec): 7.05 - samples/sec: 7253.13 - lr: 0.000195 +2023-03-29 17:56:55,589 epoch 127 - iter 147/493 - loss 0.00617894 - time (sec): 10.55 - samples/sec: 7273.58 - lr: 0.000195 +2023-03-29 17:56:59,189 epoch 127 - iter 196/493 - loss 0.00608748 - time (sec): 14.15 - samples/sec: 7268.28 - lr: 0.000195 +2023-03-29 17:57:02,785 epoch 127 - iter 245/493 - loss 0.00603498 - time (sec): 17.74 - samples/sec: 7266.59 - lr: 0.000195 +2023-03-29 17:57:06,220 epoch 127 - iter 294/493 - loss 0.00615045 - time (sec): 21.18 - samples/sec: 7316.83 - lr: 0.000195 +2023-03-29 17:57:09,644 epoch 127 - iter 343/493 - loss 0.00612571 - time (sec): 24.60 - samples/sec: 7342.44 - lr: 0.000195 +2023-03-29 17:57:12,918 epoch 127 - iter 392/493 - loss 0.00613199 - time (sec): 27.88 - samples/sec: 7384.95 - lr: 0.000195 +2023-03-29 17:57:16,356 epoch 127 - iter 441/493 - loss 0.00614883 - time (sec): 31.31 - samples/sec: 7396.48 - lr: 0.000195 +2023-03-29 17:57:19,891 epoch 127 - iter 490/493 - loss 0.00591375 - time (sec): 34.85 - samples/sec: 7392.05 - lr: 0.000195 +2023-03-29 17:57:20,083 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:57:20,083 EPOCH 127 done: loss 0.0059 - lr 0.000195 +2023-03-29 17:57:20,083 BAD EPOCHS (no improvement): 2 +2023-03-29 17:57:20,086 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:57:23,457 epoch 128 - iter 49/493 - loss 0.00656639 - time (sec): 3.37 - samples/sec: 7663.82 - lr: 0.000195 +2023-03-29 17:57:26,901 epoch 128 - iter 98/493 - loss 0.00669642 - time (sec): 6.81 - samples/sec: 7573.89 - lr: 0.000195 +2023-03-29 17:57:30,313 epoch 128 - iter 147/493 - loss 0.00723402 - time (sec): 10.23 - samples/sec: 7616.30 - lr: 0.000195 +2023-03-29 17:57:33,609 epoch 128 - iter 196/493 - loss 0.00689746 - time (sec): 13.52 - samples/sec: 7581.50 - lr: 0.000195 +2023-03-29 17:57:37,084 epoch 128 - iter 245/493 - loss 0.00678309 - time (sec): 17.00 - samples/sec: 7558.15 - lr: 0.000195 +2023-03-29 17:57:40,479 epoch 128 - iter 294/493 - loss 0.00675309 - time (sec): 20.39 - samples/sec: 7566.31 - lr: 0.000195 +2023-03-29 17:57:43,787 epoch 128 - iter 343/493 - loss 0.00681580 - time (sec): 23.70 - samples/sec: 7600.83 - lr: 0.000195 +2023-03-29 17:57:47,283 epoch 128 - iter 392/493 - loss 0.00674115 - time (sec): 27.20 - samples/sec: 7580.60 - lr: 0.000195 +2023-03-29 17:57:50,613 epoch 128 - iter 441/493 - loss 0.00665183 - time (sec): 30.53 - samples/sec: 7593.71 - lr: 0.000195 +2023-03-29 17:57:54,084 epoch 128 - iter 490/493 - loss 0.00671389 - time (sec): 34.00 - samples/sec: 7577.51 - lr: 0.000195 +2023-03-29 17:57:54,282 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:57:54,282 EPOCH 128 done: loss 0.0067 - lr 0.000195 +2023-03-29 17:57:54,282 BAD EPOCHS (no improvement): 3 +2023-03-29 17:57:54,285 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:57:57,711 epoch 129 - iter 49/493 - loss 0.00723180 - time (sec): 3.43 - samples/sec: 7595.09 - lr: 0.000195 +2023-03-29 17:58:01,130 epoch 129 - iter 98/493 - loss 0.00660335 - time (sec): 6.84 - samples/sec: 7512.29 - lr: 0.000195 +2023-03-29 17:58:04,637 epoch 129 - iter 147/493 - loss 0.00653070 - time (sec): 10.35 - samples/sec: 7491.41 - lr: 0.000195 +2023-03-29 17:58:08,032 epoch 129 - iter 196/493 - loss 0.00667291 - time (sec): 13.75 - samples/sec: 7523.23 - lr: 0.000195 +2023-03-29 17:58:11,433 epoch 129 - iter 245/493 - loss 0.00661422 - time (sec): 17.15 - samples/sec: 7523.71 - lr: 0.000195 +2023-03-29 17:58:14,804 epoch 129 - iter 294/493 - loss 0.00623407 - time (sec): 20.52 - samples/sec: 7539.20 - lr: 0.000195 +2023-03-29 17:58:18,120 epoch 129 - iter 343/493 - loss 0.00659638 - time (sec): 23.83 - samples/sec: 7559.03 - lr: 0.000195 +2023-03-29 17:58:21,529 epoch 129 - iter 392/493 - loss 0.00666303 - time (sec): 27.24 - samples/sec: 7579.16 - lr: 0.000195 +2023-03-29 17:58:25,095 epoch 129 - iter 441/493 - loss 0.00657534 - time (sec): 30.81 - samples/sec: 7542.97 - lr: 0.000195 +2023-03-29 17:58:28,374 epoch 129 - iter 490/493 - loss 0.00663830 - time (sec): 34.09 - samples/sec: 7559.31 - lr: 0.000195 +2023-03-29 17:58:28,582 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:58:28,582 EPOCH 129 done: loss 0.0066 - lr 0.000195 +2023-03-29 17:58:28,582 Epoch 129: reducing learning rate of group 0 to 9.7656e-05. +2023-03-29 17:58:28,582 BAD EPOCHS (no improvement): 4 +2023-03-29 17:58:28,585 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:58:28,585 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:58:28,585 learning rate too small - quitting training! +2023-03-29 17:58:28,585 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:58:35,394 ---------------------------------------------------------------------------------------------------- +2023-03-29 17:58:35,394 Testing using last state of model ... +2023-03-29 17:58:49,720 Evaluating as a multi-label problem: False +2023-03-29 17:58:49,743 0.8966 0.8584 0.8771 0.8024 +2023-03-29 17:58:49,743 +Results: +- F-score (micro) 0.8771 +- F-score (macro) 0.8091 +- Accuracy 0.8024 + +By class: + precision recall f1-score support + + PER 0.9367 0.9413 0.9390 1210 + LOC 0.8997 0.8877 0.8937 1051 + ORG 0.8226 0.7620 0.7911 584 + MISC 0.8031 0.4951 0.6126 206 + + micro avg 0.8966 0.8584 0.8771 3051 + macro avg 0.8655 0.7715 0.8091 3051 +weighted avg 0.8931 0.8584 0.8730 3051 + +2023-03-29 17:58:49,743 ----------------------------------------------------------------------------------------------------