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called : 10 + +PARAMETERS +Image characteristics +- QF = 75 +- Image size = 512 +- Embedding rate = 0.4 bpnzAC +- Cover images are taken in folder /gpfswork/rech/srp/commun/JPEG_75_512/c_coeffs/ +- Stego images are taken in folder /gpfswork/rech/srp/commun/JPEG_75_512/J_UNI_0_4_npy/ +- Cost maps are taken in folder /gpfswork/rech/srp/commun/JPEG_75_512/costs/ + +Protocol setup +- Strategy =minmax + +Model description +- The 3 model architectures are efnet,xunet,srnet with the following setup : + - Efficient-net version is b0 pretrained on image-net + - First conv stem is with stride = 1 + + - XuNet architecture is composed with 5 big blocks + +Training setup +- Train size = 4000 +- Valid size = 1000 +- Test size = 5000 +- Files permutation, which order determines train, valid and test sets is /gpfswork/rech/srp/commun/python3/tifs_protocol_efficientnet/models/permutation_files.npy +- Model efnet is trained during 30 epochs +- Pair training is not used +- Batch size is 8 +- Curriculum 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@@ +Fitter prepared. Device is cuda:0 + +2021-04-06T13:41:24.960986 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.38457, final_score: 0.15859, time: 446.41050 +[RESULT]: Val. Epoch: 1, summary_loss: 1.65717, final_score: 0.36663, time: 103.23291 + +2021-04-06T13:50:34.987949 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.25451, final_score: 0.06511, time: 464.97037 +[RESULT]: Val. Epoch: 2, summary_loss: 1.58793, final_score: 0.30619, time: 108.87386 + +2021-04-06T14:00:09.112296 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.20949, final_score: 0.04149, time: 444.50158 +[RESULT]: Val. Epoch: 3, summary_loss: 1.87403, final_score: 0.25624, time: 105.46765 + +2021-04-06T14:09:19.228772 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22217, final_score: 0.04849, time: 456.23604 +[RESULT]: Val. Epoch: 4, summary_loss: 1.30484, final_score: 0.20130, time: 110.81499 + +2021-04-06T14:18:46.532736 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.19602, final_score: 0.03662, time: 433.32361 +[RESULT]: Val. Epoch: 5, summary_loss: 1.52900, final_score: 0.31568, time: 106.10954 + +2021-04-06T14:27:46.086618 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22254, final_score: 0.05199, time: 455.11430 +[RESULT]: Val. Epoch: 6, summary_loss: 2.05622, final_score: 0.32168, time: 103.39090 + +2021-04-06T14:37:04.741094 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.19837, final_score: 0.03862, time: 476.46509 +[RESULT]: Val. Epoch: 7, summary_loss: 1.06776, final_score: 0.24775, time: 114.84630 + +2021-04-06T14:46:56.368150 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.22327, final_score: 0.05236, time: 478.20518 +[RESULT]: Val. Epoch: 8, summary_loss: 1.87947, final_score: 0.32567, time: 115.83542 + +2021-04-06T14:56:50.551096 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.21421, final_score: 0.04749, time: 466.70660 +[RESULT]: Val. Epoch: 9, summary_loss: 0.37249, final_score: 0.13187, time: 110.53179 + +2021-04-06T15:06:28.052539 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.23362, final_score: 0.05999, time: 468.94585 +[RESULT]: Val. Epoch: 10, summary_loss: 0.61707, final_score: 0.09341, time: 107.26632 + +2021-04-06T15:16:04.379549 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.22881, final_score: 0.05524, time: 463.31607 +[RESULT]: Val. Epoch: 11, summary_loss: 1.42742, final_score: 0.19730, time: 107.25408 + +2021-04-06T15:25:35.067026 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.24591, final_score: 0.06636, time: 472.86618 +[RESULT]: Val. Epoch: 12, summary_loss: 0.68325, final_score: 0.11888, time: 107.56692 + +2021-04-06T15:35:15.647462 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.23399, final_score: 0.06148, time: 484.51604 +[RESULT]: Val. Epoch: 13, summary_loss: 0.98300, final_score: 0.14835, time: 114.08524 + +2021-04-06T15:45:14.391014 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.26335, final_score: 0.07823, time: 461.35396 +[RESULT]: Val. Epoch: 14, summary_loss: 0.52365, final_score: 0.09341, time: 105.38135 + +2021-04-06T15:54:41.237102 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.24524, final_score: 0.06611, time: 451.49072 +[RESULT]: Val. Epoch: 15, summary_loss: 1.57966, final_score: 0.22228, time: 103.64308 + +2021-04-06T16:03:56.506007 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.27711, final_score: 0.08798, time: 464.12727 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69393, final_score: 0.11239, time: 107.76890 + +2021-04-06T16:13:28.516214 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.27007, final_score: 0.08210, time: 458.48955 +[RESULT]: Val. Epoch: 17, summary_loss: 0.26598, final_score: 0.06643, time: 107.14588 + +2021-04-06T16:22:54.401930 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.28404, final_score: 0.09135, time: 455.02252 +[RESULT]: Val. Epoch: 18, summary_loss: 1.25297, final_score: 0.17383, time: 106.17660 + +2021-04-06T16:32:15.739027 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.27969, final_score: 0.08435, time: 465.55680 +[RESULT]: Val. Epoch: 19, summary_loss: 0.45947, final_score: 0.09441, time: 104.74326 + +2021-04-06T16:41:46.193268 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.24403, final_score: 0.07048, time: 457.30382 +[RESULT]: Val. Epoch: 20, summary_loss: 0.28149, final_score: 0.05495, time: 106.19020 + +2021-04-06T16:51:09.825655 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.23540, final_score: 0.06261, time: 459.04081 +[RESULT]: Val. Epoch: 21, summary_loss: 0.22065, final_score: 0.05195, time: 105.68800 + +2021-04-06T17:00:34.779046 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.22848, final_score: 0.06023, time: 460.78100 +[RESULT]: Val. Epoch: 22, summary_loss: 0.56600, final_score: 0.08991, time: 104.49872 + +2021-04-06T17:10:00.186664 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.22442, final_score: 0.05649, time: 452.74057 +[RESULT]: Val. Epoch: 23, summary_loss: 0.70976, final_score: 0.09590, time: 106.62299 + +2021-04-06T17:19:19.688767 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.20737, final_score: 0.04599, time: 460.69333 +[RESULT]: Val. Epoch: 24, summary_loss: 0.26602, final_score: 0.04496, time: 106.68803 + +2021-04-06T17:28:47.183044 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.21228, final_score: 0.05049, time: 451.73303 +[RESULT]: Val. Epoch: 25, summary_loss: 0.53535, final_score: 0.07742, time: 106.14428 + +2021-04-06T17:38:05.199378 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.18933, final_score: 0.03699, time: 455.90954 +[RESULT]: Val. Epoch: 26, summary_loss: 0.28445, final_score: 0.04595, time: 105.60008 + +2021-04-06T17:47:26.849064 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.19479, final_score: 0.04136, time: 452.54981 +[RESULT]: Val. Epoch: 27, summary_loss: 0.33729, final_score: 0.05095, time: 109.18742 + +2021-04-06T17:56:48.729971 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.19070, final_score: 0.03899, time: 463.43152 +[RESULT]: Val. Epoch: 28, summary_loss: 0.34065, final_score: 0.04945, time: 104.66443 + +2021-04-06T18:06:16.942842 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.18514, final_score: 0.03599, time: 460.37873 +[RESULT]: Val. Epoch: 29, summary_loss: 0.35515, final_score: 0.04895, time: 109.67818 + +2021-04-06T18:15:47.129815 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.18381, final_score: 0.03512, time: 455.40007 +[RESULT]: Val. Epoch: 30, summary_loss: 0.32251, final_score: 0.04595, time: 106.60117 +Fitter prepared. Device is cuda:0 + +2021-04-12T08:15:48.336681 +LR: 0.0005 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 +Fitter prepared. Device is cuda:0 + +2021-04-28T09:38:24.921363 +LR: 1.5625e-05 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 31, summary_loss: 0.39903, final_score: 0.16058, time: 743.66876 +[RESULT]: Val. Epoch: 31, summary_loss: 1.12617, final_score: 0.33816, time: 173.86461 + +2021-04-28T09:53:42.841988 +LR: 1.5625e-05 +Emb_rate: 0.18000000000000002 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..a5ec401fcd5861cdc3cca299f16f60eb2c83f273 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-036epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-036epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..3d4e0335272abace179c80654fb23c6fda20b5e9 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-036epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b57fe71c04bd8749a3b533fb8b0214c99f016142b3622ad5642c9201accee032 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-038epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-038epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..de806797a76801c62f6b7af93a1db9303703a769 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-038epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:64a04cffc61194279f303b5a8218e082b9a91feb66e5ec98f63e3c76073fdd3f +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-039epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-039epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f596fdb9e8505f3a59023b224e116ba9acb5157d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/best-checkpoint-039epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e7e65b05a91249c6321b437da83c275a9dfbac00f4f0f7db4d1d24a2967ab01b +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..c1f1ad66803847960a80c0fa8f3f2982b7ad6c86 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7e6e3dd2ecad90902b314d9a1e8aae687fdf4db6ef8e8c9c2740c429e0fe2961 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..7c78c8a074d5eb327abf5ca909822a965737e774 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/log.txt @@ -0,0 +1,242 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:48:18.286009 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.43501, final_score: 0.19145, time: 720.08656 +[RESULT]: Val. Epoch: 1, summary_loss: 3.53685, final_score: 0.45954, time: 165.93323 + +2021-04-26T10:03:04.687305 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.27887, final_score: 0.07936, time: 690.34998 +[RESULT]: Val. Epoch: 2, summary_loss: 2.19805, final_score: 0.43257, time: 166.88085 + +2021-04-26T10:17:22.243014 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.22977, final_score: 0.05374, time: 675.23893 +[RESULT]: Val. Epoch: 3, summary_loss: 3.76291, final_score: 0.43556, time: 165.13361 + +2021-04-26T10:31:22.807231 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22594, final_score: 0.05224, time: 682.05105 +[RESULT]: Val. Epoch: 4, summary_loss: 1.93782, final_score: 0.42507, time: 163.91369 + +2021-04-26T10:45:29.159406 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.20147, final_score: 0.03862, time: 687.04098 +[RESULT]: Val. Epoch: 5, summary_loss: 1.48217, final_score: 0.48052, time: 164.43833 + +2021-04-26T10:59:40.993276 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22603, final_score: 0.05449, time: 689.99004 +[RESULT]: Val. Epoch: 6, summary_loss: 1.94142, final_score: 0.46903, time: 165.01467 + +2021-04-26T11:13:56.187145 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.19619, final_score: 0.03699, time: 674.49473 +[RESULT]: Val. Epoch: 7, summary_loss: 1.59094, final_score: 0.43706, time: 164.94940 + +2021-04-26T11:27:55.818517 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.22218, final_score: 0.05186, time: 686.19339 +[RESULT]: Val. Epoch: 8, summary_loss: 0.99177, final_score: 0.38911, time: 167.37074 + +2021-04-26T11:42:09.717630 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.20586, final_score: 0.04324, time: 698.41854 +[RESULT]: Val. Epoch: 9, summary_loss: 1.44147, final_score: 0.42158, time: 168.29029 + +2021-04-26T11:56:36.599077 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.22511, final_score: 0.05486, time: 700.55670 +[RESULT]: Val. Epoch: 10, summary_loss: 2.02638, final_score: 0.42008, time: 166.98877 + +2021-04-26T12:11:04.342648 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.22125, final_score: 0.05224, time: 704.81501 +[RESULT]: Val. Epoch: 11, summary_loss: 1.63879, final_score: 0.39510, time: 164.60945 + +2021-04-26T12:25:33.959582 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.23000, final_score: 0.05811, time: 694.38467 +[RESULT]: Val. Epoch: 12, summary_loss: 2.32041, final_score: 0.40609, time: 164.73405 + +2021-04-26T12:39:53.281183 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.23265, final_score: 0.05911, time: 692.64143 +[RESULT]: Val. Epoch: 13, summary_loss: 1.51879, final_score: 0.43906, time: 163.35546 + +2021-04-26T12:54:09.477626 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.24724, final_score: 0.06811, time: 693.94303 +[RESULT]: Val. Epoch: 14, summary_loss: 1.82567, final_score: 0.38811, time: 166.58948 + +2021-04-26T13:08:30.192923 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.22853, final_score: 0.05874, time: 697.08200 +[RESULT]: Val. Epoch: 15, summary_loss: 1.87019, final_score: 0.40909, time: 163.81336 + +2021-04-26T13:22:51.262240 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.26629, final_score: 0.07998, time: 701.74162 +[RESULT]: Val. Epoch: 16, summary_loss: 1.54548, final_score: 0.35065, time: 163.85540 + +2021-04-26T13:37:17.073147 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.25805, final_score: 0.07436, time: 688.21683 +[RESULT]: Val. Epoch: 17, summary_loss: 0.92029, final_score: 0.36414, time: 166.45762 + +2021-04-26T13:51:32.122459 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.27671, final_score: 0.08748, time: 706.40313 +[RESULT]: Val. Epoch: 18, summary_loss: 1.84621, final_score: 0.37612, time: 166.08317 + +2021-04-26T14:06:04.805245 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.26880, final_score: 0.08223, time: 696.93859 +[RESULT]: Val. Epoch: 19, summary_loss: 1.64067, final_score: 0.35614, time: 163.53194 + +2021-04-26T14:20:25.446638 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.29261, final_score: 0.09798, time: 718.08656 +[RESULT]: Val. Epoch: 20, summary_loss: 1.42854, final_score: 0.33267, time: 166.18933 + +2021-04-26T14:35:09.914859 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 21, summary_loss: 0.29281, final_score: 0.09835, time: 705.18243 +[RESULT]: Val. Epoch: 21, summary_loss: 2.00417, final_score: 0.34915, time: 167.56646 + +2021-04-26T14:49:42.839592 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.31986, final_score: 0.11272, time: 698.50465 +[RESULT]: Val. Epoch: 22, summary_loss: 1.36035, final_score: 0.38961, time: 163.14537 + +2021-04-26T15:04:04.669750 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.30879, final_score: 0.10760, time: 708.05474 +[RESULT]: Val. Epoch: 23, summary_loss: 1.51937, final_score: 0.34815, time: 164.73840 + +2021-04-26T15:18:37.630875 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.33874, final_score: 0.12172, time: 694.42999 +[RESULT]: Val. Epoch: 24, summary_loss: 1.05550, final_score: 0.36913, time: 167.54664 + +2021-04-26T15:32:59.790152 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 25, summary_loss: 0.33641, final_score: 0.12484, time: 696.06533 +[RESULT]: Val. Epoch: 25, summary_loss: 1.54550, final_score: 0.35465, time: 165.97788 + +2021-04-26T15:47:22.069152 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.36326, final_score: 0.14634, time: 707.90735 +[RESULT]: Val. Epoch: 26, summary_loss: 1.93412, final_score: 0.38711, time: 163.44319 + +2021-04-26T16:01:53.601447 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 27, summary_loss: 0.34997, final_score: 0.13547, time: 695.77552 +[RESULT]: Val. Epoch: 27, summary_loss: 0.98111, final_score: 0.33616, time: 164.70023 + +2021-04-26T16:16:14.307028 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.37307, final_score: 0.14859, time: 704.90242 +[RESULT]: Val. Epoch: 28, summary_loss: 0.94927, final_score: 0.32118, time: 167.62900 + +2021-04-26T16:30:47.031973 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 29, summary_loss: 0.37986, final_score: 0.15346, time: 690.02928 +[RESULT]: Val. Epoch: 29, summary_loss: 1.12114, final_score: 0.33467, time: 165.43189 + +2021-04-26T16:45:02.675569 +LR: 0.0005 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 30, summary_loss: 0.40831, final_score: 0.17296, time: 693.70758 +[RESULT]: Val. Epoch: 30, summary_loss: 0.81160, final_score: 0.32118, time: 164.75570 +Fitter prepared. Device is cuda:0 + +2021-04-28T10:05:02.433990 +LR: 0.0005 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 31, summary_loss: 0.40259, final_score: 0.16908, time: 719.53492 +[RESULT]: Val. Epoch: 31, summary_loss: 0.67385, final_score: 0.31069, time: 163.08922 + +2021-04-28T10:19:45.564530 +LR: 0.0005 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 32, summary_loss: 0.43800, final_score: 0.19133, time: 705.38239 +[RESULT]: Val. Epoch: 32, summary_loss: 1.35296, final_score: 0.33816, time: 164.46076 + +2021-04-28T10:34:15.581470 +LR: 0.0005 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 33, summary_loss: 0.43168, final_score: 0.19333, time: 722.00718 +[RESULT]: Val. Epoch: 33, summary_loss: 0.80095, final_score: 0.32567, time: 164.39163 + +2021-04-28T10:49:02.159009 +LR: 0.0005 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 34, summary_loss: 0.46100, final_score: 0.21182, time: 709.51972 +[RESULT]: Val. Epoch: 34, summary_loss: 0.66319, final_score: 0.31518, time: 163.10031 + +2021-04-28T11:03:35.342215 +LR: 0.0005 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 35, summary_loss: 0.45019, final_score: 0.20720, time: 717.34234 +[RESULT]: Val. Epoch: 35, summary_loss: 0.66912, final_score: 0.30619, time: 165.26908 + +2021-04-28T11:18:18.146232 +LR: 0.0005 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 36, summary_loss: 0.48384, final_score: 0.23157, time: 716.23115 +[RESULT]: Val. Epoch: 36, summary_loss: 0.59882, final_score: 0.29920, time: 163.25293 + +2021-04-28T11:32:57.997398 +LR: 0.0005 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 37, summary_loss: 0.47147, final_score: 0.22169, time: 706.46444 +[RESULT]: Val. Epoch: 37, summary_loss: 0.62365, final_score: 0.29870, time: 165.80943 + +2021-04-28T11:47:30.511321 +LR: 0.0005 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 38, summary_loss: 0.49579, final_score: 0.23569, time: 724.98851 +[RESULT]: Val. Epoch: 38, summary_loss: 0.59242, final_score: 0.30020, time: 163.78264 + +2021-04-28T12:02:19.633813 +LR: 0.0005 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 39, summary_loss: 0.49743, final_score: 0.23919, time: 728.28275 +[RESULT]: Val. Epoch: 39, summary_loss: 0.57864, final_score: 0.28372, time: 163.70417 + +2021-04-28T12:17:11.923696 +LR: 0.0005 +Emb_rate: 0.11809800000000004 +[RESULT]: Train. Epoch: 40, summary_loss: 0.51478, final_score: 0.25606, time: 724.76678 +[RESULT]: Val. Epoch: 40, summary_loss: 1.23882, final_score: 0.33516, time: 165.65714 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..7cb8ab686e25c254904245701a6544070812bf05 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-017epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-017epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..014b5ebdaec6aa1f19ab32797da0af145c244da6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-017epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ea9097bc517f2fdffa6c52eec04dacb6d23cd1cb4a57897c20c51f986d0a7c09 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-018epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-018epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..6fc2f495bf59934048ee799419309a44a0faab2e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-018epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:43ab394b56c1324d345514454346e3dd652923ddaf5c65e42c4e57f2f44ad2e2 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..ba9845b59d84cba8d665d6a96bf710278a584c45 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c8e048cedd1befcdf868582dff464d37bb7556b2986076f1e573f7fb687f1f2a +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..097b00bed36f845a90c5c36a07b0d15f2caa440b --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3ec66213e5ac91d7625689fabf6047da3b94e355b7b400cbbf42d3d7380c9c92 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..8b7042e926f76c794e205fea1aba8e875554715f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_0_0.2/log.txt @@ -0,0 +1,182 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:42:38.956394 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.37787, final_score: 0.15621, time: 680.97926 +[RESULT]: Val. Epoch: 1, summary_loss: 1.99894, final_score: 0.47902, time: 166.53369 + +2021-04-26T09:56:46.725873 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.24563, final_score: 0.06036, time: 676.72309 +[RESULT]: Val. Epoch: 2, summary_loss: 2.76199, final_score: 0.42707, time: 165.13346 + +2021-04-26T10:10:48.707019 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.20466, final_score: 0.04061, time: 683.87065 +[RESULT]: Val. Epoch: 3, summary_loss: 1.77149, final_score: 0.36813, time: 164.33880 + +2021-04-26T10:24:57.182041 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.20667, final_score: 0.04361, time: 688.78306 +[RESULT]: Val. Epoch: 4, summary_loss: 1.97962, final_score: 0.38462, time: 162.37636 + +2021-04-26T10:39:08.480336 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.19156, final_score: 0.03287, time: 664.63021 +[RESULT]: Val. Epoch: 5, summary_loss: 2.39761, final_score: 0.42557, time: 163.02837 + +2021-04-26T10:52:56.293432 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.21613, final_score: 0.04799, time: 683.56305 +[RESULT]: Val. Epoch: 6, summary_loss: 1.42065, final_score: 0.37962, time: 162.26185 + +2021-04-26T11:07:02.385275 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.20115, final_score: 0.04099, time: 683.88505 +[RESULT]: Val. Epoch: 7, summary_loss: 1.40856, final_score: 0.31518, time: 163.03656 + +2021-04-26T11:21:09.550049 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.22536, final_score: 0.05286, time: 681.47892 +[RESULT]: Val. Epoch: 8, summary_loss: 1.64898, final_score: 0.33467, time: 164.81276 + +2021-04-26T11:35:15.979109 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.20761, final_score: 0.04511, time: 684.94377 +[RESULT]: Val. Epoch: 9, summary_loss: 1.75014, final_score: 0.38711, time: 165.34193 + +2021-04-26T11:49:26.377682 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.23017, final_score: 0.05786, time: 694.25029 +[RESULT]: Val. Epoch: 10, summary_loss: 0.80731, final_score: 0.27622, time: 162.79960 + +2021-04-26T12:03:43.673128 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.23934, final_score: 0.06211, time: 699.93721 +[RESULT]: Val. Epoch: 11, summary_loss: 0.85419, final_score: 0.25674, time: 163.89502 + +2021-04-26T12:18:07.639646 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.24860, final_score: 0.06661, time: 687.75638 +[RESULT]: Val. Epoch: 12, summary_loss: 1.46492, final_score: 0.29321, time: 164.30324 + +2021-04-26T12:32:19.833428 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.23604, final_score: 0.05886, time: 687.47868 +[RESULT]: Val. Epoch: 13, summary_loss: 1.76193, final_score: 0.34116, time: 162.47569 + +2021-04-26T12:46:29.928646 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.25205, final_score: 0.07036, time: 687.02018 +[RESULT]: Val. Epoch: 14, summary_loss: 1.06660, final_score: 0.29570, time: 165.31148 + +2021-04-26T13:00:42.371493 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.25429, final_score: 0.07298, time: 691.20165 +[RESULT]: Val. Epoch: 15, summary_loss: 1.38822, final_score: 0.25874, time: 162.74216 + +2021-04-26T13:14:56.425800 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.27370, final_score: 0.08548, time: 693.00431 +[RESULT]: Val. Epoch: 16, summary_loss: 1.47160, final_score: 0.27522, time: 163.64580 + +2021-04-26T13:29:13.185087 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.26319, final_score: 0.07948, time: 697.42029 +[RESULT]: Val. Epoch: 17, summary_loss: 0.72113, final_score: 0.22577, time: 163.38783 + +2021-04-26T13:43:34.315463 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.29882, final_score: 0.09585, time: 690.47745 +[RESULT]: Val. Epoch: 18, summary_loss: 0.54267, final_score: 0.21179, time: 163.72035 + +2021-04-26T13:57:48.754039 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.28953, final_score: 0.09498, time: 685.91874 +[RESULT]: Val. Epoch: 19, summary_loss: 1.31976, final_score: 0.22877, time: 163.61401 + +2021-04-26T14:11:58.421961 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.30814, final_score: 0.10597, time: 697.91424 +[RESULT]: Val. Epoch: 20, summary_loss: 0.84348, final_score: 0.23427, time: 161.98513 + +2021-04-26T14:26:18.478114 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 21, summary_loss: 0.30275, final_score: 0.10147, time: 690.88045 +[RESULT]: Val. Epoch: 21, summary_loss: 1.24073, final_score: 0.27323, time: 163.36699 + +2021-04-26T14:40:32.893504 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.33174, final_score: 0.12259, time: 687.19787 +[RESULT]: Val. Epoch: 22, summary_loss: 0.71227, final_score: 0.22977, time: 161.65373 + +2021-04-26T14:54:41.878711 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.32784, final_score: 0.11947, time: 704.33893 +[RESULT]: Val. Epoch: 23, summary_loss: 1.36628, final_score: 0.21728, time: 165.83316 + +2021-04-26T15:09:12.183007 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.34365, final_score: 0.12959, time: 698.65438 +[RESULT]: Val. Epoch: 24, summary_loss: 0.69318, final_score: 0.20480, time: 161.94093 + +2021-04-26T15:23:32.914631 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 25, summary_loss: 0.34507, final_score: 0.13259, time: 698.34160 +[RESULT]: Val. Epoch: 25, summary_loss: 0.46614, final_score: 0.18182, time: 161.92198 + +2021-04-26T15:37:53.422171 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.36971, final_score: 0.14309, time: 689.22697 +[RESULT]: Val. Epoch: 26, summary_loss: 0.75347, final_score: 0.20829, time: 164.26572 + +2021-04-26T15:52:07.050591 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 27, summary_loss: 0.36230, final_score: 0.14409, time: 699.02312 +[RESULT]: Val. Epoch: 27, summary_loss: 0.52706, final_score: 0.19131, time: 162.99755 + +2021-04-26T16:06:29.205988 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.38894, final_score: 0.15671, time: 682.92175 +[RESULT]: Val. Epoch: 28, summary_loss: 0.54008, final_score: 0.17882, time: 162.26578 + +2021-04-26T16:20:34.532981 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 29, summary_loss: 0.37982, final_score: 0.15121, time: 692.02997 +[RESULT]: Val. Epoch: 29, summary_loss: 0.88350, final_score: 0.19780, time: 162.07168 + +2021-04-26T16:34:48.782006 +LR: 0.0005 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 30, summary_loss: 0.41183, final_score: 0.17558, time: 685.94667 +[RESULT]: Val. Epoch: 30, summary_loss: 0.74262, final_score: 0.20130, time: 163.84190 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:42:33.501870 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.38708, final_score: 0.15821, time: 705.93890 +[RESULT]: Val. Epoch: 1, summary_loss: 1.65027, final_score: 0.41508, time: 164.04028 + +2021-04-26T09:57:03.849085 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.25293, final_score: 0.06561, time: 675.82266 +[RESULT]: Val. Epoch: 2, summary_loss: 1.74864, final_score: 0.34815, time: 163.34013 + +2021-04-26T10:11:03.185284 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.20655, final_score: 0.04149, time: 668.84584 +[RESULT]: Val. Epoch: 3, summary_loss: 1.56498, final_score: 0.32368, time: 162.09735 + +2021-04-26T10:24:54.504321 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22039, final_score: 0.04974, time: 675.45446 +[RESULT]: Val. Epoch: 4, summary_loss: 1.22362, final_score: 0.27123, time: 162.08292 + +2021-04-26T10:38:52.421169 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.20125, final_score: 0.04024, time: 680.91575 +[RESULT]: Val. Epoch: 5, summary_loss: 1.32875, final_score: 0.28921, time: 165.55257 + +2021-04-26T10:52:59.088715 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22772, final_score: 0.05511, time: 684.90550 +[RESULT]: Val. Epoch: 6, summary_loss: 1.31337, final_score: 0.20879, time: 161.80147 + +2021-04-26T11:07:05.987177 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.20929, final_score: 0.04336, time: 685.62151 +[RESULT]: Val. Epoch: 7, summary_loss: 1.94350, final_score: 0.34066, time: 163.22191 + +2021-04-26T11:21:14.999560 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.22576, final_score: 0.05324, time: 678.80042 +[RESULT]: Val. Epoch: 8, summary_loss: 1.13579, final_score: 0.23526, time: 163.03063 + +2021-04-26T11:35:17.182504 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.21663, final_score: 0.04724, time: 677.48215 +[RESULT]: Val. Epoch: 9, summary_loss: 2.11393, final_score: 0.25524, time: 163.36381 + +2021-04-26T11:49:18.192155 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.23906, final_score: 0.06261, time: 696.97676 +[RESULT]: Val. Epoch: 10, summary_loss: 1.36289, final_score: 0.17033, time: 162.23995 + +2021-04-26T12:03:37.572664 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.22236, final_score: 0.05161, time: 690.23052 +[RESULT]: Val. Epoch: 11, summary_loss: 1.14024, final_score: 0.19580, time: 162.41618 + +2021-04-26T12:17:50.411112 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.25309, final_score: 0.06936, time: 695.15843 +[RESULT]: Val. Epoch: 12, summary_loss: 1.03795, final_score: 0.19231, time: 162.59750 + +2021-04-26T12:32:08.510986 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.23917, final_score: 0.06261, time: 676.75777 +[RESULT]: Val. Epoch: 13, summary_loss: 1.21966, final_score: 0.20480, time: 164.12270 + +2021-04-26T12:46:09.522273 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.25573, final_score: 0.07373, time: 691.66937 +[RESULT]: Val. Epoch: 14, summary_loss: 0.42461, final_score: 0.16084, time: 161.73974 + +2021-04-26T13:00:23.285051 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.24597, final_score: 0.06686, time: 702.91537 +[RESULT]: Val. Epoch: 15, summary_loss: 1.38118, final_score: 0.19231, time: 163.99361 + +2021-04-26T13:14:50.424609 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.27711, final_score: 0.08360, time: 699.26809 +[RESULT]: Val. Epoch: 16, summary_loss: 0.92684, final_score: 0.14735, time: 165.85875 + +2021-04-26T13:29:15.734350 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.27198, final_score: 0.08473, time: 682.70001 +[RESULT]: Val. Epoch: 17, summary_loss: 0.47470, final_score: 0.15135, time: 163.19384 + +2021-04-26T13:43:21.837596 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.29714, final_score: 0.09885, time: 697.63713 +[RESULT]: Val. Epoch: 18, summary_loss: 0.39894, final_score: 0.15185, time: 161.83027 + +2021-04-26T13:57:41.710955 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.27622, final_score: 0.08535, time: 687.85438 +[RESULT]: Val. Epoch: 19, summary_loss: 0.57311, final_score: 0.12038, time: 161.44874 + +2021-04-26T14:11:51.237671 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.30904, final_score: 0.10347, time: 693.09301 +[RESULT]: Val. Epoch: 20, summary_loss: 0.69632, final_score: 0.11688, time: 162.20061 + +2021-04-26T14:26:06.721982 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 21, summary_loss: 0.29490, final_score: 0.09710, time: 691.48102 +[RESULT]: Val. Epoch: 21, summary_loss: 0.40236, final_score: 0.12438, time: 161.36569 + +2021-04-26T14:40:19.759796 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.32847, final_score: 0.12184, time: 691.64201 +[RESULT]: Val. Epoch: 22, summary_loss: 0.39000, final_score: 0.12088, time: 161.11540 + +2021-04-26T14:54:32.879919 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.31839, final_score: 0.11210, time: 708.63301 +[RESULT]: Val. Epoch: 23, summary_loss: 0.36083, final_score: 0.10639, time: 165.65502 + +2021-04-26T15:09:07.529176 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 24, summary_loss: 0.32839, final_score: 0.11760, time: 702.29530 +[RESULT]: Val. Epoch: 24, summary_loss: 0.51369, final_score: 0.10789, time: 162.16720 + +2021-04-26T15:23:32.173306 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 25, summary_loss: 0.32136, final_score: 0.11122, time: 684.04516 +[RESULT]: Val. Epoch: 25, summary_loss: 0.29104, final_score: 0.08791, time: 162.18789 + +2021-04-26T15:37:38.755509 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 26, summary_loss: 0.32112, final_score: 0.11510, time: 682.34516 +[RESULT]: Val. Epoch: 26, summary_loss: 0.30537, final_score: 0.10240, time: 162.75153 + +2021-04-26T15:51:44.041393 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 27, summary_loss: 0.31160, final_score: 0.10847, time: 692.97416 +[RESULT]: Val. Epoch: 27, summary_loss: 0.43067, final_score: 0.12987, time: 164.87310 + +2021-04-26T16:06:02.063514 +LR: 0.00025 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 28, summary_loss: 0.27504, final_score: 0.08573, time: 701.32362 +[RESULT]: Val. Epoch: 28, summary_loss: 0.48262, final_score: 0.09640, time: 164.83962 + +2021-04-26T16:20:28.569966 +LR: 0.00025 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 29, summary_loss: 0.27286, final_score: 0.08710, time: 693.66442 +[RESULT]: Val. Epoch: 29, summary_loss: 0.60810, final_score: 0.11039, time: 161.05649 + +2021-04-26T16:34:43.487347 +LR: 0.000125 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 30, summary_loss: 0.25375, final_score: 0.07311, time: 688.20090 +[RESULT]: Val. Epoch: 30, summary_loss: 0.45358, final_score: 0.09191, time: 161.52871 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:43:26.681932 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.38451, final_score: 0.15971, time: 708.58558 +[RESULT]: Val. Epoch: 1, summary_loss: 1.49582, final_score: 0.26673, time: 167.86630 + +2021-04-26T09:58:03.558800 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.25564, final_score: 0.06336, time: 691.50563 +[RESULT]: Val. Epoch: 2, summary_loss: 1.19938, final_score: 0.18432, time: 167.97683 + +2021-04-26T10:12:23.432351 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.20637, final_score: 0.04136, time: 692.81944 +[RESULT]: Val. Epoch: 3, summary_loss: 1.53257, final_score: 0.25375, time: 170.33976 + +2021-04-26T10:26:46.800552 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22069, final_score: 0.04899, time: 684.20858 +[RESULT]: Val. Epoch: 4, summary_loss: 1.00555, final_score: 0.20130, time: 168.33094 + +2021-04-26T10:40:59.740037 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.19455, final_score: 0.03474, time: 687.43336 +[RESULT]: Val. Epoch: 5, summary_loss: 1.14709, final_score: 0.17283, time: 167.95696 + +2021-04-26T10:55:15.337585 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.21943, final_score: 0.04911, time: 679.65361 +[RESULT]: Val. Epoch: 6, summary_loss: 0.53038, final_score: 0.11538, time: 169.76675 + +2021-04-26T11:09:25.149731 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.20611, final_score: 0.04349, time: 687.85509 +[RESULT]: Val. Epoch: 7, summary_loss: 1.41937, final_score: 0.16733, time: 167.64857 + +2021-04-26T11:23:40.846091 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.22444, final_score: 0.05299, time: 708.42452 +[RESULT]: Val. Epoch: 8, summary_loss: 0.43820, final_score: 0.10140, time: 169.60399 + +2021-04-26T11:38:19.270173 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.21248, final_score: 0.04636, time: 693.60747 +[RESULT]: Val. Epoch: 9, summary_loss: 1.11879, final_score: 0.12887, time: 168.23868 + +2021-04-26T11:52:41.288880 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.23560, final_score: 0.05949, time: 694.66531 +[RESULT]: Val. Epoch: 10, summary_loss: 0.27473, final_score: 0.06543, time: 166.41243 + +2021-04-26T12:07:02.717860 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.22134, final_score: 0.05374, time: 710.90734 +[RESULT]: Val. Epoch: 11, summary_loss: 1.17226, final_score: 0.12787, time: 170.00023 + +2021-04-26T12:21:43.784268 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.25348, final_score: 0.07248, time: 706.53331 +[RESULT]: Val. Epoch: 12, summary_loss: 0.22927, final_score: 0.04895, time: 169.45037 + +2021-04-26T12:36:20.094650 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.23746, final_score: 0.06061, time: 702.52931 +[RESULT]: Val. Epoch: 13, summary_loss: 0.98835, final_score: 0.08392, time: 168.95457 + +2021-04-26T12:50:51.753688 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 14, summary_loss: 0.24163, final_score: 0.06461, time: 702.08159 +[RESULT]: Val. Epoch: 14, summary_loss: 0.45427, final_score: 0.06194, time: 169.10712 + +2021-04-26T13:05:23.098950 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 15, summary_loss: 0.24787, final_score: 0.06823, time: 708.19037 +[RESULT]: Val. Epoch: 15, summary_loss: 0.66149, final_score: 0.06494, time: 168.82795 + +2021-04-26T13:20:00.288864 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 16, summary_loss: 0.23327, final_score: 0.06186, time: 720.34999 +[RESULT]: Val. Epoch: 16, summary_loss: 0.25926, final_score: 0.04795, time: 167.92726 + +2021-04-26T13:34:48.723693 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 17, summary_loss: 0.22977, final_score: 0.05711, time: 691.75033 +[RESULT]: Val. Epoch: 17, summary_loss: 0.24632, final_score: 0.03946, time: 170.17429 + +2021-04-26T13:49:10.830311 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 18, summary_loss: 0.22224, final_score: 0.05361, time: 705.99420 +[RESULT]: Val. Epoch: 18, summary_loss: 0.50843, final_score: 0.06044, time: 169.89016 + +2021-04-26T14:03:46.887546 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 19, summary_loss: 0.22442, final_score: 0.05524, time: 706.63011 +[RESULT]: Val. Epoch: 19, summary_loss: 0.20327, final_score: 0.02947, time: 169.85269 + +2021-04-26T14:18:23.764746 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 20, summary_loss: 0.21478, final_score: 0.04874, time: 708.04086 +[RESULT]: Val. Epoch: 20, summary_loss: 0.39465, final_score: 0.04396, time: 169.36116 + +2021-04-26T14:33:01.347082 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 21, summary_loss: 0.21368, final_score: 0.04924, time: 702.95291 +[RESULT]: Val. Epoch: 21, summary_loss: 0.42117, final_score: 0.05594, time: 168.39942 + +2021-04-26T14:47:32.866204 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 22, summary_loss: 0.19370, final_score: 0.03837, time: 696.75437 +[RESULT]: Val. Epoch: 22, summary_loss: 0.26193, final_score: 0.03347, time: 167.18058 + +2021-04-26T15:01:56.955715 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 23, summary_loss: 0.18316, final_score: 0.03162, time: 705.06735 +[RESULT]: Val. Epoch: 23, summary_loss: 0.17692, final_score: 0.02797, time: 167.87533 + +2021-04-26T15:16:30.234447 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 24, summary_loss: 0.18070, final_score: 0.03174, time: 711.36618 +[RESULT]: Val. Epoch: 24, summary_loss: 0.28420, final_score: 0.02997, time: 169.17524 + +2021-04-26T15:31:10.936590 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 25, summary_loss: 0.17993, final_score: 0.03249, time: 715.84734 +[RESULT]: Val. Epoch: 25, summary_loss: 0.38916, final_score: 0.03447, time: 169.30674 + +2021-04-26T15:45:56.261283 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 26, summary_loss: 0.16155, final_score: 0.02087, time: 705.92641 +[RESULT]: Val. Epoch: 26, summary_loss: 0.30980, final_score: 0.02498, time: 170.61838 + +2021-04-26T16:00:32.965638 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 27, summary_loss: 0.16179, final_score: 0.02174, time: 701.34230 +[RESULT]: Val. Epoch: 27, summary_loss: 0.22600, final_score: 0.02747, time: 169.79041 + +2021-04-26T16:15:04.265750 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 28, summary_loss: 0.15644, final_score: 0.02062, time: 706.29722 +[RESULT]: Val. Epoch: 28, summary_loss: 0.19484, final_score: 0.02348, time: 169.34178 + +2021-04-26T16:29:40.064039 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 29, summary_loss: 0.15421, final_score: 0.01737, time: 722.88852 +[RESULT]: Val. Epoch: 29, summary_loss: 0.23174, final_score: 0.02398, time: 168.79899 + +2021-04-26T16:44:31.921504 +LR: 3.125e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 30, summary_loss: 0.15421, final_score: 0.01862, time: 702.64587 +[RESULT]: Val. Epoch: 30, summary_loss: 0.23230, final_score: 0.02448, time: 169.51447 +Fitter prepared. 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Device is cuda:0 + +2021-04-13T13:00:25.291620 +LR: 0.0005 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-13T13:08:45.564644 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.42323, final_score: 0.18283, time: 468.37462 +[RESULT]: Val. Epoch: 1, summary_loss: 1.68779, final_score: 0.40759, time: 112.16986 + +2021-04-13T13:18:26.615014 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.27664, final_score: 0.07736, time: 460.56769 +[RESULT]: Val. Epoch: 2, summary_loss: 1.11326, final_score: 0.34466, time: 108.51722 + +2021-04-13T13:27:56.056765 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.23485, final_score: 0.05436, time: 460.05409 +[RESULT]: Val. Epoch: 3, summary_loss: 1.51121, final_score: 0.32268, time: 110.42398 + +2021-04-13T13:37:26.730381 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.26064, final_score: 0.07136, time: 467.33574 +[RESULT]: Val. Epoch: 4, summary_loss: 1.11581, final_score: 0.33816, time: 110.32539 + +2021-04-13T13:47:04.628163 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.23661, final_score: 0.05899, time: 465.99016 +[RESULT]: Val. Epoch: 5, summary_loss: 1.13542, final_score: 0.32368, time: 109.64362 + +2021-04-13T13:56:40.444197 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.26177, final_score: 0.07411, time: 464.86002 +[RESULT]: Val. Epoch: 6, summary_loss: 1.05434, final_score: 0.28621, time: 109.70806 + +2021-04-13T14:06:15.422402 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.24772, final_score: 0.06598, time: 464.87695 +[RESULT]: Val. Epoch: 7, summary_loss: 1.06286, final_score: 0.28721, time: 109.30548 + +2021-04-13T14:15:49.786055 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.28460, final_score: 0.08598, time: 469.91484 +[RESULT]: Val. Epoch: 8, summary_loss: 1.20879, final_score: 0.36813, time: 112.38205 + +2021-04-13T14:25:32.267123 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.28085, final_score: 0.08560, time: 464.67462 +[RESULT]: Val. Epoch: 9, summary_loss: 0.57337, final_score: 0.23027, time: 109.73953 + +2021-04-13T14:35:07.072636 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.31847, final_score: 0.11122, time: 471.40729 +[RESULT]: Val. Epoch: 10, summary_loss: 0.61359, final_score: 0.22178, time: 109.72122 + +2021-04-13T14:44:48.412908 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.30471, final_score: 0.10010, time: 469.64367 +[RESULT]: Val. Epoch: 11, summary_loss: 0.97412, final_score: 0.29121, time: 110.63186 + +2021-04-13T14:54:28.929140 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.35073, final_score: 0.12709, time: 472.90650 +[RESULT]: Val. Epoch: 12, summary_loss: 0.82454, final_score: 0.19131, time: 111.17438 + +2021-04-13T15:04:13.204075 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.33424, final_score: 0.12059, time: 474.27531 +[RESULT]: Val. Epoch: 13, summary_loss: 1.42159, final_score: 0.29570, time: 110.91285 + +2021-04-13T15:13:58.815938 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.37317, final_score: 0.14571, time: 479.87929 +[RESULT]: Val. Epoch: 14, summary_loss: 0.64368, final_score: 0.19780, time: 109.80132 + +2021-04-13T15:23:48.731359 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.36444, final_score: 0.14696, time: 475.16461 +[RESULT]: Val. Epoch: 15, summary_loss: 1.02107, final_score: 0.21079, time: 110.72362 + +2021-04-13T15:33:34.780216 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.40310, final_score: 0.16796, time: 476.80413 +[RESULT]: Val. Epoch: 16, summary_loss: 1.14654, final_score: 0.22677, time: 110.26891 + +2021-04-13T15:43:22.046044 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.39199, final_score: 0.16521, time: 473.94077 +[RESULT]: Val. Epoch: 17, summary_loss: 0.62247, final_score: 0.18332, time: 111.40826 + +2021-04-13T15:53:07.588368 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.41350, final_score: 0.17796, time: 474.37207 +[RESULT]: Val. Epoch: 18, summary_loss: 0.38309, final_score: 0.14985, time: 112.48841 + +2021-04-13T16:02:54.811500 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.41202, final_score: 0.17758, time: 478.46110 +[RESULT]: Val. Epoch: 19, summary_loss: 0.77753, final_score: 0.17582, time: 110.84504 + +2021-04-13T16:12:44.315920 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.40698, final_score: 0.17258, time: 475.87078 +[RESULT]: Val. Epoch: 20, summary_loss: 0.47070, final_score: 0.16134, time: 110.66133 + +2021-04-13T16:22:31.049199 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.35896, final_score: 0.14434, time: 479.38055 +[RESULT]: Val. Epoch: 21, summary_loss: 0.55279, final_score: 0.14136, time: 110.82816 + +2021-04-13T16:32:21.473156 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.34660, final_score: 0.13372, time: 482.95989 +[RESULT]: Val. Epoch: 22, summary_loss: 0.58999, final_score: 0.15534, time: 109.87995 + +2021-04-13T16:42:14.510996 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.32070, final_score: 0.11835, time: 481.13461 +[RESULT]: Val. Epoch: 23, summary_loss: 0.38846, final_score: 0.11638, time: 110.49141 + +2021-04-13T16:52:06.332601 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.31173, final_score: 0.11160, time: 473.57437 +[RESULT]: Val. Epoch: 24, summary_loss: 0.32844, final_score: 0.11239, time: 109.80523 + +2021-04-13T17:01:50.079107 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.31596, final_score: 0.11535, time: 481.28372 +[RESULT]: Val. Epoch: 25, summary_loss: 0.34147, final_score: 0.11239, time: 110.32200 + +2021-04-13T17:11:41.852868 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.29869, final_score: 0.10510, time: 475.83167 +[RESULT]: Val. Epoch: 26, summary_loss: 0.56750, final_score: 0.13586, time: 110.11445 + +2021-04-13T17:21:28.097170 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.29782, final_score: 0.10472, time: 481.31235 +[RESULT]: Val. Epoch: 27, summary_loss: 0.42254, final_score: 0.13237, time: 109.69493 + +2021-04-13T17:31:19.305093 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.29625, final_score: 0.10110, time: 474.47014 +[RESULT]: Val. Epoch: 28, summary_loss: 0.36210, final_score: 0.11439, time: 109.08414 + +2021-04-13T17:41:03.050412 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.28081, final_score: 0.09310, time: 488.25298 +[RESULT]: Val. Epoch: 29, summary_loss: 0.45189, final_score: 0.11489, time: 109.37328 + +2021-04-13T17:51:00.873097 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.27820, final_score: 0.08948, time: 472.12445 +[RESULT]: Val. Epoch: 30, summary_loss: 0.42170, final_score: 0.11538, time: 112.00125 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..b32f1e77a8214e4a64ba9c1698c568ac80e02c35 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..cf93849d9b7020066472e52214b425aa125020a6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:df0b32a6f42594f3a6c54106925eb9a402c57ea0c02a9166f7e90d43c146f9aa +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..4b702b31ac8b5d77173df3d455fb1168f1d4da83 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2398885c53bb146537a65f28491f67a7af0ce0ce0c268d18a911a8b7a6f3f680 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f5c323140fb0f36b4c201a7f12d3b677e68c1147 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e80f10acb4548789b9c944ee586cdd78e386c05bfc764836d7b727eb190028b6 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..270524cbfe223d5b0c8314b8ced1eb2d2e814ce6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b62530d55a9a51438c0b5667d305f7c9398aebf67e843f2c50d700b58b0c7490 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..82daea9ca6decd9fba599df89f9da4e32586a1ce --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-04-15T07:51:54.808601 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.45485, final_score: 0.21482, time: 457.84298 +[RESULT]: Val. Epoch: 1, summary_loss: 1.30415, final_score: 0.44156, time: 109.36026 + +2021-04-15T08:01:22.430356 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.30962, final_score: 0.09735, time: 437.51393 +[RESULT]: Val. Epoch: 2, summary_loss: 1.91660, final_score: 0.39910, time: 106.24927 + +2021-04-15T08:10:26.409150 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.25558, final_score: 0.07086, time: 439.29720 +[RESULT]: Val. Epoch: 3, summary_loss: 1.94049, final_score: 0.39860, time: 107.67715 + +2021-04-15T08:19:33.558910 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.28423, final_score: 0.08673, time: 440.51807 +[RESULT]: Val. Epoch: 4, summary_loss: 1.83119, final_score: 0.39910, time: 107.26134 + +2021-04-15T08:28:41.572798 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.25178, final_score: 0.06436, time: 456.17909 +[RESULT]: Val. Epoch: 5, summary_loss: 1.70017, final_score: 0.38661, time: 107.40718 + +2021-04-15T08:38:05.351348 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.29160, final_score: 0.08985, time: 460.02076 +[RESULT]: Val. Epoch: 6, summary_loss: 1.32882, final_score: 0.38911, time: 107.90734 + +2021-04-15T08:47:33.437687 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.27620, final_score: 0.08023, time: 446.31064 +[RESULT]: Val. Epoch: 7, summary_loss: 2.72350, final_score: 0.41858, time: 107.53073 + +2021-04-15T08:56:47.479715 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.32947, final_score: 0.11485, time: 449.34126 +[RESULT]: Val. Epoch: 8, summary_loss: 1.11535, final_score: 0.35165, time: 108.14041 + +2021-04-15T09:06:05.340763 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.31097, final_score: 0.10110, time: 459.32956 +[RESULT]: Val. Epoch: 9, summary_loss: 1.77398, final_score: 0.37662, time: 106.21387 + +2021-04-15T09:15:31.085026 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.36320, final_score: 0.13934, time: 456.73215 +[RESULT]: Val. Epoch: 10, summary_loss: 1.23927, final_score: 0.34216, time: 106.96972 + +2021-04-15T09:24:54.983599 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.35706, final_score: 0.13184, time: 451.99358 +[RESULT]: Val. Epoch: 11, summary_loss: 1.22517, final_score: 0.29221, time: 109.28364 + +2021-04-15T09:34:16.546716 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.41225, final_score: 0.16771, time: 471.08088 +[RESULT]: Val. Epoch: 12, summary_loss: 0.92266, final_score: 0.29371, time: 108.57938 + +2021-04-15T09:43:56.613946 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.39633, final_score: 0.16733, time: 461.64806 +[RESULT]: Val. Epoch: 13, summary_loss: 1.11128, final_score: 0.30519, time: 105.72076 + +2021-04-15T09:53:24.180286 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.45628, final_score: 0.20557, time: 467.59621 +[RESULT]: Val. Epoch: 14, summary_loss: 0.89081, final_score: 0.32567, time: 106.29032 + +2021-04-15T10:02:58.565337 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.45308, final_score: 0.20132, time: 456.57598 +[RESULT]: Val. Epoch: 15, summary_loss: 0.97629, final_score: 0.26523, time: 108.02346 + +2021-04-15T10:12:23.346300 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.50301, final_score: 0.23107, time: 459.91355 +[RESULT]: Val. Epoch: 16, summary_loss: 0.64755, final_score: 0.27473, time: 107.64899 + +2021-04-15T10:21:51.253988 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.48561, final_score: 0.22669, time: 462.31668 +[RESULT]: Val. Epoch: 17, summary_loss: 0.91089, final_score: 0.27622, time: 108.15919 + +2021-04-15T10:31:21.923401 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.52496, final_score: 0.26081, time: 469.39386 +[RESULT]: Val. Epoch: 18, summary_loss: 0.79822, final_score: 0.27423, time: 108.60826 + +2021-04-15T10:41:00.123827 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.51822, final_score: 0.25344, time: 457.17897 +[RESULT]: Val. Epoch: 19, summary_loss: 0.48673, final_score: 0.22777, time: 105.69308 + +2021-04-15T10:50:23.399146 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.50823, final_score: 0.24694, time: 465.87453 +[RESULT]: Val. Epoch: 20, summary_loss: 0.50951, final_score: 0.23177, time: 106.04302 + +2021-04-15T10:59:55.478106 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.50236, final_score: 0.24119, time: 459.61589 +[RESULT]: Val. Epoch: 21, summary_loss: 1.65767, final_score: 0.34715, time: 109.59370 + +2021-04-15T11:09:24.875815 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.47203, final_score: 0.21882, time: 455.45161 +[RESULT]: Val. Epoch: 22, summary_loss: 0.48314, final_score: 0.22228, time: 106.77089 + +2021-04-15T11:18:47.476402 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.45958, final_score: 0.20920, time: 460.87027 +[RESULT]: Val. Epoch: 23, summary_loss: 0.57750, final_score: 0.21828, time: 108.53271 + +2021-04-15T11:28:17.071780 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.44700, final_score: 0.20320, time: 455.00002 +[RESULT]: Val. Epoch: 24, summary_loss: 0.59290, final_score: 0.22278, time: 108.34316 + +2021-04-15T11:37:40.612653 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.42549, final_score: 0.18845, time: 462.80188 +[RESULT]: Val. Epoch: 25, summary_loss: 0.73943, final_score: 0.21678, time: 107.20796 + +2021-04-15T11:47:10.812704 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.41011, final_score: 0.17608, time: 462.08325 +[RESULT]: Val. Epoch: 26, summary_loss: 0.45292, final_score: 0.19131, time: 108.00441 + +2021-04-15T11:56:41.289675 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.40923, final_score: 0.18133, time: 456.11564 +[RESULT]: Val. Epoch: 27, summary_loss: 0.58553, final_score: 0.19980, time: 106.09764 + +2021-04-15T12:06:03.775825 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.40042, final_score: 0.17258, time: 460.39776 +[RESULT]: Val. Epoch: 28, summary_loss: 0.79088, final_score: 0.20879, time: 108.73030 + +2021-04-15T12:15:33.117703 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.39719, final_score: 0.16208, time: 462.05352 +[RESULT]: Val. Epoch: 29, summary_loss: 0.43576, final_score: 0.16933, time: 107.68080 + +2021-04-15T12:25:03.259303 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.38826, final_score: 0.16033, time: 458.84551 +[RESULT]: Val. Epoch: 30, summary_loss: 0.48889, final_score: 0.18332, time: 106.83413 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..0c8bdfab655d192aee5ebe8cb1e3004bd5895925 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_2/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..ae997ed9124f5999093e5adbcb10cc72faa52258 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f7cf39d035041f2305cbdbdb308124b3bef6af9c853122dc2745bfa81f051ad0 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-028epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-028epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..65bc86381d30068e3d21a38e4a39e134fa87c7ba --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-028epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:69b09cb891d2248ec545d6507a04b9f8b1b17e308af5f0d8d484fa679686ff8f +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b170948dc3744df4805e50d6d1a55d1d42267373 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:059a0bb9333f2ecce223a61de52ca4272dd54a710280db5a1cee20402dc56b95 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..4033f3fd2f422308e73e144f3288700c5e08e664 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:febb7648c03bd10dc00ad22a588681fae94953a4464ed2066e34125266e6b341 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..8a1823f0d7768e7c118b2312537584741ec1a428 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/log.txt @@ -0,0 +1,227 @@ +Fitter prepared. Device is cuda:0 + +2021-04-19T06:46:36.752895 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.44328, final_score: 0.20295, time: 773.30344 +[RESULT]: Val. Epoch: 1, summary_loss: 1.43230, final_score: 0.42557, time: 179.00703 + +2021-04-19T07:02:29.456993 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.31864, final_score: 0.10060, time: 758.38839 +[RESULT]: Val. Epoch: 2, summary_loss: 1.67968, final_score: 0.41958, time: 197.06500 + +2021-04-19T07:18:25.109909 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.26666, final_score: 0.07436, time: 749.78796 +[RESULT]: Val. Epoch: 3, summary_loss: 1.64414, final_score: 0.40609, time: 187.74909 + +2021-04-19T07:34:02.875541 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.29336, final_score: 0.08973, time: 741.09868 +[RESULT]: Val. Epoch: 4, summary_loss: 1.42515, final_score: 0.40959, time: 176.15598 + +2021-04-19T07:49:20.537097 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.26527, final_score: 0.07973, time: 742.46101 +[RESULT]: Val. Epoch: 5, summary_loss: 2.10666, final_score: 0.41508, time: 187.95412 + +2021-04-19T08:04:51.138152 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +Fitter prepared. Device is cuda:0 + +2021-04-19T18:41:08.642639 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.47737, final_score: 0.23207, time: 786.14268 +[RESULT]: Val. Epoch: 1, summary_loss: 1.12468, final_score: 0.43906, time: 172.54792 + +2021-04-19T18:57:07.731678 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.33665, final_score: 0.11560, time: 729.55439 +[RESULT]: Val. Epoch: 2, summary_loss: 1.16209, final_score: 0.42607, time: 169.69648 + +2021-04-19T19:12:07.183369 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.28452, final_score: 0.08735, time: 734.54312 +[RESULT]: Val. Epoch: 3, summary_loss: 1.31979, final_score: 0.41508, time: 169.41596 + +2021-04-19T19:27:11.387317 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.30609, final_score: 0.09810, time: 751.90603 +[RESULT]: Val. Epoch: 4, summary_loss: 1.81883, final_score: 0.41459, time: 169.69129 + +2021-04-19T19:42:33.176783 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.28051, final_score: 0.08260, time: 730.95309 +[RESULT]: Val. Epoch: 5, summary_loss: 1.57500, final_score: 0.39810, time: 167.99674 + +2021-04-19T19:57:32.309293 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.31937, final_score: 0.10722, time: 735.50927 +[RESULT]: Val. Epoch: 6, summary_loss: 1.34070, final_score: 0.40110, time: 167.91637 + +2021-04-19T20:12:35.942021 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.30655, final_score: 0.10222, time: 738.08575 +[RESULT]: Val. Epoch: 7, summary_loss: 1.77714, final_score: 0.41159, time: 166.89743 + +2021-04-19T20:27:41.126229 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.37113, final_score: 0.14059, time: 747.11871 +[RESULT]: Val. Epoch: 8, summary_loss: 1.54774, final_score: 0.38861, time: 166.70131 + +2021-04-19T20:42:55.167645 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.35099, final_score: 0.12884, time: 734.29406 +[RESULT]: Val. Epoch: 9, summary_loss: 1.18642, final_score: 0.39610, time: 165.27648 + +2021-04-19T20:57:54.921690 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.40693, final_score: 0.16546, time: 751.38886 +[RESULT]: Val. Epoch: 10, summary_loss: 0.80724, final_score: 0.37063, time: 167.21007 + +2021-04-19T21:13:13.924623 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39955, final_score: 0.16246, time: 742.89235 +[RESULT]: Val. Epoch: 11, summary_loss: 0.95691, final_score: 0.36663, time: 165.42960 + +2021-04-19T21:28:22.441901 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.46854, final_score: 0.21545, time: 733.80649 +[RESULT]: Val. Epoch: 12, summary_loss: 0.81337, final_score: 0.35365, time: 165.93953 + +2021-04-19T21:43:22.417313 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44726, final_score: 0.19870, time: 735.38461 +[RESULT]: Val. Epoch: 13, summary_loss: 0.66380, final_score: 0.35664, time: 164.95873 + +2021-04-19T21:58:23.134346 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.51624, final_score: 0.24919, time: 735.93973 +[RESULT]: Val. Epoch: 14, summary_loss: 0.85946, final_score: 0.34665, time: 163.64824 + +2021-04-19T22:13:22.897019 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.49864, final_score: 0.23732, time: 729.73192 +[RESULT]: Val. Epoch: 15, summary_loss: 0.85448, final_score: 0.32667, time: 165.28364 + +2021-04-19T22:28:18.090176 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.55939, final_score: 0.29018, time: 743.37867 +[RESULT]: Val. Epoch: 16, summary_loss: 0.71481, final_score: 0.35015, time: 165.98252 + +2021-04-19T22:43:27.628625 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.54665, final_score: 0.28318, time: 742.92577 +[RESULT]: Val. Epoch: 17, summary_loss: 0.62211, final_score: 0.32817, time: 165.02472 + +2021-04-19T22:58:35.938406 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.58210, final_score: 0.31717, time: 735.08998 +[RESULT]: Val. Epoch: 18, summary_loss: 0.76191, final_score: 0.32767, time: 164.51817 + +2021-04-19T23:13:35.741652 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.57830, final_score: 0.31092, time: 741.18757 +[RESULT]: Val. Epoch: 19, summary_loss: 0.59845, final_score: 0.31269, time: 163.44419 + +2021-04-19T23:28:40.769838 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.57512, final_score: 0.30892, time: 731.55611 +[RESULT]: Val. Epoch: 20, summary_loss: 0.55676, final_score: 0.27572, time: 164.86913 + +2021-04-19T23:43:37.540769 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.56312, final_score: 0.29980, time: 741.89931 +[RESULT]: Val. Epoch: 21, summary_loss: 0.62585, final_score: 0.32368, time: 165.12319 + +2021-04-19T23:58:44.730220 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.56126, final_score: 0.29580, time: 724.56501 +[RESULT]: Val. Epoch: 22, summary_loss: 0.65063, final_score: 0.30270, time: 165.76097 + +2021-04-20T00:13:35.225637 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.51954, final_score: 0.26293, time: 736.41555 +[RESULT]: Val. Epoch: 23, summary_loss: 0.56405, final_score: 0.26573, time: 166.80786 + +2021-04-20T00:28:38.634538 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.50703, final_score: 0.25131, time: 741.08236 +[RESULT]: Val. Epoch: 24, summary_loss: 0.53809, final_score: 0.24775, time: 164.93450 + +2021-04-20T00:43:44.979860 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.50095, final_score: 0.24619, time: 724.57404 +[RESULT]: Val. Epoch: 25, summary_loss: 0.66300, final_score: 0.26274, time: 166.55208 + +2021-04-20T00:58:36.276382 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.49023, final_score: 0.23519, time: 725.93102 +[RESULT]: Val. Epoch: 26, summary_loss: 0.51967, final_score: 0.23676, time: 165.96945 + +2021-04-20T01:13:28.482509 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.48155, final_score: 0.22944, time: 727.35663 +[RESULT]: Val. Epoch: 27, summary_loss: 0.53949, final_score: 0.25175, time: 163.98416 + +2021-04-20T01:28:19.991168 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.47842, final_score: 0.23157, time: 742.50146 +[RESULT]: Val. Epoch: 28, summary_loss: 0.49954, final_score: 0.22577, time: 164.53107 + +2021-04-20T01:43:27.356441 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.47140, final_score: 0.22269, time: 722.34062 +[RESULT]: Val. Epoch: 29, summary_loss: 0.48160, final_score: 0.21978, time: 166.47781 + +2021-04-20T01:58:16.498841 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.46083, final_score: 0.21495, time: 742.54762 +[RESULT]: Val. Epoch: 30, summary_loss: 0.51615, final_score: 0.23926, time: 164.36111 +Fitter prepared. Device is cuda:0 + +2021-04-28T09:36:32.682731 +LR: 0.00025 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 31, summary_loss: 0.65854, final_score: 0.39628, time: 785.03612 +[RESULT]: Val. Epoch: 31, summary_loss: 0.70610, final_score: 0.40160, time: 166.26262 + +2021-04-28T09:52:24.228144 +LR: 0.00025 +Emb_rate: 0.18000000000000002 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..a0ff0fab62bf46537bf8830543c5781a3ca9d713 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-030epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-030epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b4816f170f8460ca6b9d67041e0d48260d1e363c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-030epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:32734d9727fef8bc43ada9dd7b97c69e418bd9e3999e644a8ea141fa9a0f3a6e +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-032epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-032epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..3cf2013047ee56c79013eae0117c732d0388fc6d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-032epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2eaff43abc22e8c3ce0902f5cf5240d396701e5749fc87db3d39c95173fe5a5b +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-036epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-036epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..56672d47a9ee366f238260a9894e01d9da88a486 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/best-checkpoint-036epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:37ee2c2fd155afa7469f613d15cf091142de91e81ea3be4c2018b7f021eb8521 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..965e89aa12c7d59eee475612b0792b57d6b385ba --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:50e82ad9783f60b506d6e6948ab65c73a677e751604887905f5119570387497b +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..9d48e26e181bee4c0a2cd341deb05112cd8c5391 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/log.txt @@ -0,0 +1,240 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:56:43.155091 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.44540, final_score: 0.20482, time: 974.10172 +[RESULT]: Val. Epoch: 1, summary_loss: 1.33332, final_score: 0.50000, time: 260.97505 + +2021-04-26T10:17:18.725432 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.32684, final_score: 0.10997, time: 1014.76367 +[RESULT]: Val. Epoch: 2, summary_loss: 1.75346, final_score: 0.50000, time: 210.29546 + +2021-04-26T10:37:43.952245 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27220, final_score: 0.07773, time: 1016.25265 +[RESULT]: Val. Epoch: 3, summary_loss: 2.04468, final_score: 0.49950, time: 259.89722 + +2021-04-26T10:59:00.321411 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.30327, final_score: 0.09410, time: 965.67374 +[RESULT]: Val. Epoch: 4, summary_loss: 2.22072, final_score: 0.50000, time: 244.91394 + +2021-04-26T11:19:11.130654 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.26480, final_score: 0.07748, time: 949.69133 +[RESULT]: Val. Epoch: 5, summary_loss: 1.73163, final_score: 0.49850, time: 227.18994 + +2021-04-26T11:38:48.188350 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.32203, final_score: 0.10647, time: 1014.66729 +[RESULT]: Val. Epoch: 6, summary_loss: 1.36024, final_score: 0.49351, time: 228.81075 + +2021-04-26T11:59:31.834078 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.30068, final_score: 0.09773, time: 1006.77130 +[RESULT]: Val. Epoch: 7, summary_loss: 1.76627, final_score: 0.50000, time: 253.39142 + +2021-04-26T12:20:32.156784 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.35176, final_score: 0.13184, time: 1019.66192 +[RESULT]: Val. Epoch: 8, summary_loss: 2.60219, final_score: 0.50000, time: 222.84421 + +2021-04-26T12:41:14.872549 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.33492, final_score: 0.11972, time: 1021.42626 +[RESULT]: Val. Epoch: 9, summary_loss: 1.32545, final_score: 0.50000, time: 241.85572 + +2021-04-26T13:02:18.566082 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.41982, final_score: 0.17658, time: 1049.05175 +[RESULT]: Val. Epoch: 10, summary_loss: 2.29335, final_score: 0.50000, time: 222.40633 + +2021-04-26T13:23:30.246540 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39650, final_score: 0.16033, time: 960.96584 +[RESULT]: Val. Epoch: 11, summary_loss: 1.31397, final_score: 0.49950, time: 218.58543 + +2021-04-26T13:43:10.208082 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.45975, final_score: 0.20682, time: 1015.14738 +[RESULT]: Val. Epoch: 12, summary_loss: 1.66180, final_score: 0.50000, time: 246.17360 + +2021-04-26T14:04:11.716819 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44748, final_score: 0.19358, time: 961.22777 +[RESULT]: Val. Epoch: 13, summary_loss: 2.11723, final_score: 0.50000, time: 257.71829 + +2021-04-26T14:24:30.858173 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.51250, final_score: 0.24881, time: 992.03841 +[RESULT]: Val. Epoch: 14, summary_loss: 1.48539, final_score: 0.50000, time: 235.74129 + +2021-04-26T14:44:58.851386 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.50448, final_score: 0.24356, time: 1006.89527 +[RESULT]: Val. Epoch: 15, summary_loss: 1.43534, final_score: 0.49950, time: 246.16029 + +2021-04-26T15:05:52.135473 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.56305, final_score: 0.29693, time: 999.86398 +[RESULT]: Val. Epoch: 16, summary_loss: 1.13516, final_score: 0.49950, time: 250.29098 + +2021-04-26T15:26:42.760264 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.54559, final_score: 0.27768, time: 1055.16345 +[RESULT]: Val. Epoch: 17, summary_loss: 1.33832, final_score: 0.49950, time: 240.87720 + +2021-04-26T15:48:18.999991 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.59440, final_score: 0.32829, time: 1023.63443 +[RESULT]: Val. Epoch: 18, summary_loss: 1.18218, final_score: 0.49950, time: 236.53697 + +2021-04-26T16:09:19.420815 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.59012, final_score: 0.31980, time: 1004.93828 +[RESULT]: Val. Epoch: 19, summary_loss: 1.15869, final_score: 0.50000, time: 240.29869 + +2021-04-26T16:30:04.850983 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.62203, final_score: 0.35779, time: 1002.86017 +[RESULT]: Val. Epoch: 20, summary_loss: 0.96110, final_score: 0.49950, time: 214.66728 + +2021-04-26T16:50:22.857595 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 21, summary_loss: 0.61485, final_score: 0.34779, time: 1014.84030 +[RESULT]: Val. Epoch: 21, summary_loss: 1.10856, final_score: 0.49850, time: 256.64491 + +2021-04-26T17:11:34.518804 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.63623, final_score: 0.37341, time: 1032.32735 +[RESULT]: Val. Epoch: 22, summary_loss: 0.76973, final_score: 0.45704, time: 233.42484 + +2021-04-26T17:32:40.669613 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.61275, final_score: 0.33992, time: 1028.63575 +[RESULT]: Val. Epoch: 23, summary_loss: 1.13348, final_score: 0.40160, time: 243.41275 + +2021-04-26T17:53:52.926331 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.56040, final_score: 0.28155, time: 959.31886 +[RESULT]: Val. Epoch: 24, summary_loss: 0.58998, final_score: 0.22627, time: 216.86012 + +2021-04-26T18:13:29.454090 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 25, summary_loss: 0.48453, final_score: 0.21907, time: 937.02140 +[RESULT]: Val. Epoch: 25, summary_loss: 0.46243, final_score: 0.18981, time: 208.07738 + +2021-04-26T18:32:34.875176 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.44727, final_score: 0.18833, time: 998.25177 +[RESULT]: Val. Epoch: 26, summary_loss: 0.53899, final_score: 0.19381, time: 221.74335 + +2021-04-26T18:52:55.031119 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 27, summary_loss: 0.42733, final_score: 0.18070, time: 973.65151 +[RESULT]: Val. Epoch: 27, summary_loss: 0.52402, final_score: 0.19281, time: 214.50564 + +2021-04-26T19:12:43.391003 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.41319, final_score: 0.17008, time: 957.65060 +[RESULT]: Val. Epoch: 28, summary_loss: 0.56075, final_score: 0.15085, time: 205.47115 + +2021-04-26T19:32:06.679603 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 29, summary_loss: 0.40066, final_score: 0.16046, time: 987.14075 +[RESULT]: Val. Epoch: 29, summary_loss: 0.38681, final_score: 0.13087, time: 209.04230 + +2021-04-26T19:52:03.208789 +LR: 0.0005 +Emb_rate: 0.2058911320946491 +Fitter prepared. Device is cuda:0 + +2021-04-28T10:06:53.044264 +LR: 0.0005 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.37668, final_score: 0.14246, time: 775.52208 +[RESULT]: Val. Epoch: 30, summary_loss: 0.35193, final_score: 0.12088, time: 171.82202 + +2021-04-28T10:22:41.188794 +LR: 0.0005 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 31, summary_loss: 0.37518, final_score: 0.14909, time: 749.24501 +[RESULT]: Val. Epoch: 31, summary_loss: 0.57143, final_score: 0.14036, time: 171.01923 + +2021-04-28T10:38:01.647263 +LR: 0.0005 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 32, summary_loss: 0.36947, final_score: 0.14159, time: 729.83548 +[RESULT]: Val. Epoch: 32, summary_loss: 0.34794, final_score: 0.12288, time: 169.83013 + +2021-04-28T10:53:01.758891 +LR: 0.0005 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 33, summary_loss: 0.35906, final_score: 0.13284, time: 734.20498 +[RESULT]: Val. Epoch: 33, summary_loss: 0.34834, final_score: 0.11888, time: 172.21820 + +2021-04-28T11:08:08.390415 +LR: 0.0005 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 34, summary_loss: 0.35179, final_score: 0.13134, time: 751.98429 +[RESULT]: Val. Epoch: 34, summary_loss: 0.42885, final_score: 0.11988, time: 170.46193 + +2021-04-28T11:23:31.032670 +LR: 0.0005 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 35, summary_loss: 0.34333, final_score: 0.12572, time: 749.46733 +[RESULT]: Val. Epoch: 35, summary_loss: 0.52539, final_score: 0.12438, time: 172.56363 + +2021-04-28T11:38:53.221646 +LR: 0.0005 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 36, summary_loss: 0.34328, final_score: 0.12459, time: 741.96778 +[RESULT]: Val. Epoch: 36, summary_loss: 0.33860, final_score: 0.10889, time: 169.80062 + +2021-04-28T11:54:05.392306 +LR: 0.0005 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 37, summary_loss: 0.33970, final_score: 0.12184, time: 719.92210 +[RESULT]: Val. Epoch: 37, summary_loss: 0.35776, final_score: 0.11888, time: 170.40954 + +2021-04-28T12:08:55.890067 +LR: 0.0005 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 38, summary_loss: 0.33934, final_score: 0.12472, time: 737.44173 +[RESULT]: Val. Epoch: 38, summary_loss: 0.34220, final_score: 0.11538, time: 171.74103 + +2021-04-28T12:24:05.242933 +LR: 0.0005 +Emb_rate: 0.11809800000000004 +[RESULT]: Train. Epoch: 39, summary_loss: 0.33296, final_score: 0.11910, time: 738.70743 +[RESULT]: Val. Epoch: 39, summary_loss: 0.42958, final_score: 0.13187, time: 175.30044 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..613314113296c21d911c2144486fbec3637c2b42 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..aed95129445bc289f8937728fd0817dc8f324e31 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7539e2c6d5ec07f9b45f0bb497e690f2242630dae990e23a881caeda728759c0 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-028epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-028epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..4ae67ee7499b201613387134a4e0e444b07ba066 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-028epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7ede98b082583034ddc77a0d5a941d6722391e3c0478b81925e27effebc652db +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..5e4a2f9f3638ba82e0488b918e115f096f9211cf --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e403de00ac247f165b152f79174b41d985cfdfe35de5a54081c3e059bdb6961d +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..fabda8eda4c7c350682e97279addac03a04e2b6d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:85ac97ac54acfdf442f94824e99d036c0ba56f69a9f533a7912d03ca6485d195 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d7013695c3975beebea2f8fbc23891b23eabb7f8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_3_0.2/log.txt @@ -0,0 +1,182 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:31:40.859434 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.46403, final_score: 0.22082, time: 759.89895 +[RESULT]: Val. Epoch: 1, summary_loss: 1.61314, final_score: 0.49800, time: 181.90306 + +2021-04-26T09:47:22.981534 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.31024, final_score: 0.09885, time: 775.72641 +[RESULT]: Val. Epoch: 2, summary_loss: 1.65319, final_score: 0.49950, time: 232.63727 + +2021-04-26T10:04:11.538851 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27014, final_score: 0.07411, time: 813.44190 +[RESULT]: Val. Epoch: 3, summary_loss: 2.84616, final_score: 0.49850, time: 187.82921 + +2021-04-26T10:20:53.022280 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.28595, final_score: 0.08735, time: 768.53532 +[RESULT]: Val. Epoch: 4, summary_loss: 1.85338, final_score: 0.49950, time: 189.88578 + +2021-04-26T10:36:51.640278 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27080, final_score: 0.08098, time: 773.28084 +[RESULT]: Val. Epoch: 5, summary_loss: 2.28717, final_score: 0.49850, time: 188.78612 + +2021-04-26T10:52:53.859579 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.31102, final_score: 0.10360, time: 779.95394 +[RESULT]: Val. Epoch: 6, summary_loss: 1.68300, final_score: 0.49950, time: 188.43408 + +2021-04-26T11:09:02.416547 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.29646, final_score: 0.09585, time: 770.78542 +[RESULT]: Val. Epoch: 7, summary_loss: 3.77968, final_score: 0.49950, time: 188.12409 + +2021-04-26T11:25:01.487209 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.35786, final_score: 0.13084, time: 783.41525 +[RESULT]: Val. Epoch: 8, summary_loss: 1.98318, final_score: 0.49900, time: 191.41373 + +2021-04-26T11:41:16.485458 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.33607, final_score: 0.11847, time: 776.85529 +[RESULT]: Val. Epoch: 9, summary_loss: 1.32060, final_score: 0.49900, time: 190.68007 + +2021-04-26T11:57:24.363894 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.40223, final_score: 0.16158, time: 804.46131 +[RESULT]: Val. Epoch: 10, summary_loss: 1.63675, final_score: 0.49850, time: 186.08549 + +2021-04-26T12:13:55.073389 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39079, final_score: 0.15459, time: 782.17791 +[RESULT]: Val. Epoch: 11, summary_loss: 2.20134, final_score: 0.49900, time: 192.90415 + +2021-04-26T12:30:10.303854 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.45654, final_score: 0.20295, time: 793.44857 +[RESULT]: Val. Epoch: 12, summary_loss: 1.46025, final_score: 0.49850, time: 189.91426 + +2021-04-26T12:46:33.840658 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44461, final_score: 0.19520, time: 792.46565 +[RESULT]: Val. Epoch: 13, summary_loss: 1.77451, final_score: 0.49950, time: 190.92163 + +2021-04-26T13:02:57.425121 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.51352, final_score: 0.24894, time: 783.14103 +[RESULT]: Val. Epoch: 14, summary_loss: 1.39658, final_score: 0.49800, time: 187.30109 + +2021-04-26T13:19:08.019154 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.50105, final_score: 0.23694, time: 778.72723 +[RESULT]: Val. Epoch: 15, summary_loss: 1.44828, final_score: 0.49700, time: 181.42484 + +2021-04-26T13:35:08.338803 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.55435, final_score: 0.28618, time: 784.74546 +[RESULT]: Val. Epoch: 16, summary_loss: 1.16943, final_score: 0.49700, time: 190.71833 + +2021-04-26T13:51:24.209370 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.54921, final_score: 0.28430, time: 807.37053 +[RESULT]: Val. Epoch: 17, summary_loss: 1.21956, final_score: 0.49750, time: 191.50704 + +2021-04-26T14:08:03.240725 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.59846, final_score: 0.33654, time: 809.95386 +[RESULT]: Val. Epoch: 18, summary_loss: 0.92157, final_score: 0.49151, time: 190.26253 + +2021-04-26T14:24:43.829713 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.58988, final_score: 0.32154, time: 802.72294 +[RESULT]: Val. Epoch: 19, summary_loss: 1.13600, final_score: 0.49151, time: 185.51690 + +2021-04-26T14:41:12.282409 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.62349, final_score: 0.36266, time: 838.14583 +[RESULT]: Val. Epoch: 20, summary_loss: 1.25946, final_score: 0.48751, time: 190.61583 + +2021-04-26T14:58:21.240351 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 21, summary_loss: 0.61602, final_score: 0.34754, time: 802.37367 +[RESULT]: Val. Epoch: 21, summary_loss: 0.95338, final_score: 0.47852, time: 185.29157 + +2021-04-26T15:14:49.116964 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.64034, final_score: 0.37391, time: 798.39661 +[RESULT]: Val. Epoch: 22, summary_loss: 0.73949, final_score: 0.45455, time: 219.19994 + +2021-04-26T15:31:47.091854 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.63362, final_score: 0.36591, time: 789.67024 +[RESULT]: Val. Epoch: 23, summary_loss: 0.75492, final_score: 0.43457, time: 195.85755 + +2021-04-26T15:48:12.772739 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.61238, final_score: 0.33754, time: 796.00332 +[RESULT]: Val. Epoch: 24, summary_loss: 0.56623, final_score: 0.26474, time: 187.96069 + +2021-04-26T16:04:37.060800 +LR: 0.0005 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 25, summary_loss: 0.53632, final_score: 0.26368, time: 802.97043 +[RESULT]: Val. Epoch: 25, summary_loss: 1.10342, final_score: 0.24126, time: 171.64869 + +2021-04-26T16:20:51.872425 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.48526, final_score: 0.21795, time: 794.00560 +[RESULT]: Val. Epoch: 26, summary_loss: 0.62376, final_score: 0.20729, time: 189.38328 + +2021-04-26T16:37:16.329785 +LR: 0.0005 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 27, summary_loss: 0.45736, final_score: 0.19795, time: 781.05814 +[RESULT]: Val. Epoch: 27, summary_loss: 0.72108, final_score: 0.20480, time: 188.77410 + +2021-04-26T16:53:26.362901 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.42441, final_score: 0.17771, time: 818.30639 +[RESULT]: Val. Epoch: 28, summary_loss: 0.41498, final_score: 0.16683, time: 186.70602 + +2021-04-26T17:10:11.706348 +LR: 0.0005 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 29, summary_loss: 0.41186, final_score: 0.16733, time: 831.57560 +[RESULT]: Val. Epoch: 29, summary_loss: 0.36380, final_score: 0.12737, time: 199.31931 + +2021-04-26T17:27:23.014362 +LR: 0.0005 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 30, summary_loss: 0.38676, final_score: 0.14884, time: 815.29753 +[RESULT]: Val. Epoch: 30, summary_loss: 0.53831, final_score: 0.12737, time: 186.39940 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:32:25.773820 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.44186, final_score: 0.20557, time: 726.58946 +[RESULT]: Val. Epoch: 1, summary_loss: 1.32824, final_score: 0.47752, time: 169.21040 + +2021-04-26T09:47:22.003863 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.33012, final_score: 0.11272, time: 719.78873 +[RESULT]: Val. Epoch: 2, summary_loss: 1.62371, final_score: 0.47802, time: 172.63492 + +2021-04-26T10:02:14.614542 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27330, final_score: 0.07923, time: 724.38541 +[RESULT]: Val. Epoch: 3, summary_loss: 1.59675, final_score: 0.47952, time: 168.06914 + +2021-04-26T10:17:07.224938 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.30432, final_score: 0.09823, time: 726.86723 +[RESULT]: Val. Epoch: 4, summary_loss: 1.11498, final_score: 0.48452, time: 170.86186 + +2021-04-26T10:32:05.309063 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27869, final_score: 0.08610, time: 723.85958 +[RESULT]: Val. Epoch: 5, summary_loss: 2.80902, final_score: 0.48651, time: 170.43473 + +2021-04-26T10:46:59.792585 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.31909, final_score: 0.10510, time: 726.36373 +[RESULT]: Val. Epoch: 6, summary_loss: 1.95219, final_score: 0.47502, time: 170.76251 + +2021-04-26T11:01:57.073949 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.31428, final_score: 0.10497, time: 755.13758 +[RESULT]: Val. Epoch: 7, summary_loss: 2.35144, final_score: 0.48402, time: 172.19957 + +2021-04-26T11:17:24.613942 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.36128, final_score: 0.13347, time: 747.07605 +[RESULT]: Val. Epoch: 8, summary_loss: 1.87567, final_score: 0.49051, time: 169.25372 + +2021-04-26T11:32:41.136252 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.34462, final_score: 0.12422, time: 746.25183 +[RESULT]: Val. Epoch: 9, summary_loss: 1.03171, final_score: 0.45954, time: 168.46109 + +2021-04-26T11:47:56.216584 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.40307, final_score: 0.16408, time: 727.76973 +[RESULT]: Val. Epoch: 10, summary_loss: 1.48269, final_score: 0.46953, time: 171.02564 + +2021-04-26T12:02:55.173273 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.40191, final_score: 0.16421, time: 738.71602 +[RESULT]: Val. Epoch: 11, summary_loss: 1.57936, final_score: 0.46104, time: 169.55578 + +2021-04-26T12:18:03.641863 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.46288, final_score: 0.20770, time: 735.42863 +[RESULT]: Val. Epoch: 12, summary_loss: 0.84615, final_score: 0.46553, time: 171.60854 + +2021-04-26T12:33:11.104235 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44869, final_score: 0.19683, time: 726.43879 +[RESULT]: Val. Epoch: 13, summary_loss: 1.52270, final_score: 0.45754, time: 168.81345 + +2021-04-26T12:48:06.554243 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.51907, final_score: 0.25794, time: 738.16803 +[RESULT]: Val. Epoch: 14, summary_loss: 1.20560, final_score: 0.45005, time: 170.57404 + +2021-04-26T13:03:15.492396 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.51171, final_score: 0.25044, time: 736.44293 +[RESULT]: Val. Epoch: 15, summary_loss: 0.97018, final_score: 0.43207, time: 169.98266 + +2021-04-26T13:18:22.101836 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.55723, final_score: 0.28468, time: 739.76696 +[RESULT]: Val. Epoch: 16, summary_loss: 0.83471, final_score: 0.42458, time: 169.17455 + +2021-04-26T13:33:31.413830 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.55387, final_score: 0.28455, time: 746.91899 +[RESULT]: Val. Epoch: 17, summary_loss: 0.78863, final_score: 0.41858, time: 170.01842 + +2021-04-26T13:48:48.764767 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.59459, final_score: 0.32467, time: 767.31851 +[RESULT]: Val. Epoch: 18, summary_loss: 0.91662, final_score: 0.41359, time: 169.68538 + +2021-04-26T14:04:25.969865 +LR: 0.0005 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.59151, final_score: 0.32804, time: 738.71136 +[RESULT]: Val. Epoch: 19, summary_loss: 0.65755, final_score: 0.38961, time: 171.84713 + +2021-04-26T14:19:36.894703 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.61353, final_score: 0.34666, time: 739.11555 +[RESULT]: Val. Epoch: 20, summary_loss: 0.75230, final_score: 0.38412, time: 170.99122 + +2021-04-26T14:34:47.184122 +LR: 0.0005 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 21, summary_loss: 0.59314, final_score: 0.31680, time: 761.97549 +[RESULT]: Val. Epoch: 21, summary_loss: 0.64665, final_score: 0.32018, time: 171.29907 + +2021-04-26T14:50:20.823756 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.56186, final_score: 0.28518, time: 746.42617 +[RESULT]: Val. Epoch: 22, summary_loss: 0.47929, final_score: 0.20979, time: 168.71790 + +2021-04-26T15:05:36.300520 +LR: 0.0005 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.50654, final_score: 0.23532, time: 755.18688 +[RESULT]: Val. Epoch: 23, summary_loss: 0.46920, final_score: 0.20729, time: 170.73649 + +2021-04-26T15:21:02.574513 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 24, summary_loss: 0.47049, final_score: 0.20620, time: 740.08124 +[RESULT]: Val. Epoch: 24, summary_loss: 0.42066, final_score: 0.14885, time: 168.79011 + +2021-04-26T15:36:11.768475 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 25, summary_loss: 0.45142, final_score: 0.19533, time: 754.63597 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69186, final_score: 0.20030, time: 172.60389 + +2021-04-26T15:51:39.185389 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 26, summary_loss: 0.43253, final_score: 0.17658, time: 755.08008 +[RESULT]: Val. Epoch: 26, summary_loss: 0.37739, final_score: 0.12338, time: 170.36705 + +2021-04-26T16:07:04.959096 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 27, summary_loss: 0.42052, final_score: 0.16971, time: 735.61372 +[RESULT]: Val. Epoch: 27, summary_loss: 0.44784, final_score: 0.14635, time: 169.69027 + +2021-04-26T16:22:10.451656 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 28, summary_loss: 0.41430, final_score: 0.16746, time: 745.27764 +[RESULT]: Val. Epoch: 28, summary_loss: 0.38172, final_score: 0.13586, time: 170.62299 + +2021-04-26T16:37:26.511860 +LR: 0.00025 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 29, summary_loss: 0.38227, final_score: 0.14896, time: 742.51501 +[RESULT]: Val. Epoch: 29, summary_loss: 0.35389, final_score: 0.12038, time: 169.31000 + +2021-04-26T16:52:38.770582 +LR: 0.00025 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 30, summary_loss: 0.36777, final_score: 0.13797, time: 751.71544 +[RESULT]: Val. Epoch: 30, summary_loss: 0.37508, final_score: 0.13237, time: 169.34574 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:34:09.844401 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.45487, final_score: 0.21707, time: 755.58496 +[RESULT]: Val. Epoch: 1, summary_loss: 0.98446, final_score: 0.37013, time: 164.53891 + +2021-04-26T09:49:30.356170 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.31693, final_score: 0.10285, time: 690.49379 +[RESULT]: Val. Epoch: 2, summary_loss: 1.17790, final_score: 0.30919, time: 165.84205 + +2021-04-26T10:03:46.913840 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.25595, final_score: 0.06848, time: 691.61054 +[RESULT]: Val. Epoch: 3, summary_loss: 1.44489, final_score: 0.32967, time: 166.44214 + +2021-04-26T10:18:05.162674 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.28381, final_score: 0.08623, time: 696.73522 +[RESULT]: Val. Epoch: 4, summary_loss: 1.17660, final_score: 0.30120, time: 164.11633 + +2021-04-26T10:32:26.203448 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.26923, final_score: 0.07923, time: 695.69807 +[RESULT]: Val. Epoch: 5, summary_loss: 1.57745, final_score: 0.32218, time: 164.38646 + +2021-04-26T10:46:46.494665 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.32264, final_score: 0.10947, time: 693.82402 +[RESULT]: Val. Epoch: 6, summary_loss: 1.01428, final_score: 0.32068, time: 167.98240 + +2021-04-26T11:01:08.472814 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28786, final_score: 0.09185, time: 699.57360 +[RESULT]: Val. Epoch: 7, summary_loss: 1.59503, final_score: 0.28521, time: 165.88706 + +2021-04-26T11:15:34.114461 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.35549, final_score: 0.13209, time: 702.91317 +[RESULT]: Val. Epoch: 8, summary_loss: 1.08550, final_score: 0.29570, time: 167.81207 + +2021-04-26T11:30:05.021090 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.33718, final_score: 0.12309, time: 713.37569 +[RESULT]: Val. Epoch: 9, summary_loss: 0.88556, final_score: 0.24725, time: 166.97929 + +2021-04-26T11:44:45.825773 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.40646, final_score: 0.16533, time: 694.14366 +[RESULT]: Val. Epoch: 10, summary_loss: 1.04534, final_score: 0.23926, time: 164.30511 + +2021-04-26T11:59:04.464755 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39405, final_score: 0.15896, time: 695.43515 +[RESULT]: Val. Epoch: 11, summary_loss: 1.52472, final_score: 0.32118, time: 166.99711 + +2021-04-26T12:13:27.104677 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.45317, final_score: 0.20332, time: 703.30782 +[RESULT]: Val. Epoch: 12, summary_loss: 0.63625, final_score: 0.24675, time: 164.38252 + +2021-04-26T12:27:55.139872 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.43888, final_score: 0.19170, time: 693.93411 +[RESULT]: Val. Epoch: 13, summary_loss: 0.92006, final_score: 0.27223, time: 167.60375 + +2021-04-26T12:42:16.893566 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 14, summary_loss: 0.48173, final_score: 0.22057, time: 713.36994 +[RESULT]: Val. Epoch: 14, summary_loss: 0.47606, final_score: 0.20480, time: 167.51161 + +2021-04-26T12:56:58.180977 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 15, summary_loss: 0.47294, final_score: 0.22094, time: 694.71445 +[RESULT]: Val. Epoch: 15, summary_loss: 0.55986, final_score: 0.24426, time: 166.20192 + +2021-04-26T13:11:19.284107 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 16, summary_loss: 0.46415, final_score: 0.20995, time: 711.53229 +[RESULT]: Val. Epoch: 16, summary_loss: 1.17536, final_score: 0.27872, time: 166.23783 + +2021-04-26T13:25:57.271193 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 17, summary_loss: 0.41993, final_score: 0.18633, time: 718.44210 +[RESULT]: Val. Epoch: 17, summary_loss: 0.47061, final_score: 0.18132, time: 168.32497 + +2021-04-26T13:40:44.439875 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 18, summary_loss: 0.40192, final_score: 0.17046, time: 715.84248 +[RESULT]: Val. Epoch: 18, summary_loss: 0.48376, final_score: 0.17433, time: 164.66565 + +2021-04-26T13:55:26.477562 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 19, summary_loss: 0.39396, final_score: 0.16521, time: 704.95786 +[RESULT]: Val. Epoch: 19, summary_loss: 0.63794, final_score: 0.18282, time: 164.75714 + +2021-04-26T14:09:56.605170 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 20, summary_loss: 0.37171, final_score: 0.15284, time: 707.08383 +[RESULT]: Val. Epoch: 20, summary_loss: 0.59149, final_score: 0.16184, time: 165.45018 + +2021-04-26T14:24:29.327559 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 21, summary_loss: 0.35434, final_score: 0.13434, time: 708.94347 +[RESULT]: Val. Epoch: 21, summary_loss: 0.55880, final_score: 0.17383, time: 164.77131 + +2021-04-26T14:39:03.221192 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 22, summary_loss: 0.34789, final_score: 0.13484, time: 703.84374 +[RESULT]: Val. Epoch: 22, summary_loss: 0.44682, final_score: 0.15335, time: 165.01951 + +2021-04-26T14:53:32.634894 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 23, summary_loss: 0.33579, final_score: 0.12822, time: 710.88396 +[RESULT]: Val. Epoch: 23, summary_loss: 0.52625, final_score: 0.16184, time: 166.29344 + +2021-04-26T15:08:10.015441 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 24, summary_loss: 0.33206, final_score: 0.12359, time: 713.01336 +[RESULT]: Val. Epoch: 24, summary_loss: 0.48045, final_score: 0.16084, time: 166.03013 + +2021-04-26T15:22:49.242673 +LR: 3.125e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 25, summary_loss: 0.32778, final_score: 0.12097, time: 705.40984 +[RESULT]: Val. Epoch: 25, summary_loss: 0.54000, final_score: 0.15235, time: 164.16805 + +2021-04-26T15:37:18.993807 +LR: 3.125e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 26, summary_loss: 0.32004, final_score: 0.11535, time: 716.77298 +[RESULT]: Val. Epoch: 26, summary_loss: 0.64942, final_score: 0.16134, time: 164.56222 + +2021-04-26T15:52:00.511909 +LR: 1.5625e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 27, summary_loss: 0.31601, final_score: 0.11310, time: 716.76286 +[RESULT]: Val. Epoch: 27, summary_loss: 0.56556, final_score: 0.15884, time: 165.65165 + +2021-04-26T16:06:43.118977 +LR: 1.5625e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 28, summary_loss: 0.31718, final_score: 0.11710, time: 694.98416 +[RESULT]: Val. Epoch: 28, summary_loss: 0.55095, final_score: 0.15435, time: 166.66665 + +2021-04-26T16:21:04.928981 +LR: 7.8125e-06 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 29, summary_loss: 0.30915, final_score: 0.10772, time: 712.94500 +[RESULT]: Val. Epoch: 29, summary_loss: 0.58684, final_score: 0.15834, time: 167.47458 + +2021-04-26T16:35:45.543404 +LR: 7.8125e-06 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 30, summary_loss: 0.31119, final_score: 0.11222, time: 706.14286 +[RESULT]: Val. Epoch: 30, summary_loss: 0.58120, final_score: 0.15734, time: 165.28202 +Fitter prepared. 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Device is cuda:0 + +2021-04-25T01:46:26.463481 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.47832, final_score: 0.23607, time: 722.09276 +[RESULT]: Val. Epoch: 1, summary_loss: 1.48428, final_score: 0.43307, time: 173.39201 + +2021-04-25T02:01:22.435049 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.30692, final_score: 0.09510, time: 733.11573 +[RESULT]: Val. Epoch: 2, summary_loss: 1.36792, final_score: 0.40759, time: 175.40392 + +2021-04-25T02:16:31.312565 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27150, final_score: 0.07448, time: 722.45672 +[RESULT]: Val. Epoch: 3, summary_loss: 2.30018, final_score: 0.42857, time: 176.23771 + +2021-04-25T02:31:30.170066 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.30390, final_score: 0.09360, time: 727.95214 +[RESULT]: Val. Epoch: 4, summary_loss: 1.84662, final_score: 0.40210, time: 175.40318 + +2021-04-25T02:46:33.702797 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27469, final_score: 0.07898, time: 741.22916 +[RESULT]: Val. Epoch: 5, summary_loss: 2.78385, final_score: 0.41009, time: 174.57139 + +2021-04-25T03:01:49.681532 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.32112, final_score: 0.10735, time: 731.90716 +[RESULT]: Val. Epoch: 6, summary_loss: 1.36704, final_score: 0.40360, time: 171.23469 + +2021-04-25T03:16:53.167428 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.30290, final_score: 0.09835, time: 723.79755 +[RESULT]: Val. Epoch: 7, summary_loss: 1.32742, final_score: 0.40959, time: 174.27954 + +2021-04-25T03:31:51.632296 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.36877, final_score: 0.14034, time: 750.88577 +[RESULT]: Val. Epoch: 8, summary_loss: 1.71704, final_score: 0.39960, time: 169.32627 + +2021-04-25T03:47:12.047293 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.34829, final_score: 0.12709, time: 725.52443 +[RESULT]: Val. Epoch: 9, summary_loss: 1.21154, final_score: 0.37213, time: 172.94269 + +2021-04-25T04:02:10.863572 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.41623, final_score: 0.17408, time: 742.80683 +[RESULT]: Val. Epoch: 10, summary_loss: 0.75624, final_score: 0.36663, time: 171.08996 + +2021-04-25T04:17:25.112006 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39974, final_score: 0.16271, time: 729.57646 +[RESULT]: Val. Epoch: 11, summary_loss: 0.94686, final_score: 0.37413, time: 174.31170 + +2021-04-25T04:32:29.178684 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.47761, final_score: 0.22119, time: 732.20310 +[RESULT]: Val. Epoch: 12, summary_loss: 1.17539, final_score: 0.38162, time: 173.23935 + +2021-04-25T04:47:34.791941 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47239, final_score: 0.21732, time: 749.13574 +[RESULT]: Val. Epoch: 13, summary_loss: 1.19044, final_score: 0.35614, time: 176.01910 + +2021-04-25T05:03:00.147273 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.53195, final_score: 0.26368, time: 739.53159 +[RESULT]: Val. Epoch: 14, summary_loss: 0.72612, final_score: 0.35015, time: 170.36899 + +2021-04-25T05:18:10.400030 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.52739, final_score: 0.26431, time: 736.22642 +[RESULT]: Val. Epoch: 15, summary_loss: 0.73948, final_score: 0.35015, time: 171.69948 + +2021-04-25T05:33:18.500475 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.58066, final_score: 0.31105, time: 743.70539 +[RESULT]: Val. Epoch: 16, summary_loss: 0.80720, final_score: 0.38012, time: 169.32711 + +2021-04-25T05:48:31.715242 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.58547, final_score: 0.31880, time: 743.93330 +[RESULT]: Val. Epoch: 17, summary_loss: 0.81934, final_score: 0.37962, time: 172.53054 + +2021-04-25T06:03:48.348962 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.60847, final_score: 0.34729, time: 736.60329 +[RESULT]: Val. Epoch: 18, summary_loss: 0.82340, final_score: 0.34466, time: 170.75967 + +2021-04-25T06:18:55.917676 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.60388, final_score: 0.34229, time: 753.89420 +[RESULT]: Val. Epoch: 19, summary_loss: 0.62105, final_score: 0.33467, time: 169.50630 + +2021-04-25T06:34:19.696463 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.59567, final_score: 0.33192, time: 745.86096 +[RESULT]: Val. Epoch: 20, summary_loss: 0.65132, final_score: 0.36264, time: 174.82508 + +2021-04-25T06:49:40.554432 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.60028, final_score: 0.33392, time: 736.74177 +[RESULT]: Val. Epoch: 21, summary_loss: 0.61770, final_score: 0.34116, time: 172.73295 + +2021-04-25T07:04:50.548069 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.59429, final_score: 0.32629, time: 749.54624 +[RESULT]: Val. Epoch: 22, summary_loss: 0.64722, final_score: 0.32917, time: 172.33298 + +2021-04-25T07:20:13.222344 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.59014, final_score: 0.32604, time: 740.64717 +[RESULT]: Val. Epoch: 23, summary_loss: 0.63198, final_score: 0.34266, time: 169.55644 + +2021-04-25T07:35:23.616571 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.55941, final_score: 0.29605, time: 745.01283 +[RESULT]: Val. Epoch: 24, summary_loss: 0.55672, final_score: 0.28422, time: 173.03378 + +2021-04-25T07:50:42.019910 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.54210, final_score: 0.28068, time: 750.18058 +[RESULT]: Val. Epoch: 25, summary_loss: 0.53520, final_score: 0.27473, time: 174.99913 + +2021-04-25T08:06:07.553257 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.53201, final_score: 0.27093, time: 746.67730 +[RESULT]: Val. Epoch: 26, summary_loss: 0.56924, final_score: 0.27572, time: 173.36763 + +2021-04-25T08:21:27.808232 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.53081, final_score: 0.27481, time: 756.92998 +[RESULT]: Val. Epoch: 27, summary_loss: 0.58526, final_score: 0.28571, time: 171.01733 + +2021-04-25T08:36:55.935608 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.50209, final_score: 0.24694, time: 742.42175 +[RESULT]: Val. Epoch: 28, summary_loss: 0.53069, final_score: 0.24625, time: 172.98755 + +2021-04-25T08:52:11.708836 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.50508, final_score: 0.25456, time: 746.63017 +[RESULT]: Val. Epoch: 29, summary_loss: 0.52435, final_score: 0.25874, time: 170.60782 + +2021-04-25T09:07:29.463035 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.49151, final_score: 0.23982, time: 765.13900 +[RESULT]: Val. Epoch: 30, summary_loss: 0.58910, final_score: 0.26623, time: 176.79979 +Fitter prepared. Device is cuda:0 + +2021-04-26T00:51:30.057129 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.44351, final_score: 0.20220, time: 724.35247 +[RESULT]: Val. Epoch: 1, summary_loss: 1.65485, final_score: 0.45105, time: 168.92811 + +2021-04-26T01:06:23.715542 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.31669, final_score: 0.10422, time: 717.97256 +[RESULT]: Val. Epoch: 2, summary_loss: 1.65705, final_score: 0.44056, time: 168.29749 + +2021-04-26T01:21:10.168315 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27157, final_score: 0.07811, time: 706.53822 +[RESULT]: Val. Epoch: 3, summary_loss: 1.47557, final_score: 0.43556, time: 170.96144 + +2021-04-26T01:35:48.040424 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.30929, final_score: 0.10047, time: 744.09160 +[RESULT]: Val. Epoch: 4, summary_loss: 1.13178, final_score: 0.43906, time: 172.78501 + +2021-04-26T01:51:05.330111 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27658, final_score: 0.08373, time: 734.21588 +[RESULT]: Val. Epoch: 5, summary_loss: 2.26784, final_score: 0.45105, time: 172.02173 + +2021-04-26T02:06:11.764670 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.32596, final_score: 0.11235, time: 731.85799 +[RESULT]: Val. Epoch: 6, summary_loss: 1.84699, final_score: 0.44505, time: 168.55239 + +2021-04-26T02:21:12.346577 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.31788, final_score: 0.10572, time: 742.21023 +[RESULT]: Val. Epoch: 7, summary_loss: 0.96060, final_score: 0.42957, time: 170.83584 + +2021-04-26T02:36:25.797532 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.38312, final_score: 0.14609, time: 734.74228 +[RESULT]: Val. Epoch: 8, summary_loss: 1.54619, final_score: 0.44805, time: 168.60274 + +2021-04-26T02:51:29.315215 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.36465, final_score: 0.13847, time: 729.00196 +[RESULT]: Val. Epoch: 9, summary_loss: 1.24385, final_score: 0.42807, time: 169.59376 + +2021-04-26T03:06:28.092165 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.42863, final_score: 0.17983, time: 754.90148 +[RESULT]: Val. Epoch: 10, summary_loss: 0.83973, final_score: 0.39960, time: 168.17030 + +2021-04-26T03:21:51.517034 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.41010, final_score: 0.16846, time: 737.03647 +[RESULT]: Val. Epoch: 11, summary_loss: 2.04576, final_score: 0.41858, time: 171.87096 + +2021-04-26T03:37:00.601827 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.48905, final_score: 0.22557, time: 734.76943 +[RESULT]: Val. Epoch: 12, summary_loss: 0.92476, final_score: 0.38262, time: 169.20191 + +2021-04-26T03:52:04.746496 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47941, final_score: 0.21995, time: 740.52299 +[RESULT]: Val. Epoch: 13, summary_loss: 1.08410, final_score: 0.40809, time: 169.44640 + +2021-04-26T04:07:14.889557 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.54482, final_score: 0.27206, time: 751.16783 +[RESULT]: Val. Epoch: 14, summary_loss: 0.92899, final_score: 0.37812, time: 168.94062 + +2021-04-26T04:22:35.170199 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54477, final_score: 0.27093, time: 739.63438 +[RESULT]: Val. Epoch: 15, summary_loss: 0.71464, final_score: 0.38062, time: 168.75539 + +2021-04-26T04:37:43.896753 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.58886, final_score: 0.31067, time: 752.90686 +[RESULT]: Val. Epoch: 16, summary_loss: 1.00534, final_score: 0.38911, time: 169.16908 + +2021-04-26T04:53:06.161839 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.57646, final_score: 0.30592, time: 753.72700 +[RESULT]: Val. Epoch: 17, summary_loss: 0.64558, final_score: 0.33317, time: 170.43174 + +2021-04-26T05:08:30.675015 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.60540, final_score: 0.32992, time: 752.52656 +[RESULT]: Val. Epoch: 18, summary_loss: 0.61456, final_score: 0.33167, time: 168.66271 + +2021-04-26T05:23:52.248975 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.59943, final_score: 0.32767, time: 736.29588 +[RESULT]: Val. Epoch: 19, summary_loss: 0.75326, final_score: 0.33417, time: 170.72128 + +2021-04-26T05:38:59.441840 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.59497, final_score: 0.32304, time: 750.54994 +[RESULT]: Val. Epoch: 20, summary_loss: 0.67435, final_score: 0.33017, time: 172.11572 + +2021-04-26T05:54:22.283473 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.55572, final_score: 0.28393, time: 739.77338 +[RESULT]: Val. Epoch: 21, summary_loss: 0.57776, final_score: 0.25924, time: 168.04923 + +2021-04-26T06:09:30.870609 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.53890, final_score: 0.26906, time: 740.37017 +[RESULT]: Val. Epoch: 22, summary_loss: 0.55863, final_score: 0.26374, time: 170.87568 + +2021-04-26T06:24:42.517184 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.53188, final_score: 0.26518, time: 756.09033 +[RESULT]: Val. Epoch: 23, summary_loss: 0.70919, final_score: 0.29970, time: 170.10509 + +2021-04-26T06:40:08.877159 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.51785, final_score: 0.25056, time: 737.78975 +[RESULT]: Val. Epoch: 24, summary_loss: 0.89305, final_score: 0.30270, time: 171.52685 + +2021-04-26T06:55:18.367204 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.49913, final_score: 0.23507, time: 739.58340 +[RESULT]: Val. Epoch: 25, summary_loss: 0.48525, final_score: 0.23127, time: 170.08611 + +2021-04-26T07:10:28.388502 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.48590, final_score: 0.22819, time: 738.60303 +[RESULT]: Val. Epoch: 26, summary_loss: 0.54862, final_score: 0.23726, time: 168.80679 + +2021-04-26T07:25:35.988140 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.48731, final_score: 0.23169, time: 756.44103 +[RESULT]: Val. Epoch: 27, summary_loss: 0.47756, final_score: 0.21778, time: 170.96208 + +2021-04-26T07:41:03.763326 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.47351, final_score: 0.22269, time: 730.06542 +[RESULT]: Val. Epoch: 28, summary_loss: 0.56726, final_score: 0.22827, time: 170.13497 + +2021-04-26T07:56:04.126504 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.47526, final_score: 0.22369, time: 760.77203 +[RESULT]: Val. Epoch: 29, summary_loss: 0.58349, final_score: 0.24126, time: 172.64918 + +2021-04-26T08:11:37.722245 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.45729, final_score: 0.20845, time: 743.79463 +[RESULT]: Val. Epoch: 30, summary_loss: 0.47381, final_score: 0.20979, time: 171.48538 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_4/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_4/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..ea0f145b91c8880b0ed369344022a5be43a3b319 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_4/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..cd94348652b675c738fd9c588cc9ee1aa7563a5f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:88bc6bdd69e8b2a74b697c9656e9d0c096536a7950343d2cf2870b3b51f7613c +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c9d347c17efa508b80e9c894905b28b988a1d7c9 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0de9a1c473183436a924054f06938581826237e814226573c66d207bb0726129 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-028epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-028epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..14368e590793db4848f876508cda355415a95e52 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/best-checkpoint-028epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:493fba42557200a0430a175ad83e8be994eaf8c61e60d4afbf8561ba535abbc0 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..1bf71adc6ab028cd424695a4ac7664b8e3d0231e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f2c6e59643fdabb8543c5eb55fdd5c8173544db4b61d1adf675a9f780d1a4dd4 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..fe1836c86cf8f1e45f2ed6562e6328c185ca6b31 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-04-28T09:17:03.232334 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.43120, final_score: 0.19083, time: 770.44519 +[RESULT]: Val. Epoch: 1, summary_loss: 2.02583, final_score: 0.44406, time: 168.18836 + +2021-04-28T09:32:42.535348 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.32814, final_score: 0.11035, time: 718.51863 +[RESULT]: Val. Epoch: 2, summary_loss: 1.48277, final_score: 0.41758, time: 166.20211 + +2021-04-28T09:47:27.648485 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.29020, final_score: 0.08835, time: 713.48085 +[RESULT]: Val. Epoch: 3, summary_loss: 1.41004, final_score: 0.45055, time: 166.05420 + +2021-04-28T10:02:07.620260 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.30586, final_score: 0.09998, time: 698.13017 +[RESULT]: Val. Epoch: 4, summary_loss: 1.78963, final_score: 0.42008, time: 166.38322 + +2021-04-28T10:16:32.379550 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27410, final_score: 0.07986, time: 704.37154 +[RESULT]: Val. Epoch: 5, summary_loss: 1.21424, final_score: 0.41459, time: 166.99426 + +2021-04-28T10:31:04.222600 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.31630, final_score: 0.10897, time: 715.65573 +[RESULT]: Val. Epoch: 6, summary_loss: 1.63527, final_score: 0.42358, time: 164.87781 + +2021-04-28T10:45:44.965919 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.31157, final_score: 0.10322, time: 721.33731 +[RESULT]: Val. Epoch: 7, summary_loss: 2.45567, final_score: 0.41259, time: 167.87363 + +2021-04-28T11:00:34.411386 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.36591, final_score: 0.14059, time: 719.35259 +[RESULT]: Val. Epoch: 8, summary_loss: 1.16181, final_score: 0.38561, time: 166.19622 + +2021-04-28T11:15:20.449642 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.35238, final_score: 0.12909, time: 725.30531 +[RESULT]: Val. Epoch: 9, summary_loss: 4.34630, final_score: 0.45005, time: 166.37514 + +2021-04-28T11:30:12.353186 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.41731, final_score: 0.16721, time: 721.03552 +[RESULT]: Val. Epoch: 10, summary_loss: 0.67000, final_score: 0.36513, time: 168.19448 + +2021-04-28T11:45:01.999730 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.40808, final_score: 0.16546, time: 723.24248 +[RESULT]: Val. Epoch: 11, summary_loss: 1.76425, final_score: 0.39261, time: 166.98754 + +2021-04-28T11:59:52.443051 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.47660, final_score: 0.21757, time: 744.01080 +[RESULT]: Val. Epoch: 12, summary_loss: 1.34662, final_score: 0.37163, time: 167.91500 + +2021-04-28T12:15:04.550126 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.46893, final_score: 0.21157, time: 744.22696 +[RESULT]: Val. Epoch: 13, summary_loss: 0.78680, final_score: 0.35864, time: 169.36894 + +2021-04-28T12:30:18.350288 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.53950, final_score: 0.27343, time: 725.85576 +[RESULT]: Val. Epoch: 14, summary_loss: 0.98634, final_score: 0.37612, time: 165.74663 + +2021-04-28T12:45:10.167955 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.53585, final_score: 0.26518, time: 727.96284 +[RESULT]: Val. Epoch: 15, summary_loss: 0.76603, final_score: 0.37762, time: 168.35354 + +2021-04-28T13:00:06.684168 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.58964, final_score: 0.31792, time: 731.65884 +[RESULT]: Val. Epoch: 16, summary_loss: 0.62868, final_score: 0.34366, time: 165.97172 + +2021-04-28T13:15:04.862257 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.59520, final_score: 0.32254, time: 726.30549 +[RESULT]: Val. Epoch: 17, summary_loss: 0.76307, final_score: 0.36314, time: 165.33532 + +2021-04-28T13:29:56.708383 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.61874, final_score: 0.35416, time: 735.57496 +[RESULT]: Val. Epoch: 18, summary_loss: 0.79492, final_score: 0.37512, time: 168.09463 + +2021-04-28T13:45:00.579582 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.61293, final_score: 0.34641, time: 732.34059 +[RESULT]: Val. Epoch: 19, summary_loss: 0.63543, final_score: 0.33666, time: 169.80477 + +2021-04-28T14:00:02.965975 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.61233, final_score: 0.34529, time: 729.15614 +[RESULT]: Val. Epoch: 20, summary_loss: 0.61507, final_score: 0.34466, time: 167.64996 + +2021-04-28T14:15:00.237932 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.61177, final_score: 0.34804, time: 730.53373 +[RESULT]: Val. Epoch: 21, summary_loss: 0.65820, final_score: 0.35764, time: 168.53457 + +2021-04-28T14:29:59.515475 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.60923, final_score: 0.34479, time: 743.16409 +[RESULT]: Val. Epoch: 22, summary_loss: 0.60414, final_score: 0.33017, time: 167.57299 + +2021-04-28T14:45:10.655810 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.60567, final_score: 0.34116, time: 742.97615 +[RESULT]: Val. Epoch: 23, summary_loss: 0.63344, final_score: 0.33816, time: 168.07160 + +2021-04-28T15:00:21.908057 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.59728, final_score: 0.33717, time: 727.40635 +[RESULT]: Val. Epoch: 24, summary_loss: 0.68907, final_score: 0.34565, time: 166.85558 + +2021-04-28T15:15:16.375172 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.58039, final_score: 0.31717, time: 724.16358 +[RESULT]: Val. Epoch: 25, summary_loss: 0.57677, final_score: 0.30919, time: 168.42940 + +2021-04-28T15:30:09.399731 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.56767, final_score: 0.30705, time: 737.78669 +[RESULT]: Val. Epoch: 26, summary_loss: 0.60062, final_score: 0.30919, time: 170.52595 + +2021-04-28T15:45:17.925070 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.55909, final_score: 0.30267, time: 750.00070 +[RESULT]: Val. Epoch: 27, summary_loss: 0.60322, final_score: 0.30769, time: 170.51203 + +2021-04-28T16:00:38.712086 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.53794, final_score: 0.28043, time: 752.90585 +[RESULT]: Val. Epoch: 28, summary_loss: 0.55387, final_score: 0.28521, time: 172.64037 + +2021-04-28T16:16:04.666818 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.52483, final_score: 0.26993, time: 760.67863 +[RESULT]: Val. Epoch: 29, summary_loss: 0.60101, final_score: 0.28621, time: 169.65839 + +2021-04-28T16:31:35.205669 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.52965, final_score: 0.26893, time: 743.43080 +[RESULT]: Val. Epoch: 30, summary_loss: 0.63522, final_score: 0.29620, time: 170.03517 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..c142a50e980cd44b149dc74cc55e70fe247e7c14 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_5/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..0371a835712114aba67cd81ac33eec54a00b877a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bb019c66c1df37c7fcb3da45e38281bdc52ccf0aeb9a1a75ca33dc6f20b30001 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..146b86019e5d55f7a26f6afecdf45ff2501012c8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5bcfefd1890bb17fc1bda0636a0dd6dc51e2c95b1cdaaf483ad65e09265f1a9b +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..619a1cdc6049be5df75f9e40cc4246b883dbe69e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a392fd0ce94f7a7cdd09732802efc62bd235fa03484379eb0876a0fa62a93b3b +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..9e350630695e8faa0a5a67e420635c2790621b25 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:622af4b769a41f34f3bc8dbec9f8cfc959706cfa8b10188071e5ed6e8e788827 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..33d1aae030c760922afe03bfe52412c3907d1f57 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-10T19:19:47.442463 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.45388, final_score: 0.20257, time: 786.67450 +[RESULT]: Val. Epoch: 1, summary_loss: 1.48949, final_score: 0.44456, time: 169.55192 + +2021-06-10T19:35:44.029584 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.34371, final_score: 0.12072, time: 734.42114 +[RESULT]: Val. Epoch: 2, summary_loss: 1.18128, final_score: 0.41359, time: 171.49347 + +2021-06-10T19:50:50.729948 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.28940, final_score: 0.09135, time: 737.76680 +[RESULT]: Val. Epoch: 3, summary_loss: 1.73999, final_score: 0.41758, time: 169.56870 + +2021-06-10T20:05:58.225067 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.31013, final_score: 0.09973, time: 737.93447 +[RESULT]: Val. Epoch: 4, summary_loss: 2.09962, final_score: 0.40909, time: 168.53317 + +2021-06-10T20:21:04.994273 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.28527, final_score: 0.08473, time: 749.58752 +[RESULT]: Val. Epoch: 5, summary_loss: 1.40107, final_score: 0.39960, time: 168.63383 + +2021-06-10T20:36:23.431120 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.33343, final_score: 0.11810, time: 740.73124 +[RESULT]: Val. Epoch: 6, summary_loss: 1.15360, final_score: 0.41059, time: 170.83969 + +2021-06-10T20:51:35.383831 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.31677, final_score: 0.10760, time: 748.97478 +[RESULT]: Val. Epoch: 7, summary_loss: 1.41023, final_score: 0.41309, time: 170.70341 + +2021-06-10T21:06:55.252436 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.37511, final_score: 0.14284, time: 745.98827 +[RESULT]: Val. Epoch: 8, summary_loss: 1.67994, final_score: 0.39510, time: 170.31402 + +2021-06-10T21:22:11.710887 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.36122, final_score: 0.13584, time: 756.43049 +[RESULT]: Val. Epoch: 9, summary_loss: 1.64699, final_score: 0.40659, time: 172.55175 + +2021-06-10T21:37:40.895336 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.42671, final_score: 0.17821, time: 745.74569 +[RESULT]: Val. Epoch: 10, summary_loss: 0.70505, final_score: 0.36763, time: 170.90596 + +2021-06-10T21:52:57.922869 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.41837, final_score: 0.17633, time: 740.01523 +[RESULT]: Val. Epoch: 11, summary_loss: 1.48208, final_score: 0.40709, time: 172.20450 + +2021-06-10T22:08:10.299362 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.48107, final_score: 0.22132, time: 740.73840 +[RESULT]: Val. Epoch: 12, summary_loss: 0.80681, final_score: 0.36863, time: 173.10238 + +2021-06-10T22:23:24.301902 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47549, final_score: 0.21870, time: 743.01223 +[RESULT]: Val. Epoch: 13, summary_loss: 0.78311, final_score: 0.36014, time: 170.96435 + +2021-06-10T22:38:38.450608 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.54764, final_score: 0.27193, time: 758.06523 +[RESULT]: Val. Epoch: 14, summary_loss: 0.74704, final_score: 0.38711, time: 170.79328 + +2021-06-10T22:54:07.709199 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54117, final_score: 0.27143, time: 746.88044 +[RESULT]: Val. Epoch: 15, summary_loss: 0.70421, final_score: 0.36763, time: 170.58662 + +2021-06-10T23:09:25.542221 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.58806, final_score: 0.31905, time: 746.20884 +[RESULT]: Val. Epoch: 16, summary_loss: 0.67951, final_score: 0.37163, time: 178.67921 + +2021-06-10T23:24:50.888299 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.59266, final_score: 0.32254, time: 776.14567 +[RESULT]: Val. Epoch: 17, summary_loss: 0.77496, final_score: 0.36264, time: 177.08186 + +2021-06-10T23:40:44.356820 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.61663, final_score: 0.35066, time: 770.32459 +[RESULT]: Val. Epoch: 18, summary_loss: 0.70961, final_score: 0.35365, time: 179.38435 + +2021-06-10T23:56:34.323929 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.62151, final_score: 0.35629, time: 785.19341 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69610, final_score: 0.34965, time: 179.66040 + +2021-06-11T00:12:39.430356 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.61750, final_score: 0.35104, time: 788.16230 +[RESULT]: Val. Epoch: 20, summary_loss: 0.64051, final_score: 0.34765, time: 178.57044 + +2021-06-11T00:28:46.648896 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.61412, final_score: 0.34754, time: 770.63618 +[RESULT]: Val. Epoch: 21, summary_loss: 0.79013, final_score: 0.37712, time: 176.77399 + +2021-06-11T00:44:34.294133 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.61233, final_score: 0.34391, time: 764.98196 +[RESULT]: Val. Epoch: 22, summary_loss: 0.59992, final_score: 0.32917, time: 175.36970 + +2021-06-11T01:00:15.058895 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.60395, final_score: 0.34116, time: 768.02503 +[RESULT]: Val. Epoch: 23, summary_loss: 0.64006, final_score: 0.35415, time: 174.93086 + +2021-06-11T01:15:58.232842 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.60756, final_score: 0.34354, time: 760.40500 +[RESULT]: Val. Epoch: 24, summary_loss: 0.61232, final_score: 0.34166, time: 176.75163 + +2021-06-11T01:31:35.596117 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.57552, final_score: 0.30942, time: 768.68371 +[RESULT]: Val. Epoch: 25, summary_loss: 0.58315, final_score: 0.31219, time: 176.82714 + +2021-06-11T01:47:21.546318 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.56726, final_score: 0.30342, time: 745.41632 +[RESULT]: Val. Epoch: 26, summary_loss: 0.56444, final_score: 0.30170, time: 179.22549 + +2021-06-11T02:02:46.560119 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.55857, final_score: 0.29505, time: 773.08944 +[RESULT]: Val. Epoch: 27, summary_loss: 0.56636, final_score: 0.30020, time: 178.32887 + +2021-06-11T02:18:38.197672 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.55636, final_score: 0.29305, time: 775.17920 +[RESULT]: Val. Epoch: 28, summary_loss: 0.65323, final_score: 0.32068, time: 179.33646 + +2021-06-11T02:34:32.950476 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.53048, final_score: 0.26818, time: 765.00939 +[RESULT]: Val. Epoch: 29, summary_loss: 0.62147, final_score: 0.29820, time: 178.15008 + +2021-06-11T02:50:16.356239 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.52547, final_score: 0.27168, time: 766.49372 +[RESULT]: Val. Epoch: 30, summary_loss: 0.60613, final_score: 0.29870, time: 178.19872 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..ef657777cb67203dca4ef7ed9e8aebf0ff3e2eee Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_6/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..d9cb80a539f00336785f4ccb979b3539854a2d0f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c840b6b6711451a2fb4dc7ecfedad7a8ecc13a8d966080c45b73bdf3cdcb7386 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..47e8f588fb54ebb2524ff0fbed5ebce8fc89d5c4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:668847bc06f6fc51bc7b8536f64e5c7e491c144f9bfddd8866109a56376ed185 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..901100175ac399159e0b95aa2151b3e0c40b619f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6ee4097c7bdda8411c903d02088143679bbed13dea12f345290a11a7aae80dfa +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..068741691ecccd3968ab884c4ea599aa4852a776 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:062b27571d0d2b91c93a702cc2c88adda2aaf8163eefe736ba492b2399aae707 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c74fb4cd310adea5a453cfb5ecbd8527f1551bd9 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-11T15:46:09.236344 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.47016, final_score: 0.22832, time: 784.10441 +[RESULT]: Val. Epoch: 1, summary_loss: 1.26562, final_score: 0.43506, time: 178.98511 + +2021-06-11T16:02:13.152531 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.33347, final_score: 0.11172, time: 752.45231 +[RESULT]: Val. Epoch: 2, summary_loss: 1.05763, final_score: 0.41708, time: 178.15213 + +2021-06-11T16:17:44.166583 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27113, final_score: 0.07598, time: 728.68928 +[RESULT]: Val. Epoch: 3, summary_loss: 2.86054, final_score: 0.45005, time: 179.07876 + +2021-06-11T16:32:52.133949 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.29232, final_score: 0.09335, time: 751.76307 +[RESULT]: Val. Epoch: 4, summary_loss: 1.01323, final_score: 0.39960, time: 178.00892 + +2021-06-11T16:48:22.388636 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27053, final_score: 0.07848, time: 739.37653 +[RESULT]: Val. Epoch: 5, summary_loss: 1.81453, final_score: 0.43307, time: 177.40929 + +2021-06-11T17:03:39.337604 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.32518, final_score: 0.11135, time: 752.14536 +[RESULT]: Val. Epoch: 6, summary_loss: 3.23962, final_score: 0.45055, time: 178.67347 + +2021-06-11T17:19:10.370748 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.31498, final_score: 0.10360, time: 766.43373 +[RESULT]: Val. Epoch: 7, summary_loss: 1.61973, final_score: 0.43606, time: 178.32690 + +2021-06-11T17:34:55.328996 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.37204, final_score: 0.14421, time: 760.80712 +[RESULT]: Val. Epoch: 8, summary_loss: 1.53977, final_score: 0.40310, time: 176.72202 + +2021-06-11T17:50:33.126821 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.35048, final_score: 0.13072, time: 768.46043 +[RESULT]: Val. Epoch: 9, summary_loss: 1.17713, final_score: 0.40110, time: 176.54098 + +2021-06-11T18:06:18.330735 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.42207, final_score: 0.17358, time: 757.82272 +[RESULT]: Val. Epoch: 10, summary_loss: 1.17391, final_score: 0.40310, time: 177.81716 + +2021-06-11T18:21:54.156962 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.40725, final_score: 0.16558, time: 775.20901 +[RESULT]: Val. Epoch: 11, summary_loss: 1.43023, final_score: 0.42757, time: 177.89517 + +2021-06-11T18:37:47.430925 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.48152, final_score: 0.22219, time: 762.56798 +[RESULT]: Val. Epoch: 12, summary_loss: 1.07538, final_score: 0.38162, time: 178.02451 + +2021-06-11T18:53:28.241081 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47375, final_score: 0.21732, time: 763.77661 +[RESULT]: Val. Epoch: 13, summary_loss: 0.80794, final_score: 0.36813, time: 180.07864 + +2021-06-11T19:09:12.500292 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.55398, final_score: 0.28155, time: 763.27514 +[RESULT]: Val. Epoch: 14, summary_loss: 0.67377, final_score: 0.36364, time: 176.59949 + +2021-06-11T19:24:52.748235 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54359, final_score: 0.27243, time: 758.40614 +[RESULT]: Val. Epoch: 15, summary_loss: 0.67121, final_score: 0.35814, time: 173.56183 + +2021-06-11T19:40:25.146305 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.60017, final_score: 0.32679, time: 753.23508 +[RESULT]: Val. Epoch: 16, summary_loss: 0.75437, final_score: 0.38312, time: 168.30320 + +2021-06-11T19:55:46.873566 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.59636, final_score: 0.32629, time: 743.03965 +[RESULT]: Val. Epoch: 17, summary_loss: 0.67835, final_score: 0.36264, time: 171.40761 + +2021-06-11T20:11:01.483091 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.63022, final_score: 0.36641, time: 746.51867 +[RESULT]: Val. Epoch: 18, summary_loss: 0.67873, final_score: 0.37962, time: 169.34024 + +2021-06-11T20:26:17.577221 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.62472, final_score: 0.35516, time: 747.86598 +[RESULT]: Val. Epoch: 19, summary_loss: 0.63726, final_score: 0.36513, time: 172.25550 + +2021-06-11T20:41:38.136508 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.62248, final_score: 0.35504, time: 743.52092 +[RESULT]: Val. Epoch: 20, summary_loss: 0.61464, final_score: 0.34416, time: 168.47927 + +2021-06-11T20:56:50.508986 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.61778, final_score: 0.35041, time: 735.15513 +[RESULT]: Val. Epoch: 21, summary_loss: 0.61269, final_score: 0.34016, time: 170.78215 + +2021-06-11T21:11:56.843068 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.61313, final_score: 0.35079, time: 747.37880 +[RESULT]: Val. Epoch: 22, summary_loss: 0.64494, final_score: 0.35514, time: 171.65881 + +2021-06-11T21:27:16.081912 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.61056, final_score: 0.33979, time: 755.51063 +[RESULT]: Val. Epoch: 23, summary_loss: 0.74099, final_score: 0.36414, time: 168.78504 + +2021-06-11T21:42:40.568747 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.57820, final_score: 0.31305, time: 740.26192 +[RESULT]: Val. Epoch: 24, summary_loss: 0.60662, final_score: 0.30320, time: 168.45823 + +2021-06-11T21:57:49.629791 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.56209, final_score: 0.29443, time: 734.78119 +[RESULT]: Val. Epoch: 25, summary_loss: 0.55978, final_score: 0.29471, time: 168.45490 + +2021-06-11T22:12:53.225591 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.55840, final_score: 0.29618, time: 743.00305 +[RESULT]: Val. Epoch: 26, summary_loss: 0.57219, final_score: 0.30070, time: 171.86667 + +2021-06-11T22:28:08.293780 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.55203, final_score: 0.28668, time: 732.47939 +[RESULT]: Val. Epoch: 27, summary_loss: 0.54490, final_score: 0.27722, time: 168.24182 + +2021-06-11T22:43:09.362613 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.54723, final_score: 0.28280, time: 733.67869 +[RESULT]: Val. Epoch: 28, summary_loss: 0.55823, final_score: 0.27822, time: 168.06386 + +2021-06-11T22:58:11.273905 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.53891, final_score: 0.27856, time: 743.11742 +[RESULT]: Val. Epoch: 29, summary_loss: 0.71525, final_score: 0.30420, time: 171.22217 + +2021-06-11T23:13:25.811841 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.51665, final_score: 0.25994, time: 737.56921 +[RESULT]: Val. Epoch: 30, summary_loss: 0.57939, final_score: 0.27173, time: 168.68089 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..6ce8ce0b911bde07fc8c7390238d6bbc1d1f9726 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_7/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..105ae54fe653e40a27cb39acb40b12e49b7c843b Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..8e3984540a29270602e0e9f8683d04b7c988c19d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fd2df09108ddb019c3f2228a4af71ef11e4b3d9998403bb57cf8a9368a83cd0a +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c8b59847630d81ee3645f734a462c56446bc5630 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:03062534d899c7d9f534b5cafa6c469672527db6ac8326f1ef76ba7b79869b8b +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..1cf87890507e51847e4a5a480a24377e83f4e54c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f478b638874dba09e9d39062f611ddccb79a0374b5a8074743120a2704906b05 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..a4f11a162a0c4d97d68d28850f08c1678cb3a8b1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7e7e5e0453ba51c46cfe42409a3dacc93ba59bb5e42b1d8c97bbb0b6cded293f +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b603e91a5979226d014e3cd4bd4c9bf0e3f72eb8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_1/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T13:10:55.808293 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.70753, final_score: 0.49950, time: 396.39662 +[RESULT]: Val. Epoch: 1, summary_loss: 0.70361, final_score: 0.49600, time: 24.41295 + +2021-06-25T13:17:56.973781 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.70009, final_score: 0.48988, time: 388.06204 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69941, final_score: 0.49650, time: 24.28344 + +2021-06-25T13:24:49.688625 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69862, final_score: 0.49738, time: 387.45537 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69446, final_score: 0.49650, time: 24.58200 + +2021-06-25T13:31:42.084325 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69832, final_score: 0.49288, time: 387.40908 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69558, final_score: 0.49351, time: 24.44517 + +2021-06-25T13:38:34.098589 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69699, final_score: 0.49550, time: 387.86132 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69464, final_score: 0.49650, time: 24.32813 + +2021-06-25T13:45:26.456789 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69709, final_score: 0.49425, time: 387.51171 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69509, final_score: 0.49700, time: 24.78928 + +2021-06-25T13:52:19.015976 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69653, final_score: 0.49763, time: 387.35743 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69481, final_score: 0.49650, time: 24.99536 + +2021-06-25T13:59:11.568233 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69682, final_score: 0.49788, time: 387.30101 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69525, final_score: 0.49550, time: 24.29747 + +2021-06-25T14:06:03.324199 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69555, final_score: 0.48350, time: 387.81760 +[RESULT]: Val. Epoch: 9, summary_loss: 0.70270, final_score: 0.49700, time: 24.28934 + +2021-06-25T14:12:55.585838 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69625, final_score: 0.49150, time: 387.45835 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69921, final_score: 0.49700, time: 25.79453 + +2021-06-25T14:19:49.071500 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69622, final_score: 0.49350, time: 387.17709 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69508, final_score: 0.49600, time: 24.67909 + +2021-06-25T14:26:41.110438 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69583, final_score: 0.49575, time: 387.65794 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69426, final_score: 0.49600, time: 24.84380 + +2021-06-25T14:33:33.992465 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69531, final_score: 0.49238, time: 386.92307 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69381, final_score: 0.49700, time: 25.55408 + +2021-06-25T14:40:26.920155 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69543, final_score: 0.49400, time: 387.24716 +[RESULT]: Val. Epoch: 14, summary_loss: 0.69652, final_score: 0.49550, time: 25.72363 + +2021-06-25T14:47:20.080913 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69551, final_score: 0.49650, time: 387.02115 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69411, final_score: 0.49451, time: 25.90948 + +2021-06-25T14:54:13.201760 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69524, final_score: 0.49550, time: 386.98000 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69357, final_score: 0.49600, time: 24.87103 + +2021-06-25T15:01:05.450499 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69475, final_score: 0.48463, time: 387.57235 +[RESULT]: Val. Epoch: 17, summary_loss: 0.69822, final_score: 0.49600, time: 25.95603 + +2021-06-25T15:07:59.188905 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.69507, final_score: 0.49413, time: 386.90082 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69318, final_score: 0.49500, time: 25.05427 + +2021-06-25T15:14:51.524331 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.69440, final_score: 0.49063, time: 387.00987 +[RESULT]: Val. Epoch: 19, summary_loss: 0.70545, final_score: 0.49550, time: 24.85646 + +2021-06-25T15:21:43.599206 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.69574, final_score: 0.49738, time: 387.70616 +[RESULT]: Val. Epoch: 20, summary_loss: 0.69743, final_score: 0.49351, time: 24.32190 + +2021-06-25T15:28:35.806033 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.69396, final_score: 0.49838, time: 387.75330 +[RESULT]: Val. Epoch: 21, summary_loss: 0.69330, final_score: 0.49151, time: 24.86023 + +2021-06-25T15:35:28.627798 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.69409, final_score: 0.49600, time: 387.44009 +[RESULT]: Val. Epoch: 22, summary_loss: 0.69355, final_score: 0.49401, time: 24.29712 + +2021-06-25T15:42:20.561864 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.69370, final_score: 0.49400, time: 387.54780 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69331, final_score: 0.49451, time: 24.37190 + +2021-06-25T15:49:12.653888 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.69345, final_score: 0.49375, time: 387.35056 +[RESULT]: Val. Epoch: 24, summary_loss: 0.69380, final_score: 0.49401, time: 24.34858 + +2021-06-25T15:56:04.515329 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.69355, final_score: 0.49763, time: 387.60078 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69316, final_score: 0.49351, time: 24.58894 + +2021-06-25T16:02:57.051639 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.69348, final_score: 0.49838, time: 387.60114 +[RESULT]: Val. Epoch: 26, summary_loss: 0.69315, final_score: 0.49251, time: 24.44711 + +2021-06-25T16:09:49.451826 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.69342, final_score: 0.49788, time: 387.55608 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69315, final_score: 0.49351, time: 24.65323 + +2021-06-25T16:16:41.819317 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.69327, final_score: 0.49338, time: 387.61567 +[RESULT]: Val. Epoch: 28, summary_loss: 0.69317, final_score: 0.49251, time: 24.42060 + +2021-06-25T16:23:34.058242 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.69334, final_score: 0.49825, time: 387.73225 +[RESULT]: Val. Epoch: 29, summary_loss: 0.69314, final_score: 0.49051, time: 24.48609 + +2021-06-25T16:30:26.625451 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.69314, final_score: 0.49325, time: 387.36983 +[RESULT]: Val. Epoch: 30, summary_loss: 0.69320, final_score: 0.49451, time: 26.21957 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:34.877242 +LR: 0.000125 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 25, summary_loss: 0.32861, final_score: 0.12084, time: 393.23026 +[RESULT]: Val. Epoch: 25, summary_loss: 0.77536, final_score: 0.16583, time: 24.66131 + +2021-06-26T08:58:33.046768 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 26, summary_loss: 0.32601, final_score: 0.12172, time: 387.46520 +[RESULT]: Val. Epoch: 26, summary_loss: 0.41421, final_score: 0.13536, time: 24.82988 + +2021-06-26T09:05:25.522874 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 27, summary_loss: 0.31648, final_score: 0.11760, time: 387.10900 +[RESULT]: Val. Epoch: 27, summary_loss: 0.54164, final_score: 0.14735, time: 24.71899 + +2021-06-26T09:12:17.540378 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 28, summary_loss: 0.31816, final_score: 0.11585, time: 387.03677 +[RESULT]: Val. Epoch: 28, summary_loss: 0.55721, final_score: 0.15534, time: 24.59663 + +2021-06-26T09:19:09.342298 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 29, summary_loss: 0.31335, final_score: 0.11760, time: 386.95399 +[RESULT]: Val. Epoch: 29, summary_loss: 0.80229, final_score: 0.17932, time: 24.27713 + +2021-06-26T09:26:00.743512 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 30, summary_loss: 0.31026, final_score: 0.11297, time: 386.96069 +[RESULT]: Val. Epoch: 30, summary_loss: 0.45101, final_score: 0.12238, time: 24.44484 + +2021-06-26T09:32:52.317332 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.30543, final_score: 0.10772, time: 387.61148 +[RESULT]: Val. Epoch: 31, summary_loss: 0.57072, final_score: 0.15235, time: 24.72772 + +2021-06-26T09:39:44.813624 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.30044, final_score: 0.10560, time: 387.65959 +[RESULT]: Val. Epoch: 32, summary_loss: 0.69960, final_score: 0.14386, time: 24.52030 + +2021-06-26T09:46:37.144045 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.29912, final_score: 0.10860, time: 387.30411 +[RESULT]: Val. Epoch: 33, summary_loss: 0.38176, final_score: 0.13137, time: 24.65409 + +2021-06-26T09:53:29.274801 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 34, summary_loss: 0.29752, final_score: 0.10522, time: 387.29272 +[RESULT]: Val. Epoch: 34, summary_loss: 0.39452, final_score: 0.12537, time: 24.43143 + +2021-06-26T10:00:21.168802 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 35, summary_loss: 0.29284, final_score: 0.10222, time: 387.09337 +[RESULT]: Val. Epoch: 35, summary_loss: 0.59254, final_score: 0.15185, time: 24.50208 + +2021-06-26T10:07:12.972495 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 36, summary_loss: 0.28738, final_score: 0.09898, time: 387.15306 +[RESULT]: Val. Epoch: 36, summary_loss: 0.50444, final_score: 0.13237, time: 24.65564 + +2021-06-26T10:14:04.953963 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.28047, final_score: 0.09473, time: 387.63248 +[RESULT]: Val. Epoch: 37, summary_loss: 0.57930, final_score: 0.13536, time: 24.43974 + +2021-06-26T10:20:57.224989 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 38, summary_loss: 0.28527, final_score: 0.09798, time: 387.53238 +[RESULT]: Val. Epoch: 38, summary_loss: 0.74173, final_score: 0.14735, time: 24.52825 + +2021-06-26T10:27:49.452391 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 39, summary_loss: 0.27912, final_score: 0.08898, time: 387.58322 +[RESULT]: Val. Epoch: 39, summary_loss: 0.65632, final_score: 0.15934, time: 24.66971 + +2021-06-26T10:34:41.882648 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 40, summary_loss: 0.27441, final_score: 0.09098, time: 387.64766 +[RESULT]: Val. Epoch: 40, summary_loss: 0.54924, final_score: 0.13237, time: 24.70901 + +2021-06-26T10:41:34.407493 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 41, summary_loss: 0.27413, final_score: 0.08810, time: 387.86559 +[RESULT]: Val. Epoch: 41, summary_loss: 0.35241, final_score: 0.13736, time: 24.51835 + +2021-06-26T10:48:26.983544 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 42, summary_loss: 0.27318, final_score: 0.08610, time: 386.95095 +[RESULT]: Val. Epoch: 42, summary_loss: 0.41677, final_score: 0.12038, time: 24.53792 + +2021-06-26T10:55:18.625770 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 43, summary_loss: 0.26768, final_score: 0.08585, time: 387.84921 +[RESULT]: Val. Epoch: 43, summary_loss: 0.45870, final_score: 0.12937, time: 24.52682 + +2021-06-26T11:02:11.162315 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 44, summary_loss: 0.25181, final_score: 0.07298, time: 387.01991 +[RESULT]: Val. Epoch: 44, summary_loss: 0.47015, final_score: 0.11938, time: 24.60477 + +2021-06-26T11:09:02.939671 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 45, summary_loss: 0.25109, final_score: 0.07436, time: 387.66273 +[RESULT]: Val. Epoch: 45, summary_loss: 0.40709, final_score: 0.12537, time: 24.52839 + +2021-06-26T11:15:55.339143 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.23999, final_score: 0.06661, time: 387.74166 +[RESULT]: Val. Epoch: 46, summary_loss: 0.52285, final_score: 0.12338, time: 25.01832 + +2021-06-26T11:22:48.305611 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.23524, final_score: 0.06498, time: 387.57106 +[RESULT]: Val. Epoch: 47, summary_loss: 0.59043, final_score: 0.13536, time: 24.63105 + +2021-06-26T11:29:40.671954 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.23568, final_score: 0.06523, time: 388.12516 +[RESULT]: Val. Epoch: 48, summary_loss: 0.54253, final_score: 0.13087, time: 24.63321 + +2021-06-26T11:36:33.624107 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.23871, final_score: 0.06623, time: 387.19102 +[RESULT]: Val. Epoch: 49, summary_loss: 0.45426, final_score: 0.12238, time: 24.63515 + +2021-06-26T11:43:25.605314 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.23108, final_score: 0.06498, time: 386.74639 +[RESULT]: Val. Epoch: 50, summary_loss: 0.46794, final_score: 0.12088, time: 24.38114 + +2021-06-26T11:50:16.924842 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.23162, final_score: 0.06436, time: 386.47189 +[RESULT]: Val. Epoch: 51, summary_loss: 0.48955, final_score: 0.12288, time: 25.23351 + +2021-06-26T11:57:08.840197 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.22705, final_score: 0.06011, time: 387.06831 +[RESULT]: Val. Epoch: 52, summary_loss: 0.53186, final_score: 0.12637, time: 24.80012 + +2021-06-26T12:04:00.892398 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.23023, final_score: 0.06236, time: 387.10743 +[RESULT]: Val. Epoch: 53, summary_loss: 0.46651, final_score: 0.12288, time: 24.61362 + +2021-06-26T12:10:52.814244 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.22779, final_score: 0.06086, time: 387.25374 +[RESULT]: Val. Epoch: 54, summary_loss: 0.52609, final_score: 0.12887, time: 24.41384 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..155f37187928d3ce8f61df6c19adc93e1105cad8 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..308b76458627d6bfc7e174d2cd178fbf1f530b87 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f791882a9b3e1fb92526f05f587ef4c3855c1e2a9f731b557a8f9591d0120370 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..95035845ff2ed0da77e2b86232d49495162dcd1b --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_2/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:34.746418 +LR: 6.25e-05 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 30, summary_loss: 0.42995, final_score: 0.19358, time: 389.29355 +[RESULT]: Val. Epoch: 30, summary_loss: 0.67922, final_score: 0.23077, time: 24.61853 + +2021-06-26T08:58:28.940542 +LR: 6.25e-05 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.41980, final_score: 0.18570, time: 387.70188 +[RESULT]: Val. Epoch: 31, summary_loss: 0.70254, final_score: 0.23826, time: 24.54659 + +2021-06-26T09:05:21.352765 +LR: 6.25e-05 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 32, summary_loss: 0.41225, final_score: 0.18120, time: 387.78543 +[RESULT]: Val. Epoch: 32, summary_loss: 0.56268, final_score: 0.22677, time: 24.24182 + +2021-06-26T09:12:13.557389 +LR: 6.25e-05 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.41338, final_score: 0.18170, time: 387.95619 +[RESULT]: Val. Epoch: 33, summary_loss: 0.60657, final_score: 0.22777, time: 24.85880 + +2021-06-26T09:19:06.531885 +LR: 6.25e-05 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 34, summary_loss: 0.41191, final_score: 0.18283, time: 387.20181 +[RESULT]: Val. Epoch: 34, summary_loss: 0.69257, final_score: 0.22827, time: 24.41624 + +2021-06-26T09:25:58.311888 +LR: 6.25e-05 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.40911, final_score: 0.17621, time: 387.53704 +[RESULT]: Val. Epoch: 35, summary_loss: 0.59160, final_score: 0.22128, time: 24.42617 + +2021-06-26T09:32:50.471594 +LR: 6.25e-05 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.40209, final_score: 0.17121, time: 388.37273 +[RESULT]: Val. Epoch: 36, summary_loss: 0.51430, final_score: 0.21528, time: 24.69248 + +2021-06-26T09:39:43.700504 +LR: 6.25e-05 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.39643, final_score: 0.16908, time: 388.50904 +[RESULT]: Val. Epoch: 37, summary_loss: 0.65553, final_score: 0.22278, time: 24.42360 + +2021-06-26T09:46:36.808914 +LR: 6.25e-05 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.39790, final_score: 0.17196, time: 388.64464 +[RESULT]: Val. Epoch: 38, summary_loss: 0.58430, final_score: 0.20929, time: 24.39609 + +2021-06-26T09:53:30.017623 +LR: 6.25e-05 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.38857, final_score: 0.16433, time: 388.12736 +[RESULT]: Val. Epoch: 39, summary_loss: 0.69184, final_score: 0.22078, time: 24.39248 + +2021-06-26T10:00:22.716457 +LR: 6.25e-05 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.39156, final_score: 0.16671, time: 388.79286 +[RESULT]: Val. Epoch: 40, summary_loss: 0.79522, final_score: 0.23477, time: 24.63407 + +2021-06-26T10:07:16.323725 +LR: 6.25e-05 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.38723, final_score: 0.16396, time: 387.51142 +[RESULT]: Val. Epoch: 41, summary_loss: 0.82330, final_score: 0.23377, time: 24.58522 + +2021-06-26T10:14:08.615734 +LR: 6.25e-05 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 42, summary_loss: 0.38634, final_score: 0.15909, time: 388.02410 +[RESULT]: Val. Epoch: 42, summary_loss: 0.61075, final_score: 0.21778, time: 24.47247 + +2021-06-26T10:21:01.293905 +LR: 6.25e-05 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.38020, final_score: 0.15559, time: 388.46509 +[RESULT]: Val. Epoch: 43, summary_loss: 0.61384, final_score: 0.22028, time: 24.28219 + +2021-06-26T10:27:54.220408 +LR: 6.25e-05 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 44, summary_loss: 0.37754, final_score: 0.15471, time: 388.45471 +[RESULT]: Val. Epoch: 44, summary_loss: 0.65206, final_score: 0.21479, time: 24.62960 + +2021-06-26T10:34:47.474053 +LR: 6.25e-05 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.37752, final_score: 0.15471, time: 388.22375 +[RESULT]: Val. Epoch: 45, summary_loss: 0.66694, final_score: 0.22478, time: 24.73876 + +2021-06-26T10:41:40.605608 +LR: 6.25e-05 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 46, summary_loss: 0.37542, final_score: 0.15634, time: 387.72581 +[RESULT]: Val. Epoch: 46, summary_loss: 0.72321, final_score: 0.22378, time: 24.48023 + +2021-06-26T10:48:33.017106 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.37311, final_score: 0.15584, time: 387.63808 +[RESULT]: Val. Epoch: 47, summary_loss: 0.76962, final_score: 0.22428, time: 24.30711 + +2021-06-26T10:55:25.124627 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.36553, final_score: 0.15071, time: 387.90843 +[RESULT]: Val. Epoch: 48, summary_loss: 0.55147, final_score: 0.21129, time: 24.54059 + +2021-06-26T11:02:17.747466 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.35409, final_score: 0.14159, time: 388.23691 +[RESULT]: Val. Epoch: 49, summary_loss: 0.66907, final_score: 0.21578, time: 24.60097 + +2021-06-26T11:09:10.744491 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.35331, final_score: 0.14096, time: 389.83194 +[RESULT]: Val. Epoch: 50, summary_loss: 0.62906, final_score: 0.21379, time: 25.04806 + +2021-06-26T11:16:05.810385 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.35382, final_score: 0.13972, time: 388.00687 +[RESULT]: Val. Epoch: 51, summary_loss: 0.67049, final_score: 0.21578, time: 24.76148 + +2021-06-26T11:22:58.742227 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.34623, final_score: 0.13484, time: 388.38375 +[RESULT]: Val. Epoch: 52, summary_loss: 0.60105, final_score: 0.21079, time: 24.30279 + +2021-06-26T11:29:51.590221 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.34886, final_score: 0.14009, time: 388.46064 +[RESULT]: Val. Epoch: 53, summary_loss: 0.63358, final_score: 0.21029, time: 24.60254 + +2021-06-26T11:36:44.831607 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.34747, final_score: 0.13797, time: 387.68792 +[RESULT]: Val. Epoch: 54, summary_loss: 0.62560, final_score: 0.21029, time: 24.43520 + +2021-06-26T11:43:37.123329 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.34447, final_score: 0.13672, time: 388.06723 +[RESULT]: Val. Epoch: 55, summary_loss: 0.63056, final_score: 0.21079, time: 24.61228 + +2021-06-26T11:50:29.997207 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.34987, final_score: 0.13672, time: 388.53773 +[RESULT]: Val. Epoch: 56, summary_loss: 0.62713, final_score: 0.21229, time: 24.54574 + +2021-06-26T11:57:23.237659 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.34783, final_score: 0.13759, time: 387.53437 +[RESULT]: Val. Epoch: 57, summary_loss: 0.59475, final_score: 0.20879, time: 24.35366 + +2021-06-26T12:04:15.300490 +LR: 9.765625e-07 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.34976, final_score: 0.13622, time: 387.98264 +[RESULT]: Val. Epoch: 58, summary_loss: 0.67674, final_score: 0.21479, time: 24.93716 + +2021-06-26T12:11:08.387302 +LR: 9.765625e-07 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.34710, final_score: 0.13672, time: 388.18243 +[RESULT]: Val. Epoch: 59, summary_loss: 0.65448, final_score: 0.21329, time: 24.49351 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..d8a94126cb0ca24c7cfe1888a7bf7d1c131e358d Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-052epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-052epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..06c9539b1ee13018f88a65160f222538bc021826 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-052epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e802d9b477badfdee29bf2fdfb2a59da0f5ca392ce5b77b2f51e90283b971bf7 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-055epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-055epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..ffee9a37ded9eb891a64f3ac9f093d9444bce936 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-055epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2562aebcaaf01068e263faa02e14d625fda06090fe752ecd8dd80f2654620cbf +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-056epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-056epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..0f1bba40033c6e19fddb8bd866eb7c1159128f22 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/best-checkpoint-056epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8379240b2b51af8b2ac96c853f92b75352c0a8537f1703fe575377d28d86dd5d +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..a1c5e930b5e235b8016dc5bbe3a7d30e777c3eb8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5a85d7232ede2f0238af2434dfb7fd9be46d75b0bc90c3e66bb9435e34df4ae0 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..9e40899eabef5c9491b8345a73c68230681ba26a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_3/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:09.459660 +LR: 0.00025 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 30, summary_loss: 0.51650, final_score: 0.25931, time: 390.32434 +[RESULT]: Val. Epoch: 30, summary_loss: 0.52040, final_score: 0.24625, time: 25.67636 + +2021-06-26T08:58:05.746251 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.50259, final_score: 0.24594, time: 388.65300 +[RESULT]: Val. Epoch: 31, summary_loss: 0.49087, final_score: 0.23077, time: 25.56779 + +2021-06-26T09:05:00.183003 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 32, summary_loss: 0.49445, final_score: 0.24031, time: 388.41512 +[RESULT]: Val. Epoch: 32, summary_loss: 0.87927, final_score: 0.26474, time: 26.10995 + +2021-06-26T09:11:54.915324 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.47891, final_score: 0.23182, time: 388.54744 +[RESULT]: Val. Epoch: 33, summary_loss: 0.50617, final_score: 0.22328, time: 25.20968 + +2021-06-26T09:18:48.878039 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 34, summary_loss: 0.46401, final_score: 0.21532, time: 388.79213 +[RESULT]: Val. Epoch: 34, summary_loss: 0.45981, final_score: 0.20679, time: 24.90592 + +2021-06-26T09:25:42.962681 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.44789, final_score: 0.19545, time: 388.66114 +[RESULT]: Val. Epoch: 35, summary_loss: 0.45350, final_score: 0.20679, time: 25.21324 + +2021-06-26T09:32:37.226172 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.44320, final_score: 0.19720, time: 388.67089 +[RESULT]: Val. Epoch: 36, summary_loss: 0.43578, final_score: 0.18581, time: 25.88566 + +2021-06-26T09:39:32.193070 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.42570, final_score: 0.18670, time: 388.56963 +[RESULT]: Val. Epoch: 37, summary_loss: 0.45228, final_score: 0.16384, time: 25.73871 + +2021-06-26T09:46:26.706665 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.41397, final_score: 0.17633, time: 388.43301 +[RESULT]: Val. Epoch: 38, summary_loss: 0.68539, final_score: 0.19381, time: 25.55945 + +2021-06-26T09:53:20.896693 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.40238, final_score: 0.16971, time: 388.69320 +[RESULT]: Val. Epoch: 39, summary_loss: 0.58084, final_score: 0.20629, time: 25.85882 + +2021-06-26T10:00:15.658935 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.39666, final_score: 0.16508, time: 388.57701 +[RESULT]: Val. Epoch: 40, summary_loss: 0.51936, final_score: 0.18432, time: 25.42410 + +2021-06-26T10:07:09.894199 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.38515, final_score: 0.15771, time: 388.46965 +[RESULT]: Val. Epoch: 41, summary_loss: 0.38985, final_score: 0.14186, time: 25.31782 + +2021-06-26T10:14:04.097533 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 42, summary_loss: 0.37569, final_score: 0.15134, time: 388.75253 +[RESULT]: Val. Epoch: 42, summary_loss: 0.36786, final_score: 0.13437, time: 25.48291 + +2021-06-26T10:20:58.807546 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.36880, final_score: 0.14634, time: 389.07282 +[RESULT]: Val. Epoch: 43, summary_loss: 0.38298, final_score: 0.14486, time: 25.25338 + +2021-06-26T10:27:53.334970 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 44, summary_loss: 0.36286, final_score: 0.14334, time: 388.52595 +[RESULT]: Val. Epoch: 44, summary_loss: 0.36726, final_score: 0.13686, time: 25.93888 + +2021-06-26T10:34:48.206563 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.35234, final_score: 0.13122, time: 389.39170 +[RESULT]: Val. Epoch: 45, summary_loss: 0.35557, final_score: 0.13187, time: 25.87841 + +2021-06-26T10:41:43.902037 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 46, summary_loss: 0.36120, final_score: 0.14009, time: 388.55408 +[RESULT]: Val. Epoch: 46, summary_loss: 0.39779, final_score: 0.14885, time: 25.53296 + +2021-06-26T10:48:38.219614 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.33871, final_score: 0.12672, time: 388.62483 +[RESULT]: Val. Epoch: 47, summary_loss: 0.43585, final_score: 0.12837, time: 25.07554 + +2021-06-26T10:55:32.124228 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.34153, final_score: 0.12447, time: 388.45268 +[RESULT]: Val. Epoch: 48, summary_loss: 0.35315, final_score: 0.12388, time: 25.15313 + +2021-06-26T11:02:26.260273 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.33543, final_score: 0.12322, time: 388.36122 +[RESULT]: Val. Epoch: 49, summary_loss: 0.35221, final_score: 0.12388, time: 25.36538 + +2021-06-26T11:09:20.394973 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.32933, final_score: 0.11835, time: 388.41048 +[RESULT]: Val. Epoch: 50, summary_loss: 0.46663, final_score: 0.11588, time: 25.43111 + +2021-06-26T11:16:14.430539 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.33846, final_score: 0.12172, time: 388.74174 +[RESULT]: Val. Epoch: 51, summary_loss: 0.50982, final_score: 0.13137, time: 25.32841 + +2021-06-26T11:23:08.711955 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.30410, final_score: 0.10285, time: 388.81398 +[RESULT]: Val. Epoch: 52, summary_loss: 0.33134, final_score: 0.11389, time: 25.21264 + +2021-06-26T11:30:03.156146 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.29221, final_score: 0.09173, time: 388.77272 +[RESULT]: Val. Epoch: 53, summary_loss: 0.36525, final_score: 0.11189, time: 25.78468 + +2021-06-26T11:36:57.920701 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.28933, final_score: 0.09248, time: 388.43862 +[RESULT]: Val. Epoch: 54, summary_loss: 0.34538, final_score: 0.11139, time: 25.24311 + +2021-06-26T11:43:51.860846 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.26865, final_score: 0.08110, time: 388.70646 +[RESULT]: Val. Epoch: 55, summary_loss: 0.32888, final_score: 0.10739, time: 25.91459 + +2021-06-26T11:50:46.887124 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.26952, final_score: 0.08073, time: 389.00368 +[RESULT]: Val. Epoch: 56, summary_loss: 0.32820, final_score: 0.10440, time: 25.68913 + +2021-06-26T11:57:41.991934 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.27015, final_score: 0.08185, time: 388.69734 +[RESULT]: Val. Epoch: 57, summary_loss: 0.35212, final_score: 0.11339, time: 25.62221 + +2021-06-26T12:04:36.524916 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.25983, final_score: 0.07673, time: 388.43211 +[RESULT]: Val. Epoch: 58, summary_loss: 0.33837, final_score: 0.10789, time: 26.44676 + +2021-06-26T12:11:31.612006 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.24769, final_score: 0.06986, time: 388.75334 +[RESULT]: Val. Epoch: 59, summary_loss: 0.34362, final_score: 0.10340, time: 25.22180 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..d6dfa3ca843fce5ad64cfb6412862ec5048d7c19 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/best-checkpoint-044epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/best-checkpoint-044epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..ac62395b99426abeaa9b5fa8cc1d71ff08497773 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/best-checkpoint-044epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3d6947b98e2e50dd82c49c20d550d1bfac6c7c30c06adef313c98cd00c075821 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..28600c85debd06ad4d25ae95c142da18df878bf4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9f01bac3550e9fd7cf8940f717451d07a0d99298fc04d2a3e56036e3856caa42 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c5dba8e4b40c2de69840b0f62e546ab456243b9d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_4/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:34.951797 +LR: 6.25e-05 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 31, summary_loss: 0.48528, final_score: 0.22582, time: 394.03787 +[RESULT]: Val. Epoch: 31, summary_loss: 0.50595, final_score: 0.22328, time: 24.51910 + +2021-06-26T08:58:33.864129 +LR: 6.25e-05 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 32, summary_loss: 0.47613, final_score: 0.21895, time: 388.39636 +[RESULT]: Val. Epoch: 32, summary_loss: 0.54607, final_score: 0.22627, time: 24.59511 + +2021-06-26T09:05:27.015023 +LR: 6.25e-05 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 33, summary_loss: 0.46482, final_score: 0.21332, time: 388.26004 +[RESULT]: Val. Epoch: 33, summary_loss: 0.57591, final_score: 0.21928, time: 24.27717 + +2021-06-26T09:12:19.747551 +LR: 6.25e-05 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 34, summary_loss: 0.46521, final_score: 0.20820, time: 388.57429 +[RESULT]: Val. Epoch: 34, summary_loss: 0.49140, final_score: 0.21429, time: 24.47066 + +2021-06-26T09:19:12.947384 +LR: 6.25e-05 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 35, summary_loss: 0.45570, final_score: 0.20570, time: 387.96595 +[RESULT]: Val. Epoch: 35, summary_loss: 0.47701, final_score: 0.21079, time: 24.48185 + +2021-06-26T09:26:05.581596 +LR: 6.25e-05 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.45753, final_score: 0.20620, time: 387.72485 +[RESULT]: Val. Epoch: 36, summary_loss: 0.54588, final_score: 0.21079, time: 24.59346 + +2021-06-26T09:32:58.100606 +LR: 6.25e-05 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.45242, final_score: 0.20445, time: 387.75290 +[RESULT]: Val. Epoch: 37, summary_loss: 0.67157, final_score: 0.23676, time: 24.55085 + +2021-06-26T09:39:50.574867 +LR: 6.25e-05 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.45030, final_score: 0.20095, time: 387.43762 +[RESULT]: Val. Epoch: 38, summary_loss: 0.52380, final_score: 0.21329, time: 24.57061 + +2021-06-26T09:46:42.755386 +LR: 6.25e-05 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.44206, final_score: 0.19320, time: 387.54169 +[RESULT]: Val. Epoch: 39, summary_loss: 0.52783, final_score: 0.22028, time: 24.41045 + +2021-06-26T09:53:34.873002 +LR: 6.25e-05 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.44847, final_score: 0.19845, time: 388.49037 +[RESULT]: Val. Epoch: 40, summary_loss: 0.51061, final_score: 0.21029, time: 24.42819 + +2021-06-26T10:00:27.990670 +LR: 6.25e-05 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.44481, final_score: 0.19258, time: 387.55984 +[RESULT]: Val. Epoch: 41, summary_loss: 0.54806, final_score: 0.21379, time: 24.36468 + +2021-06-26T10:07:20.104854 +LR: 6.25e-05 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 42, summary_loss: 0.43291, final_score: 0.19270, time: 387.59194 +[RESULT]: Val. Epoch: 42, summary_loss: 0.61024, final_score: 0.21528, time: 24.69611 + +2021-06-26T10:14:12.574422 +LR: 6.25e-05 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 43, summary_loss: 0.43436, final_score: 0.18720, time: 387.40930 +[RESULT]: Val. Epoch: 43, summary_loss: 0.53214, final_score: 0.20679, time: 24.94722 + +2021-06-26T10:21:05.131818 +LR: 6.25e-05 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 44, summary_loss: 0.42716, final_score: 0.18208, time: 388.42175 +[RESULT]: Val. Epoch: 44, summary_loss: 0.46493, final_score: 0.20330, time: 24.45278 + +2021-06-26T10:27:58.357033 +LR: 6.25e-05 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 45, summary_loss: 0.42908, final_score: 0.18695, time: 388.12367 +[RESULT]: Val. Epoch: 45, summary_loss: 0.47145, final_score: 0.20979, time: 24.37597 + +2021-06-26T10:34:51.024412 +LR: 6.25e-05 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 46, summary_loss: 0.41869, final_score: 0.17808, time: 387.95820 +[RESULT]: Val. Epoch: 46, summary_loss: 0.46866, final_score: 0.20529, time: 24.51194 + +2021-06-26T10:41:43.669478 +LR: 6.25e-05 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 47, summary_loss: 0.41704, final_score: 0.17971, time: 387.40636 +[RESULT]: Val. Epoch: 47, summary_loss: 0.50273, final_score: 0.20829, time: 24.48555 + +2021-06-26T10:48:35.717929 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.41466, final_score: 0.17796, time: 387.98320 +[RESULT]: Val. Epoch: 48, summary_loss: 0.47251, final_score: 0.20729, time: 24.24158 + +2021-06-26T10:55:28.124435 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.40947, final_score: 0.17171, time: 387.58525 +[RESULT]: Val. Epoch: 49, summary_loss: 0.47494, final_score: 0.20679, time: 24.42639 + +2021-06-26T11:02:20.304871 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.41267, final_score: 0.17983, time: 387.91582 +[RESULT]: Val. Epoch: 50, summary_loss: 0.47644, final_score: 0.20480, time: 24.35416 + +2021-06-26T11:09:12.754244 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.39891, final_score: 0.16633, time: 387.82349 +[RESULT]: Val. Epoch: 51, summary_loss: 0.52998, final_score: 0.20480, time: 24.78755 + +2021-06-26T11:16:05.566613 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.39872, final_score: 0.16646, time: 388.10375 +[RESULT]: Val. Epoch: 52, summary_loss: 0.53747, final_score: 0.20480, time: 24.59043 + +2021-06-26T11:22:58.435615 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.39590, final_score: 0.16458, time: 387.75568 +[RESULT]: Val. Epoch: 53, summary_loss: 0.49574, final_score: 0.20380, time: 24.41638 + +2021-06-26T11:29:50.768179 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.38986, final_score: 0.16346, time: 387.31763 +[RESULT]: Val. Epoch: 54, summary_loss: 0.50702, final_score: 0.20180, time: 24.40626 + +2021-06-26T11:36:42.704641 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.39229, final_score: 0.16308, time: 387.83326 +[RESULT]: Val. Epoch: 55, summary_loss: 0.51658, final_score: 0.20130, time: 24.51242 + +2021-06-26T11:43:35.234199 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.37997, final_score: 0.15121, time: 387.74178 +[RESULT]: Val. Epoch: 56, summary_loss: 0.53302, final_score: 0.19880, time: 24.50913 + +2021-06-26T11:50:27.690299 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.38075, final_score: 0.15534, time: 387.73603 +[RESULT]: Val. Epoch: 57, summary_loss: 0.51409, final_score: 0.20280, time: 24.96847 + +2021-06-26T11:57:20.566789 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.38482, final_score: 0.15671, time: 388.40546 +[RESULT]: Val. Epoch: 58, summary_loss: 0.52065, final_score: 0.19830, time: 24.84498 + +2021-06-26T12:04:13.996915 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.38061, final_score: 0.15471, time: 387.39454 +[RESULT]: Val. Epoch: 59, summary_loss: 0.50388, final_score: 0.20130, time: 24.51489 + +2021-06-26T12:11:06.105981 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 60, summary_loss: 0.38285, final_score: 0.15509, time: 387.60986 +[RESULT]: Val. Epoch: 60, summary_loss: 0.51466, final_score: 0.20230, time: 24.51543 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..3c901f4fc161d1606f143f74b6282137a6682841 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..79ab7d81c41ddaa5d98e34bf937b5ccb64f64918 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4954c04d4d6c777fd94070fa8a19b9fa36a0a16af2f79ef525116da29547b721 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..33081965c4a178e3f924526ee54ba1d701c726de --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fdd870fb35e03bbcb2f028555e1da6433348ff87fb29ad7b468fbf49d0457288 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-030epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-030epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..6a26cc3c9f9a3f0e44a121829a23d3bf3e832a0c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/best-checkpoint-030epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:481ee44a588fdba69aece5078539e4f9654b1892846ac2e898e3ef4879f18682 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..62a3fef1b56b266d408b1cc27f74e30d3d9330b4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:661ad86368d9ea46dd86ca4fbfe2df6c4e5b964f840f88b54ffe00b05a9d33d1 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..09dee1a4a3af5e365fee6dec7684638a02e43d42 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_5/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T13:12:50.354898 +LR: 0.0005 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 1, summary_loss: 0.70602, final_score: 0.49525, time: 388.07192 +[RESULT]: Val. Epoch: 1, summary_loss: 0.71807, final_score: 0.49700, time: 25.57164 + +2021-06-25T13:19:44.496412 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.70192, final_score: 0.49588, time: 387.20007 +[RESULT]: Val. Epoch: 2, summary_loss: 0.70151, final_score: 0.49700, time: 25.49152 + +2021-06-25T13:26:37.522744 +LR: 0.0005 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 3, summary_loss: 0.70156, final_score: 0.49538, time: 387.38365 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69374, final_score: 0.49700, time: 24.65585 + +2021-06-25T13:33:29.926209 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69713, final_score: 0.49513, time: 386.82793 +[RESULT]: Val. Epoch: 4, summary_loss: 0.70677, final_score: 0.49700, time: 25.50580 + +2021-06-25T13:40:22.419824 +LR: 0.0005 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69700, final_score: 0.49050, time: 387.16932 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69579, final_score: 0.49700, time: 24.70141 + +2021-06-25T13:47:14.496465 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69662, final_score: 0.49475, time: 386.83823 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69420, final_score: 0.49600, time: 25.24798 + +2021-06-25T13:54:06.774037 +LR: 0.0005 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69608, final_score: 0.48988, time: 386.46168 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69344, final_score: 0.49600, time: 25.10541 + +2021-06-25T14:00:58.701291 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69632, final_score: 0.49225, time: 386.94856 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69415, final_score: 0.49650, time: 24.81153 + +2021-06-25T14:07:50.651474 +LR: 0.0005 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69597, final_score: 0.49763, time: 387.55128 +[RESULT]: Val. Epoch: 9, summary_loss: 0.69869, final_score: 0.49850, time: 24.87049 + +2021-06-25T14:14:43.247125 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69568, final_score: 0.49538, time: 387.40625 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69823, final_score: 0.49700, time: 27.19469 + +2021-06-25T14:21:38.061757 +LR: 0.0005 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69614, final_score: 0.49675, time: 387.05980 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69383, final_score: 0.49650, time: 25.67637 + +2021-06-25T14:28:30.986978 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69500, final_score: 0.49213, time: 386.73328 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69460, final_score: 0.49600, time: 26.30622 + +2021-06-25T14:35:24.227647 +LR: 0.0005 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69535, final_score: 0.49588, time: 386.99557 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69885, final_score: 0.49750, time: 26.85491 + +2021-06-25T14:42:18.264268 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69547, final_score: 0.49325, time: 386.69156 +[RESULT]: Val. Epoch: 14, summary_loss: 0.69700, final_score: 0.49550, time: 27.29900 + +2021-06-25T14:49:12.456144 +LR: 0.0005 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69500, final_score: 0.49375, time: 386.82052 +[RESULT]: Val. Epoch: 15, summary_loss: 0.70039, final_score: 0.49800, time: 27.47697 + +2021-06-25T14:56:06.951500 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69572, final_score: 0.49800, time: 386.76330 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69475, final_score: 0.49800, time: 26.60330 + +2021-06-25T15:03:00.491648 +LR: 0.0005 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69515, final_score: 0.49363, time: 386.73874 +[RESULT]: Val. Epoch: 17, summary_loss: 0.69340, final_score: 0.49700, time: 26.93613 + +2021-06-25T15:09:54.557553 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.69557, final_score: 0.49938, time: 386.93188 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69630, final_score: 0.49700, time: 26.26630 + +2021-06-25T15:16:47.966516 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.69472, final_score: 0.49275, time: 386.76928 +[RESULT]: Val. Epoch: 19, summary_loss: 0.70250, final_score: 0.49700, time: 25.69056 + +2021-06-25T15:23:40.602182 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.69394, final_score: 0.49538, time: 387.18145 +[RESULT]: Val. Epoch: 20, summary_loss: 0.69468, final_score: 0.49650, time: 25.22309 + +2021-06-25T15:30:33.173452 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.69359, final_score: 0.49075, time: 387.03346 +[RESULT]: Val. Epoch: 21, summary_loss: 0.69651, final_score: 0.49750, time: 25.03267 + +2021-06-25T15:37:25.431371 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.69366, final_score: 0.49425, time: 387.39990 +[RESULT]: Val. Epoch: 22, summary_loss: 0.69332, final_score: 0.49700, time: 25.65029 + +2021-06-25T15:44:18.839765 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.69357, final_score: 0.49675, time: 387.02838 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69325, final_score: 0.49650, time: 25.11617 + +2021-06-25T15:51:11.320464 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.69353, final_score: 0.49463, time: 387.14437 +[RESULT]: Val. Epoch: 24, summary_loss: 0.69339, final_score: 0.49750, time: 24.93916 + +2021-06-25T15:58:03.572116 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.69379, final_score: 0.49750, time: 387.03623 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69329, final_score: 0.49451, time: 25.74146 + +2021-06-25T16:04:56.538000 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.69338, final_score: 0.49213, time: 387.46551 +[RESULT]: Val. Epoch: 26, summary_loss: 0.69316, final_score: 0.49750, time: 25.38042 + +2021-06-25T16:11:49.723325 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.69324, final_score: 0.49488, time: 386.99700 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69331, final_score: 0.49700, time: 25.82227 + +2021-06-25T16:18:42.712972 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.69349, final_score: 0.49463, time: 387.15581 +[RESULT]: Val. Epoch: 28, summary_loss: 0.69317, final_score: 0.49700, time: 25.05004 + +2021-06-25T16:25:35.090019 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.69333, final_score: 0.49263, time: 386.98540 +[RESULT]: Val. Epoch: 29, summary_loss: 0.69316, final_score: 0.49700, time: 25.87224 + +2021-06-25T16:32:28.349299 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 30, summary_loss: 0.69323, final_score: 0.49725, time: 387.24028 +[RESULT]: Val. Epoch: 30, summary_loss: 0.69315, final_score: 0.49550, time: 26.29589 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:34.818129 +LR: 0.000125 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 29, summary_loss: 0.61031, final_score: 0.34904, time: 393.37572 +[RESULT]: Val. Epoch: 29, summary_loss: 0.69634, final_score: 0.36414, time: 25.00097 + +2021-06-26T08:58:33.439867 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 30, summary_loss: 0.59849, final_score: 0.33542, time: 387.30442 +[RESULT]: Val. Epoch: 30, summary_loss: 0.68898, final_score: 0.36763, time: 24.46487 + +2021-06-26T09:05:25.362718 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.59599, final_score: 0.33717, time: 386.56003 +[RESULT]: Val. Epoch: 31, summary_loss: 0.65219, final_score: 0.35664, time: 24.59465 + +2021-06-26T09:12:16.673688 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 32, summary_loss: 0.59409, final_score: 0.33367, time: 386.77685 +[RESULT]: Val. Epoch: 32, summary_loss: 0.63144, final_score: 0.34066, time: 24.59544 + +2021-06-26T09:19:08.217182 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.58814, final_score: 0.32754, time: 386.66101 +[RESULT]: Val. Epoch: 33, summary_loss: 0.62428, final_score: 0.34565, time: 24.88612 + +2021-06-26T09:25:59.950074 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.58304, final_score: 0.31705, time: 387.07351 +[RESULT]: Val. Epoch: 34, summary_loss: 0.70805, final_score: 0.35415, time: 24.65773 + +2021-06-26T09:32:51.848423 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.57518, final_score: 0.31817, time: 386.84219 +[RESULT]: Val. Epoch: 35, summary_loss: 0.65410, final_score: 0.34316, time: 24.52500 + +2021-06-26T09:39:43.393728 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.57285, final_score: 0.31742, time: 386.74081 +[RESULT]: Val. Epoch: 36, summary_loss: 0.65289, final_score: 0.34515, time: 24.79754 + +2021-06-26T09:46:35.100565 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.57158, final_score: 0.31242, time: 387.35722 +[RESULT]: Val. Epoch: 37, summary_loss: 0.63065, final_score: 0.34016, time: 24.48876 + +2021-06-26T09:53:27.099757 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 38, summary_loss: 0.56069, final_score: 0.29768, time: 386.52288 +[RESULT]: Val. Epoch: 38, summary_loss: 0.64911, final_score: 0.34116, time: 24.50184 + +2021-06-26T10:00:18.285829 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.56060, final_score: 0.30155, time: 387.37413 +[RESULT]: Val. Epoch: 39, summary_loss: 0.69817, final_score: 0.34216, time: 24.78607 + +2021-06-26T10:07:10.624423 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.55844, final_score: 0.30055, time: 386.93000 +[RESULT]: Val. Epoch: 40, summary_loss: 0.60617, final_score: 0.32917, time: 24.61658 + +2021-06-26T10:14:02.318986 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.55195, final_score: 0.29480, time: 386.87160 +[RESULT]: Val. Epoch: 41, summary_loss: 0.64171, final_score: 0.32717, time: 24.62292 + +2021-06-26T10:20:54.006738 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 42, summary_loss: 0.54451, final_score: 0.28443, time: 387.11449 +[RESULT]: Val. Epoch: 42, summary_loss: 0.66682, final_score: 0.33566, time: 24.45066 + +2021-06-26T10:27:45.725369 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.54141, final_score: 0.28543, time: 386.89049 +[RESULT]: Val. Epoch: 43, summary_loss: 0.72086, final_score: 0.34216, time: 24.88520 + +2021-06-26T10:34:37.694004 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 44, summary_loss: 0.53959, final_score: 0.28280, time: 387.21788 +[RESULT]: Val. Epoch: 44, summary_loss: 0.71323, final_score: 0.34116, time: 24.77397 + +2021-06-26T10:41:29.846857 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.53554, final_score: 0.28455, time: 387.20419 +[RESULT]: Val. Epoch: 45, summary_loss: 0.62980, final_score: 0.32418, time: 24.58274 + +2021-06-26T10:48:21.801007 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.53223, final_score: 0.28068, time: 386.47484 +[RESULT]: Val. Epoch: 46, summary_loss: 0.67292, final_score: 0.32567, time: 24.53468 + +2021-06-26T10:55:12.968001 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.51415, final_score: 0.26756, time: 387.08927 +[RESULT]: Val. Epoch: 47, summary_loss: 0.70392, final_score: 0.32817, time: 24.50734 + +2021-06-26T11:02:04.723223 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.50960, final_score: 0.25831, time: 386.75787 +[RESULT]: Val. Epoch: 48, summary_loss: 0.77279, final_score: 0.32517, time: 24.60003 + +2021-06-26T11:08:56.248049 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.50107, final_score: 0.25044, time: 387.02289 +[RESULT]: Val. Epoch: 49, summary_loss: 0.68571, final_score: 0.31668, time: 24.71478 + +2021-06-26T11:15:48.193256 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.49172, final_score: 0.24644, time: 386.98536 +[RESULT]: Val. Epoch: 50, summary_loss: 0.71909, final_score: 0.31568, time: 24.63172 + +2021-06-26T11:22:39.973502 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.49744, final_score: 0.25131, time: 387.07160 +[RESULT]: Val. Epoch: 51, summary_loss: 0.66062, final_score: 0.31518, time: 24.53967 + +2021-06-26T11:29:31.741025 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.48860, final_score: 0.24081, time: 386.53191 +[RESULT]: Val. Epoch: 52, summary_loss: 0.70141, final_score: 0.31968, time: 24.62594 + +2021-06-26T11:36:23.051122 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.49212, final_score: 0.24656, time: 386.52617 +[RESULT]: Val. Epoch: 53, summary_loss: 0.65334, final_score: 0.31369, time: 24.76551 + +2021-06-26T11:43:14.513478 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.48425, final_score: 0.23682, time: 386.70800 +[RESULT]: Val. Epoch: 54, summary_loss: 0.70028, final_score: 0.31918, time: 24.84369 + +2021-06-26T11:50:06.227064 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.48892, final_score: 0.24106, time: 386.95304 +[RESULT]: Val. Epoch: 55, summary_loss: 0.72293, final_score: 0.32018, time: 24.42350 + +2021-06-26T11:56:57.751634 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.48811, final_score: 0.24019, time: 386.79275 +[RESULT]: Val. Epoch: 56, summary_loss: 0.67692, final_score: 0.31419, time: 24.52349 + +2021-06-26T12:03:49.230039 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.48191, final_score: 0.23857, time: 386.97632 +[RESULT]: Val. Epoch: 57, summary_loss: 0.67947, final_score: 0.31518, time: 24.93628 + +2021-06-26T12:10:41.301566 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.48445, final_score: 0.24119, time: 386.69968 +[RESULT]: Val. Epoch: 58, summary_loss: 0.67765, final_score: 0.31518, time: 24.64890 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..0002dd80678278d9a5272117bf93633d3f63863b Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..e84ffd45a74ec130546bd11a3f5f91df2c356d7a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b1cbe6901b349b02bfc62c38c449cd806d06ddc065e6875c76137d3681344446 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..988814196054d7981c2e1235d126bee1d59a4b05 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_6/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:34.871318 +LR: 0.00025 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 27, summary_loss: 0.64182, final_score: 0.38003, time: 396.70955 +[RESULT]: Val. Epoch: 27, summary_loss: 0.68277, final_score: 0.38511, time: 25.42992 + +2021-06-26T08:58:37.261255 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 28, summary_loss: 0.63047, final_score: 0.37191, time: 398.93124 +[RESULT]: Val. Epoch: 28, summary_loss: 0.65640, final_score: 0.38062, time: 25.37567 + +2021-06-26T09:05:41.757206 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 29, summary_loss: 0.62633, final_score: 0.36216, time: 399.40828 +[RESULT]: Val. Epoch: 29, summary_loss: 0.65271, final_score: 0.37013, time: 25.50675 + +2021-06-26T09:12:46.864378 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 30, summary_loss: 0.62445, final_score: 0.36441, time: 398.69447 +[RESULT]: Val. Epoch: 30, summary_loss: 0.63194, final_score: 0.36364, time: 25.70384 + +2021-06-26T09:19:51.420144 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 31, summary_loss: 0.61370, final_score: 0.35054, time: 400.47170 +[RESULT]: Val. Epoch: 31, summary_loss: 0.69707, final_score: 0.38262, time: 25.55036 + +2021-06-26T09:26:57.622638 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.61340, final_score: 0.34454, time: 400.20032 +[RESULT]: Val. Epoch: 32, summary_loss: 0.65725, final_score: 0.37113, time: 26.64530 + +2021-06-26T09:34:04.644206 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.60825, final_score: 0.35004, time: 399.32783 +[RESULT]: Val. Epoch: 33, summary_loss: 0.79461, final_score: 0.39860, time: 27.21509 + +2021-06-26T09:41:11.364024 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.60044, final_score: 0.33904, time: 399.58956 +[RESULT]: Val. Epoch: 34, summary_loss: 0.65076, final_score: 0.37313, time: 28.72279 + +2021-06-26T09:48:19.846070 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.59483, final_score: 0.33742, time: 401.08017 +[RESULT]: Val. Epoch: 35, summary_loss: 0.66680, final_score: 0.36014, time: 26.51499 + +2021-06-26T09:55:27.621281 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 36, summary_loss: 0.59047, final_score: 0.32179, time: 401.32324 +[RESULT]: Val. Epoch: 36, summary_loss: 0.63981, final_score: 0.34266, time: 27.07269 + +2021-06-26T10:02:36.219552 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.58733, final_score: 0.32767, time: 399.86861 +[RESULT]: Val. Epoch: 37, summary_loss: 0.63640, final_score: 0.36014, time: 25.86097 + +2021-06-26T10:09:42.127989 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 38, summary_loss: 0.58120, final_score: 0.31492, time: 401.08972 +[RESULT]: Val. Epoch: 38, summary_loss: 0.64121, final_score: 0.35964, time: 27.90065 + +2021-06-26T10:16:51.274807 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.57505, final_score: 0.31392, time: 401.10186 +[RESULT]: Val. Epoch: 39, summary_loss: 0.61498, final_score: 0.34316, time: 27.10740 + +2021-06-26T10:23:59.658394 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 40, summary_loss: 0.57414, final_score: 0.30855, time: 399.43115 +[RESULT]: Val. Epoch: 40, summary_loss: 0.61027, final_score: 0.33966, time: 27.27149 + +2021-06-26T10:31:06.524834 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 41, summary_loss: 0.57065, final_score: 0.30280, time: 402.19798 +[RESULT]: Val. Epoch: 41, summary_loss: 0.61571, final_score: 0.33017, time: 26.87844 + +2021-06-26T10:38:15.796656 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 42, summary_loss: 0.56083, final_score: 0.30167, time: 399.83574 +[RESULT]: Val. Epoch: 42, summary_loss: 0.83644, final_score: 0.34815, time: 27.11882 + +2021-06-26T10:45:22.928993 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 43, summary_loss: 0.55814, final_score: 0.30167, time: 400.60564 +[RESULT]: Val. Epoch: 43, summary_loss: 0.59728, final_score: 0.32368, time: 26.19783 + +2021-06-26T10:52:29.902323 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 44, summary_loss: 0.55466, final_score: 0.29668, time: 401.81656 +[RESULT]: Val. Epoch: 44, summary_loss: 0.76825, final_score: 0.35514, time: 26.96509 + +2021-06-26T10:59:38.842016 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 45, summary_loss: 0.52939, final_score: 0.26918, time: 401.34306 +[RESULT]: Val. Epoch: 45, summary_loss: 0.61311, final_score: 0.31868, time: 27.51581 + +2021-06-26T11:06:47.876890 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.53273, final_score: 0.27206, time: 402.54818 +[RESULT]: Val. Epoch: 46, summary_loss: 0.70063, final_score: 0.32168, time: 26.17904 + +2021-06-26T11:13:56.763840 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.49802, final_score: 0.24431, time: 402.34622 +[RESULT]: Val. Epoch: 47, summary_loss: 0.70344, final_score: 0.31069, time: 26.61697 + +2021-06-26T11:21:05.891374 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.49610, final_score: 0.25106, time: 401.61298 +[RESULT]: Val. Epoch: 48, summary_loss: 0.60944, final_score: 0.29421, time: 26.78845 + +2021-06-26T11:28:14.470120 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.49634, final_score: 0.24281, time: 400.48645 +[RESULT]: Val. Epoch: 49, summary_loss: 0.60251, final_score: 0.28521, time: 27.05935 + +2021-06-26T11:35:22.167452 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.48680, final_score: 0.23569, time: 401.23373 +[RESULT]: Val. Epoch: 50, summary_loss: 0.62084, final_score: 0.29371, time: 26.86574 + +2021-06-26T11:42:30.431951 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.48875, final_score: 0.24069, time: 402.75819 +[RESULT]: Val. Epoch: 51, summary_loss: 0.64799, final_score: 0.29920, time: 28.17242 + +2021-06-26T11:49:41.550198 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.47936, final_score: 0.23319, time: 400.69173 +[RESULT]: Val. Epoch: 52, summary_loss: 0.63820, final_score: 0.29520, time: 28.42883 + +2021-06-26T11:56:50.880720 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.47853, final_score: 0.23119, time: 401.35636 +[RESULT]: Val. Epoch: 53, summary_loss: 0.61858, final_score: 0.29121, time: 27.04798 + +2021-06-26T12:03:59.460353 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.47333, final_score: 0.22657, time: 401.00324 +[RESULT]: Val. Epoch: 54, summary_loss: 0.63457, final_score: 0.29271, time: 26.81237 + +2021-06-26T12:11:07.433841 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.47694, final_score: 0.23319, time: 402.89364 +[RESULT]: Val. Epoch: 55, summary_loss: 0.64273, final_score: 0.29421, time: 27.79826 + +2021-06-26T12:18:18.285960 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.47961, final_score: 0.23444, time: 402.91917 +[RESULT]: Val. Epoch: 56, summary_loss: 0.65779, final_score: 0.29920, time: 27.18008 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..676d181c473f6b646f7176158b6e45d3ab37ac2e Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..803849834769a910e7afc988e4f1e6eaced6f0e6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c61f8b41071aeabdd5636ac575a88d726b89064bbf22f01e40bf279e2e00c338 +size 48550161 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..113eee1804011991bf02aed55a2d2816133ef906 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_efnet_stego_7/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-26T08:51:34.812738 +LR: 0.00025 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 28, summary_loss: 0.62198, final_score: 0.35704, time: 389.07663 +[RESULT]: Val. Epoch: 28, summary_loss: 0.73102, final_score: 0.37912, time: 24.67301 + +2021-06-26T08:58:28.824399 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 29, summary_loss: 0.61719, final_score: 0.35854, time: 388.71833 +[RESULT]: Val. Epoch: 29, summary_loss: 0.62459, final_score: 0.34466, time: 24.60369 + +2021-06-26T09:05:22.321048 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 30, summary_loss: 0.61240, final_score: 0.34079, time: 388.45510 +[RESULT]: Val. Epoch: 30, summary_loss: 0.61551, final_score: 0.34715, time: 24.45844 + +2021-06-26T09:12:15.405447 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 31, summary_loss: 0.59814, final_score: 0.33417, time: 388.10702 +[RESULT]: Val. Epoch: 31, summary_loss: 0.68128, final_score: 0.37113, time: 24.61975 + +2021-06-26T09:19:08.296365 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 32, summary_loss: 0.59333, final_score: 0.32217, time: 388.38000 +[RESULT]: Val. Epoch: 32, summary_loss: 0.65862, final_score: 0.34565, time: 24.70014 + +2021-06-26T09:26:01.545199 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.58829, final_score: 0.32192, time: 388.58022 +[RESULT]: Val. Epoch: 33, summary_loss: 0.62476, final_score: 0.33616, time: 24.41181 + +2021-06-26T09:32:54.686130 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.58640, final_score: 0.32329, time: 388.34252 +[RESULT]: Val. Epoch: 34, summary_loss: 0.59775, final_score: 0.32068, time: 24.42277 + +2021-06-26T09:39:47.608370 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.57714, final_score: 0.30467, time: 389.08628 +[RESULT]: Val. Epoch: 35, summary_loss: 0.73906, final_score: 0.33467, time: 24.39984 + +2021-06-26T09:46:41.264491 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.57016, final_score: 0.30542, time: 388.35942 +[RESULT]: Val. Epoch: 36, summary_loss: 0.62777, final_score: 0.32318, time: 24.25280 + +2021-06-26T09:53:34.025967 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.56732, final_score: 0.30280, time: 388.97781 +[RESULT]: Val. Epoch: 37, summary_loss: 0.82878, final_score: 0.35265, time: 24.91817 + +2021-06-26T10:00:28.097362 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 38, summary_loss: 0.55450, final_score: 0.28980, time: 388.29815 +[RESULT]: Val. Epoch: 38, summary_loss: 0.63556, final_score: 0.31419, time: 24.33953 + +2021-06-26T10:07:20.902120 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.54920, final_score: 0.29368, time: 388.20282 +[RESULT]: Val. Epoch: 39, summary_loss: 0.63681, final_score: 0.30569, time: 24.53177 + +2021-06-26T10:14:13.809300 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.54225, final_score: 0.27381, time: 388.93556 +[RESULT]: Val. Epoch: 40, summary_loss: 0.55619, final_score: 0.27772, time: 24.89191 + +2021-06-26T10:21:07.799773 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 41, summary_loss: 0.53582, final_score: 0.27418, time: 388.83654 +[RESULT]: Val. Epoch: 41, summary_loss: 0.63391, final_score: 0.30619, time: 24.41779 + +2021-06-26T10:28:01.227572 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 42, summary_loss: 0.53232, final_score: 0.27043, time: 388.42106 +[RESULT]: Val. Epoch: 42, summary_loss: 0.54908, final_score: 0.27822, time: 24.55919 + +2021-06-26T10:34:54.365744 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 43, summary_loss: 0.52142, final_score: 0.25919, time: 388.71356 +[RESULT]: Val. Epoch: 43, summary_loss: 0.57905, final_score: 0.29071, time: 24.88255 + +2021-06-26T10:41:48.139742 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 44, summary_loss: 0.52742, final_score: 0.26443, time: 388.44117 +[RESULT]: Val. Epoch: 44, summary_loss: 0.57285, final_score: 0.28022, time: 24.52711 + +2021-06-26T10:48:41.296254 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 45, summary_loss: 0.49475, final_score: 0.23944, time: 388.80257 +[RESULT]: Val. Epoch: 45, summary_loss: 0.62250, final_score: 0.27473, time: 24.76020 + +2021-06-26T10:55:35.041925 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.48373, final_score: 0.23557, time: 388.93505 +[RESULT]: Val. Epoch: 46, summary_loss: 0.55190, final_score: 0.26124, time: 24.37286 + +2021-06-26T11:02:28.516571 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.47616, final_score: 0.23044, time: 388.88541 +[RESULT]: Val. Epoch: 47, summary_loss: 0.62666, final_score: 0.26823, time: 24.32772 + +2021-06-26T11:09:21.916119 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.46947, final_score: 0.22732, time: 388.77917 +[RESULT]: Val. Epoch: 48, summary_loss: 0.54585, final_score: 0.26024, time: 24.18521 + +2021-06-26T11:16:15.030848 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.46717, final_score: 0.22144, time: 388.40298 +[RESULT]: Val. Epoch: 49, summary_loss: 0.57985, final_score: 0.27123, time: 24.51857 + +2021-06-26T11:23:08.111883 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.46051, final_score: 0.21357, time: 388.71236 +[RESULT]: Val. Epoch: 50, summary_loss: 0.64621, final_score: 0.26773, time: 24.34487 + +2021-06-26T11:30:01.318577 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.43940, final_score: 0.20295, time: 388.50681 +[RESULT]: Val. Epoch: 51, summary_loss: 0.63897, final_score: 0.26573, time: 24.85100 + +2021-06-26T11:36:54.822661 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.43810, final_score: 0.20395, time: 388.70530 +[RESULT]: Val. Epoch: 52, summary_loss: 0.60816, final_score: 0.25624, time: 24.59521 + +2021-06-26T11:43:48.297148 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.42145, final_score: 0.19108, time: 388.29720 +[RESULT]: Val. Epoch: 53, summary_loss: 0.60151, final_score: 0.26124, time: 24.40429 + +2021-06-26T11:50:41.162345 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.42054, final_score: 0.19108, time: 387.98199 +[RESULT]: Val. Epoch: 54, summary_loss: 0.56442, final_score: 0.24426, time: 24.42691 + +2021-06-26T11:57:33.762346 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.41393, final_score: 0.18808, time: 388.18656 +[RESULT]: Val. Epoch: 55, summary_loss: 0.61554, final_score: 0.25624, time: 24.31777 + +2021-06-26T12:04:26.450586 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.40913, final_score: 0.17971, time: 388.60468 +[RESULT]: Val. Epoch: 56, summary_loss: 0.59057, final_score: 0.25175, time: 24.58495 + +2021-06-26T12:11:19.822019 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.41374, final_score: 0.18020, time: 388.35206 +[RESULT]: Val. Epoch: 57, summary_loss: 0.59711, final_score: 0.25225, time: 24.50948 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-015epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-015epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..18150739097741c69e8d569336be41cb393db3a0 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-015epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c7d5f98a5751f4464781b43d69a5fbfa48d126aa8e5bbd89f87c2d44a3ad5786 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-023epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-023epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..5a68f49cc07eec76ae30e525b7ab2deb6d07bff4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-023epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9bda0c73b5067bf1a6dda102b7d3119a213d231b9dffbaa72f526604ceccd5bd +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..5f6762f9700ed61e0574f9d70ba0d8d6e9511227 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:345914b4334a94e6a06ad774c5d5bb0ee02c4275fe3a751bf41aea4e59e907c2 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..ee7e3b6a892a10bd0faa29a4d1c75147957b4f7d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a2561d27ff3e99dde1e7609acf69bef2e365890ddd9c4c3a0cf68cc3a4385eed +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..76560b1d03128f4c4f45bb008bb5a2abcd43993e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/log.txt @@ -0,0 +1,202 @@ +Fitter prepared. Device is cuda:0 + +2021-04-12T08:05:13.627147 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-12T08:15:46.004401 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69266, final_score: 0.46663, time: 411.31687 +[RESULT]: Val. Epoch: 0, summary_loss: 1.27957, final_score: 0.49500, time: 113.61637 + +2021-04-12T08:24:31.494324 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.64450, final_score: 0.36816, time: 419.12661 +[RESULT]: Val. Epoch: 1, summary_loss: 0.90761, final_score: 0.44605, time: 112.53803 + +2021-04-12T08:33:23.512772 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.43485, final_score: 0.17108, time: 416.39443 +[RESULT]: Val. Epoch: 2, summary_loss: 0.87840, final_score: 0.32817, time: 110.97938 + +2021-04-12T08:42:11.241254 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.31509, final_score: 0.09285, time: 412.41331 +[RESULT]: Val. Epoch: 3, summary_loss: 1.51086, final_score: 0.34865, time: 108.68435 + +2021-04-12T08:50:52.900790 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.24100, final_score: 0.05036, time: 415.51946 +[RESULT]: Val. Epoch: 4, summary_loss: 1.21758, final_score: 0.26124, time: 111.00738 + +2021-04-12T08:59:39.707385 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.23943, final_score: 0.04861, time: 417.56336 +[RESULT]: Val. Epoch: 5, summary_loss: 0.61465, final_score: 0.22927, time: 112.75383 + +2021-04-12T09:08:30.387650 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22602, final_score: 0.04049, time: 425.10885 +[RESULT]: Val. Epoch: 6, summary_loss: 0.79314, final_score: 0.20979, time: 112.08447 + +2021-04-12T09:17:27.751615 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.25971, final_score: 0.06211, time: 426.36526 +[RESULT]: Val. Epoch: 7, summary_loss: 0.61776, final_score: 0.22977, time: 111.80877 + +2021-04-12T09:26:26.143299 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.23237, final_score: 0.04461, time: 425.89023 +[RESULT]: Val. Epoch: 8, summary_loss: 1.23918, final_score: 0.24975, time: 111.66309 + +2021-04-12T09:35:23.884015 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.26334, final_score: 0.06411, time: 428.62160 +[RESULT]: Val. Epoch: 9, summary_loss: 0.47445, final_score: 0.17233, time: 111.52887 + +2021-04-12T09:44:24.471834 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.24073, final_score: 0.04949, time: 423.51209 +[RESULT]: Val. Epoch: 10, summary_loss: 0.63170, final_score: 0.17133, time: 108.78117 + +2021-04-12T09:53:16.949446 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.28133, final_score: 0.07536, time: 427.45016 +[RESULT]: Val. Epoch: 11, summary_loss: 1.11108, final_score: 0.23776, time: 112.74518 + +2021-04-12T10:02:17.582258 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.26087, final_score: 0.06373, time: 435.77290 +[RESULT]: Val. Epoch: 12, summary_loss: 1.72867, final_score: 0.25275, time: 113.72839 + +2021-04-12T10:11:27.264589 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.28921, final_score: 0.07786, time: 437.82740 +[RESULT]: Val. Epoch: 13, summary_loss: 2.84427, final_score: 0.33566, time: 113.94197 + +2021-04-12T10:20:39.217111 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.28432, final_score: 0.07248, time: 439.55967 +[RESULT]: Val. Epoch: 14, summary_loss: 0.45799, final_score: 0.12537, time: 111.93571 + +2021-04-12T10:29:51.133212 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.31104, final_score: 0.09385, time: 437.86513 +[RESULT]: Val. Epoch: 15, summary_loss: 0.45234, final_score: 0.11988, time: 113.01430 + +2021-04-12T10:39:02.382932 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.30356, final_score: 0.08560, time: 436.81560 +[RESULT]: Val. Epoch: 16, summary_loss: 0.65222, final_score: 0.14436, time: 113.19999 + +2021-04-12T10:48:12.639841 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.32020, final_score: 0.09948, time: 434.28371 +[RESULT]: Val. Epoch: 17, summary_loss: 0.70330, final_score: 0.16783, time: 112.22896 + +2021-04-12T10:57:19.333196 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.31683, final_score: 0.09098, time: 441.78845 +[RESULT]: Val. Epoch: 18, summary_loss: 0.50186, final_score: 0.13187, time: 112.38914 + +2021-04-12T11:06:34.350612 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.31139, final_score: 0.08898, time: 435.38680 +[RESULT]: Val. Epoch: 19, summary_loss: 0.85243, final_score: 0.19231, time: 113.23151 + +2021-04-12T11:15:43.189964 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.30156, final_score: 0.08310, time: 440.63462 +[RESULT]: Val. Epoch: 20, summary_loss: 0.46731, final_score: 0.12488, time: 113.19599 + +2021-04-12T11:24:57.202395 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.29356, final_score: 0.07986, time: 440.97827 +[RESULT]: Val. Epoch: 21, summary_loss: 0.74142, final_score: 0.17632, time: 112.65722 + +2021-04-12T11:34:11.037427 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.30262, final_score: 0.09048, time: 440.13018 +[RESULT]: Val. Epoch: 22, summary_loss: 0.48624, final_score: 0.11888, time: 113.88775 + +2021-04-12T11:43:25.263579 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.26437, final_score: 0.06286, time: 440.99094 +[RESULT]: Val. Epoch: 23, summary_loss: 0.35886, final_score: 0.09191, time: 113.06927 + +2021-04-12T11:52:39.732652 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.25464, final_score: 0.05886, time: 439.97573 +[RESULT]: Val. Epoch: 24, summary_loss: 0.46887, final_score: 0.11389, time: 111.17131 + +2021-04-12T12:01:51.064769 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.25448, final_score: 0.05874, time: 438.89510 +[RESULT]: Val. Epoch: 25, summary_loss: 0.61667, final_score: 0.14935, time: 113.28798 + +2021-04-12T12:11:03.430660 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.23771, final_score: 0.04836, time: 437.65083 +[RESULT]: Val. Epoch: 26, summary_loss: 0.71254, final_score: 0.12787, time: 112.67548 + +2021-04-12T12:20:13.949486 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.23966, final_score: 0.04999, time: 438.93199 +[RESULT]: Val. Epoch: 27, summary_loss: 0.55431, final_score: 0.10889, time: 114.08619 + +2021-04-12T12:29:27.216386 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.22740, final_score: 0.04274, time: 445.89171 +[RESULT]: Val. Epoch: 28, summary_loss: 0.42736, final_score: 0.09491, time: 115.77842 + +2021-04-12T12:38:49.060786 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.22583, final_score: 0.04024, time: 443.06060 +[RESULT]: Val. Epoch: 29, summary_loss: 0.33248, final_score: 0.06943, time: 112.46475 +Fitter prepared. Device is cuda:0 + +2021-04-12T13:51:48.509709 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-28T09:37:40.568357 +LR: 0.000125 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.49480, final_score: 0.20957, time: 672.13123 +[RESULT]: Val. Epoch: 30, summary_loss: 1.07944, final_score: 0.37562, time: 179.40447 + +2021-04-28T09:51:52.428460 +LR: 0.000125 +Emb_rate: 0.18000000000000002 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..86a2ff740b10ae5002b77eec4ef8799eb60ac8ce Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-002epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-002epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c00531962feb963946c3f701d08172281ba1e9a8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-002epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2e0464c5523a0d37c0c61bf69fa2e4a8eb2bfd66c17e2db0e46ae3226f58a609 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-031epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-031epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..94ba0fa9a4451422a74e9d68dfac50b24f1b386f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-031epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:304138396a7caf4bd481124657b0d13da9e0eac61fd41dd3706ce94ececf21d8 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-037epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-037epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..1a857a8f2444db083bc85e4888891d180d54dd36 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/best-checkpoint-037epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:df782ad0b12a14cb9b53594359c42fa4b7dd96a0b8483330f4aba8e35b0346f0 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..c62da2ac29acd0c94915f029fcb351263b9b9531 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6a3b633ad0d4d7a592b8a46779a719688da002ead8ef3ee946a011634a9c8e36 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ae7fe27ce56f25c3171958c516f5873b31a2c87c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/log.txt @@ -0,0 +1,242 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:47:08.076116 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.67579, final_score: 0.44239, time: 646.17002 +[RESULT]: Val. Epoch: 0, summary_loss: 7.11191, final_score: 0.49750, time: 180.61134 + +2021-04-26T10:00:55.236188 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.45130, final_score: 0.18495, time: 653.44277 +[RESULT]: Val. Epoch: 1, summary_loss: 1.05673, final_score: 0.49650, time: 183.10116 + +2021-04-26T10:14:52.116603 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40322, final_score: 0.15246, time: 653.08130 +[RESULT]: Val. Epoch: 2, summary_loss: 0.86610, final_score: 0.49401, time: 183.18653 + +2021-04-26T10:28:48.703352 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.42666, final_score: 0.17808, time: 656.00108 +[RESULT]: Val. Epoch: 3, summary_loss: 0.87118, final_score: 0.49001, time: 178.44443 + +2021-04-26T10:42:43.324527 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.41215, final_score: 0.15834, time: 655.25055 +[RESULT]: Val. Epoch: 4, summary_loss: 2.25717, final_score: 0.49151, time: 178.43446 + +2021-04-26T10:56:37.292422 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.32631, final_score: 0.09860, time: 661.94355 +[RESULT]: Val. Epoch: 5, summary_loss: 1.06681, final_score: 0.45654, time: 179.13513 + +2021-04-26T11:10:38.526426 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.24547, final_score: 0.05524, time: 657.80055 +[RESULT]: Val. Epoch: 6, summary_loss: 2.44698, final_score: 0.46603, time: 178.19766 + +2021-04-26T11:24:34.694107 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.26449, final_score: 0.06661, time: 663.41959 +[RESULT]: Val. Epoch: 7, summary_loss: 1.57971, final_score: 0.44156, time: 176.86412 + +2021-04-26T11:38:35.158484 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.23634, final_score: 0.04886, time: 661.63491 +[RESULT]: Val. Epoch: 8, summary_loss: 2.71651, final_score: 0.46054, time: 182.30619 + +2021-04-26T11:52:39.271277 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.27240, final_score: 0.06798, time: 666.13535 +[RESULT]: Val. Epoch: 9, summary_loss: 1.34887, final_score: 0.44456, time: 178.25349 + +2021-04-26T12:06:43.856410 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.26171, final_score: 0.06361, time: 667.66055 +[RESULT]: Val. Epoch: 10, summary_loss: 1.61627, final_score: 0.44256, time: 178.67625 + +2021-04-26T12:20:50.365779 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.29595, final_score: 0.08248, time: 668.15212 +[RESULT]: Val. Epoch: 11, summary_loss: 2.20656, final_score: 0.44705, time: 178.86459 + +2021-04-26T12:34:57.578748 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.28363, final_score: 0.07723, time: 659.54161 +[RESULT]: Val. Epoch: 12, summary_loss: 1.97817, final_score: 0.44206, time: 178.23861 + +2021-04-26T12:48:55.541659 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.31171, final_score: 0.09273, time: 667.59654 +[RESULT]: Val. Epoch: 13, summary_loss: 1.41760, final_score: 0.43007, time: 177.78063 + +2021-04-26T13:03:01.102667 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.29834, final_score: 0.08498, time: 666.54787 +[RESULT]: Val. Epoch: 14, summary_loss: 2.23853, final_score: 0.44555, time: 183.05013 + +2021-04-26T13:17:10.899130 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.34325, final_score: 0.11335, time: 668.03041 +[RESULT]: Val. Epoch: 15, summary_loss: 1.52987, final_score: 0.43457, time: 177.97533 + +2021-04-26T13:31:17.092482 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.32828, final_score: 0.10297, time: 671.69686 +[RESULT]: Val. Epoch: 16, summary_loss: 1.92752, final_score: 0.44056, time: 177.81627 + +2021-04-26T13:45:26.888930 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 17, summary_loss: 0.36467, final_score: 0.12334, time: 666.47828 +[RESULT]: Val. Epoch: 17, summary_loss: 1.15071, final_score: 0.40959, time: 180.49620 + +2021-04-26T13:59:34.067166 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.36169, final_score: 0.12209, time: 663.27361 +[RESULT]: Val. Epoch: 18, summary_loss: 1.16254, final_score: 0.42258, time: 177.60235 + +2021-04-26T14:13:35.267624 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.39640, final_score: 0.14584, time: 670.48746 +[RESULT]: Val. Epoch: 19, summary_loss: 0.97151, final_score: 0.41209, time: 176.44234 + +2021-04-26T14:27:42.410014 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.39130, final_score: 0.14196, time: 668.45065 +[RESULT]: Val. Epoch: 20, summary_loss: 1.74224, final_score: 0.43656, time: 178.55113 + +2021-04-26T14:41:49.607803 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 21, summary_loss: 0.41857, final_score: 0.15721, time: 672.04811 +[RESULT]: Val. Epoch: 21, summary_loss: 1.22675, final_score: 0.40559, time: 180.81749 + +2021-04-26T14:56:02.703014 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.41388, final_score: 0.15421, time: 673.03510 +[RESULT]: Val. Epoch: 22, summary_loss: 1.33998, final_score: 0.41209, time: 178.65884 + +2021-04-26T15:10:14.579777 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.44711, final_score: 0.17596, time: 674.67874 +[RESULT]: Val. Epoch: 23, summary_loss: 0.90155, final_score: 0.40010, time: 178.77535 + +2021-04-26T15:24:28.229902 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.44224, final_score: 0.17758, time: 675.76237 +[RESULT]: Val. Epoch: 24, summary_loss: 1.01245, final_score: 0.39760, time: 178.40961 + +2021-04-26T15:38:42.586833 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 25, summary_loss: 0.46122, final_score: 0.19095, time: 667.69875 +[RESULT]: Val. Epoch: 25, summary_loss: 1.21709, final_score: 0.38811, time: 180.50845 + +2021-04-26T15:52:50.981192 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.46618, final_score: 0.19320, time: 678.39998 +[RESULT]: Val. Epoch: 26, summary_loss: 0.99812, final_score: 0.40609, time: 179.95561 + +2021-04-26T16:07:09.521734 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 27, summary_loss: 0.49368, final_score: 0.21182, time: 669.97373 +[RESULT]: Val. Epoch: 27, summary_loss: 1.43572, final_score: 0.40609, time: 181.93191 + +2021-04-26T16:21:21.646331 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.48656, final_score: 0.21082, time: 670.95796 +[RESULT]: Val. Epoch: 28, summary_loss: 1.19070, final_score: 0.40759, time: 177.90370 + +2021-04-26T16:35:30.699451 +LR: 0.001 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 29, summary_loss: 0.51238, final_score: 0.22494, time: 672.72123 +[RESULT]: Val. Epoch: 29, summary_loss: 1.19053, final_score: 0.39560, time: 178.97294 +Fitter prepared. Device is cuda:0 + +2021-04-28T10:05:20.961383 +LR: 0.001 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.51816, final_score: 0.23607, time: 663.83323 +[RESULT]: Val. Epoch: 30, summary_loss: 1.20445, final_score: 0.39261, time: 179.16053 + +2021-04-28T10:19:24.143957 +LR: 0.001 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 31, summary_loss: 0.53975, final_score: 0.24881, time: 670.16255 +[RESULT]: Val. Epoch: 31, summary_loss: 0.69463, final_score: 0.37363, time: 179.48376 + +2021-04-28T10:33:34.325200 +LR: 0.001 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 32, summary_loss: 0.53825, final_score: 0.25369, time: 671.71156 +[RESULT]: Val. Epoch: 32, summary_loss: 0.74470, final_score: 0.37313, time: 180.71968 + +2021-04-28T10:47:46.924800 +LR: 0.001 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 33, summary_loss: 0.55866, final_score: 0.27418, time: 654.52229 +[RESULT]: Val. Epoch: 33, summary_loss: 0.73050, final_score: 0.37263, time: 178.60374 + +2021-04-28T11:01:40.262617 +LR: 0.001 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 34, summary_loss: 0.55321, final_score: 0.26506, time: 671.40594 +[RESULT]: Val. Epoch: 34, summary_loss: 1.06531, final_score: 0.40759, time: 178.78731 + +2021-04-28T11:15:50.658673 +LR: 0.001 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 35, summary_loss: 0.57587, final_score: 0.28255, time: 672.60641 +[RESULT]: Val. Epoch: 35, summary_loss: 0.83182, final_score: 0.37762, time: 179.78069 + +2021-04-28T11:30:03.233747 +LR: 0.001 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 36, summary_loss: 0.57467, final_score: 0.28505, time: 665.49745 +[RESULT]: Val. Epoch: 36, summary_loss: 0.86341, final_score: 0.38162, time: 180.47499 + +2021-04-28T11:44:09.383081 +LR: 0.001 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 37, summary_loss: 0.59265, final_score: 0.30517, time: 669.08984 +[RESULT]: Val. Epoch: 37, summary_loss: 0.68532, final_score: 0.35964, time: 181.16019 + +2021-04-28T11:58:19.970151 +LR: 0.001 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 38, summary_loss: 0.58437, final_score: 0.29118, time: 664.38468 +[RESULT]: Val. Epoch: 38, summary_loss: 0.69075, final_score: 0.37163, time: 178.86596 + +2021-04-28T12:12:23.371137 +LR: 0.001 +Emb_rate: 0.11809800000000004 +[RESULT]: Train. Epoch: 39, summary_loss: 0.59858, final_score: 0.31517, time: 669.13978 +[RESULT]: Val. Epoch: 39, summary_loss: 0.73019, final_score: 0.36164, time: 180.84094 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..e11b01a0811b5fab037f92cf3ba9668ef23c8b47 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-014epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-014epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a10ee89d580f91b46fb80e4f9bb366fe1d4c2636 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-014epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0d2fb0fe8b35994ff0932c85e69626ba5f110dc82c00a332eedd9f14b6bffa6a +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-023epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-023epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..cdc7c72efa1ac9e6672c948a69e94163b2b0c44e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-023epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:32099b15537c2612b4e8b153a63d4c79ae20cc8d92fd0fabf82df583c200dfe3 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..d6cc5bceedabe578212e76de00724ec36b9d4bfa --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:df0f9e6aa6e4d968837bc9930946f866e68f9c864f4df887ac21cd805b80440e +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..0bdd98db4f93ab1b86138e9aa518cdaa36e232c0 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:98d4842fb3288c61fb544f10910d1cba1fdad06a2d08c0809113d827ef3996c2 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..01984e7eab39cc7780c3094e65abbcde96183e4b --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.2/log.txt @@ -0,0 +1,182 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:43:24.948571 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69711, final_score: 0.47688, time: 650.76529 +[RESULT]: Val. Epoch: 0, summary_loss: 0.82406, final_score: 0.48801, time: 182.63257 + +2021-04-26T09:57:18.678656 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.50577, final_score: 0.23694, time: 644.24929 +[RESULT]: Val. Epoch: 1, summary_loss: 1.40181, final_score: 0.47153, time: 176.94400 + +2021-04-26T10:11:00.089493 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.29864, final_score: 0.08185, time: 661.70466 +[RESULT]: Val. Epoch: 2, summary_loss: 2.10868, final_score: 0.46054, time: 175.09514 + +2021-04-26T10:24:57.061614 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.27222, final_score: 0.06786, time: 649.29461 +[RESULT]: Val. Epoch: 3, summary_loss: 2.13104, final_score: 0.43856, time: 182.62071 + +2021-04-26T10:38:49.140433 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22396, final_score: 0.03849, time: 650.66432 +[RESULT]: Val. Epoch: 4, summary_loss: 1.65586, final_score: 0.42757, time: 176.11879 + +2021-04-26T10:52:36.088454 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24760, final_score: 0.05361, time: 655.57037 +[RESULT]: Val. Epoch: 5, summary_loss: 2.30787, final_score: 0.41009, time: 178.95763 + +2021-04-26T11:06:30.773472 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.23137, final_score: 0.04436, time: 657.49050 +[RESULT]: Val. Epoch: 6, summary_loss: 0.94150, final_score: 0.38711, time: 177.07402 + +2021-04-26T11:20:25.509476 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.24899, final_score: 0.05411, time: 663.33106 +[RESULT]: Val. Epoch: 7, summary_loss: 2.12884, final_score: 0.39610, time: 177.16665 + +2021-04-26T11:34:26.175461 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.24933, final_score: 0.05461, time: 663.86122 +[RESULT]: Val. Epoch: 8, summary_loss: 3.53307, final_score: 0.42957, time: 181.00685 + +2021-04-26T11:48:31.215869 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.27145, final_score: 0.06561, time: 672.78273 +[RESULT]: Val. Epoch: 9, summary_loss: 2.12893, final_score: 0.39660, time: 181.02754 + +2021-04-26T12:02:45.193710 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.25401, final_score: 0.06061, time: 663.91416 +[RESULT]: Val. Epoch: 10, summary_loss: 2.19078, final_score: 0.39361, time: 177.33893 + +2021-04-26T12:16:46.604723 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.29348, final_score: 0.08398, time: 665.41505 +[RESULT]: Val. Epoch: 11, summary_loss: 1.26069, final_score: 0.37512, time: 179.53604 + +2021-04-26T12:30:51.733854 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.28259, final_score: 0.07498, time: 663.94331 +[RESULT]: Val. Epoch: 12, summary_loss: 0.84845, final_score: 0.32817, time: 175.64789 + +2021-04-26T12:44:51.498356 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.31217, final_score: 0.09498, time: 656.43512 +[RESULT]: Val. Epoch: 13, summary_loss: 1.53083, final_score: 0.36314, time: 177.39041 + +2021-04-26T12:58:45.501464 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.29906, final_score: 0.08273, time: 658.48834 +[RESULT]: Val. Epoch: 14, summary_loss: 0.75309, final_score: 0.31818, time: 175.25316 + +2021-04-26T13:12:39.564961 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.32921, final_score: 0.10597, time: 662.53554 +[RESULT]: Val. Epoch: 15, summary_loss: 0.89084, final_score: 0.31718, time: 177.30701 + +2021-04-26T13:26:39.574867 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.33377, final_score: 0.10497, time: 664.39700 +[RESULT]: Val. Epoch: 16, summary_loss: 0.78219, final_score: 0.30869, time: 177.26596 + +2021-04-26T13:40:41.406060 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 17, summary_loss: 0.36172, final_score: 0.12172, time: 665.19463 +[RESULT]: Val. Epoch: 17, summary_loss: 2.29013, final_score: 0.40110, time: 176.41911 + +2021-04-26T13:54:43.181290 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.35093, final_score: 0.11735, time: 661.93207 +[RESULT]: Val. Epoch: 18, summary_loss: 0.77102, final_score: 0.29570, time: 177.56023 + +2021-04-26T14:08:42.835543 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.39029, final_score: 0.14409, time: 665.19917 +[RESULT]: Val. Epoch: 19, summary_loss: 1.08753, final_score: 0.35315, time: 177.47769 + +2021-04-26T14:22:45.714535 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.38474, final_score: 0.13997, time: 666.04964 +[RESULT]: Val. Epoch: 20, summary_loss: 0.87407, final_score: 0.31219, time: 178.91910 + +2021-04-26T14:36:50.866487 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 21, summary_loss: 0.42483, final_score: 0.16258, time: 661.72497 +[RESULT]: Val. Epoch: 21, summary_loss: 1.08079, final_score: 0.32068, time: 177.05642 + +2021-04-26T14:50:49.812140 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.41489, final_score: 0.15846, time: 663.34638 +[RESULT]: Val. Epoch: 22, summary_loss: 0.76775, final_score: 0.29171, time: 178.08436 + +2021-04-26T15:04:51.408748 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.44018, final_score: 0.17533, time: 670.07822 +[RESULT]: Val. Epoch: 23, summary_loss: 0.65625, final_score: 0.27273, time: 176.76233 + +2021-04-26T15:18:58.594864 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.43404, final_score: 0.17221, time: 666.26494 +[RESULT]: Val. Epoch: 24, summary_loss: 1.24978, final_score: 0.32468, time: 177.46173 + +2021-04-26T15:33:02.492452 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 25, summary_loss: 0.47069, final_score: 0.19208, time: 662.54267 +[RESULT]: Val. Epoch: 25, summary_loss: 0.99906, final_score: 0.31219, time: 177.46721 + +2021-04-26T15:47:02.673390 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.46859, final_score: 0.19595, time: 663.76427 +[RESULT]: Val. Epoch: 26, summary_loss: 0.95603, final_score: 0.31568, time: 176.18002 + +2021-04-26T16:01:02.797919 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 27, summary_loss: 0.49180, final_score: 0.21382, time: 667.86067 +[RESULT]: Val. Epoch: 27, summary_loss: 0.61231, final_score: 0.26324, time: 176.24345 + +2021-04-26T16:15:07.259631 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.49329, final_score: 0.21295, time: 678.75001 +[RESULT]: Val. Epoch: 28, summary_loss: 0.65580, final_score: 0.26324, time: 175.37806 + +2021-04-26T16:29:21.549848 +LR: 0.001 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 29, summary_loss: 0.51348, final_score: 0.23032, time: 663.45955 +[RESULT]: Val. Epoch: 29, summary_loss: 0.85986, final_score: 0.29670, time: 177.81262 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:39:39.092777 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.60828, final_score: 0.36053, time: 648.51146 +[RESULT]: Val. Epoch: 0, summary_loss: 1.58791, final_score: 0.47652, time: 180.86458 + +2021-04-26T09:53:28.851572 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.42515, final_score: 0.16896, time: 654.19481 +[RESULT]: Val. Epoch: 1, summary_loss: 0.80415, final_score: 0.46454, time: 179.73050 + +2021-04-26T10:07:23.166361 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.39611, final_score: 0.15009, time: 649.08123 +[RESULT]: Val. Epoch: 2, summary_loss: 0.88004, final_score: 0.46204, time: 183.54009 + +2021-04-26T10:21:15.968678 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.42690, final_score: 0.17671, time: 657.44223 +[RESULT]: Val. Epoch: 3, summary_loss: 0.82636, final_score: 0.44555, time: 177.41929 + +2021-04-26T10:35:11.002681 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.40284, final_score: 0.15809, time: 661.49872 +[RESULT]: Val. Epoch: 4, summary_loss: 1.22830, final_score: 0.45055, time: 176.47953 + +2021-04-26T10:49:09.162800 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.35963, final_score: 0.12384, time: 659.20285 +[RESULT]: Val. Epoch: 5, summary_loss: 1.61310, final_score: 0.38761, time: 177.65977 + +2021-04-26T11:03:06.186914 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.25964, final_score: 0.05886, time: 657.69542 +[RESULT]: Val. Epoch: 6, summary_loss: 1.23103, final_score: 0.35814, time: 181.24780 + +2021-04-26T11:17:05.291460 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.27006, final_score: 0.06836, time: 664.86677 +[RESULT]: Val. Epoch: 7, summary_loss: 0.72585, final_score: 0.31119, time: 180.43015 + +2021-04-26T11:31:10.929647 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.24420, final_score: 0.05249, time: 659.20489 +[RESULT]: Val. Epoch: 8, summary_loss: 1.34109, final_score: 0.32567, time: 177.36933 + +2021-04-26T11:45:07.747989 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.26992, final_score: 0.06861, time: 669.95051 +[RESULT]: Val. Epoch: 9, summary_loss: 0.78737, final_score: 0.27872, time: 181.32802 + +2021-04-26T11:59:19.201851 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.26331, final_score: 0.06273, time: 672.20847 +[RESULT]: Val. Epoch: 10, summary_loss: 0.97777, final_score: 0.28472, time: 177.65791 + +2021-04-26T12:13:29.239873 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.29187, final_score: 0.07973, time: 660.64080 +[RESULT]: Val. Epoch: 11, summary_loss: 2.23974, final_score: 0.35115, time: 179.25146 + +2021-04-26T12:27:29.292879 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.26943, final_score: 0.06811, time: 666.53248 +[RESULT]: Val. Epoch: 12, summary_loss: 1.20138, final_score: 0.26923, time: 177.72212 + +2021-04-26T12:41:33.716354 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.30822, final_score: 0.09160, time: 664.68858 +[RESULT]: Val. Epoch: 13, summary_loss: 1.35699, final_score: 0.28771, time: 178.35494 + +2021-04-26T12:55:36.935199 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.29745, final_score: 0.08310, time: 673.17323 +[RESULT]: Val. Epoch: 14, summary_loss: 0.68349, final_score: 0.22677, time: 176.68638 + +2021-04-26T13:09:47.174841 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.32711, final_score: 0.10272, time: 665.01909 +[RESULT]: Val. Epoch: 15, summary_loss: 0.72978, final_score: 0.23377, time: 178.03950 + +2021-04-26T13:23:50.402640 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.31645, final_score: 0.09835, time: 662.25855 +[RESULT]: Val. Epoch: 16, summary_loss: 0.56361, final_score: 0.19481, time: 177.64418 + +2021-04-26T13:37:50.848322 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 17, summary_loss: 0.35635, final_score: 0.11960, time: 672.39977 +[RESULT]: Val. Epoch: 17, summary_loss: 0.61029, final_score: 0.23526, time: 178.90975 + +2021-04-26T13:52:02.329362 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.34448, final_score: 0.11210, time: 676.64661 +[RESULT]: Val. Epoch: 18, summary_loss: 0.64138, final_score: 0.21628, time: 178.19812 + +2021-04-26T14:06:17.366029 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.38341, final_score: 0.13647, time: 668.92954 +[RESULT]: Val. Epoch: 19, summary_loss: 0.62668, final_score: 0.20729, time: 181.76893 + +2021-04-26T14:20:28.223536 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.37165, final_score: 0.13172, time: 670.96972 +[RESULT]: Val. Epoch: 20, summary_loss: 0.92589, final_score: 0.24376, time: 177.56115 + +2021-04-26T14:34:36.942189 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 21, summary_loss: 0.40383, final_score: 0.14859, time: 676.58603 +[RESULT]: Val. Epoch: 21, summary_loss: 0.50191, final_score: 0.18432, time: 177.88984 + +2021-04-26T14:48:51.743478 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.40388, final_score: 0.15209, time: 677.91446 +[RESULT]: Val. Epoch: 22, summary_loss: 0.84719, final_score: 0.21429, time: 177.66996 + +2021-04-26T15:03:07.517223 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 23, summary_loss: 0.41086, final_score: 0.15521, time: 669.98829 +[RESULT]: Val. Epoch: 23, summary_loss: 0.75048, final_score: 0.22677, time: 179.51779 + +2021-04-26T15:17:17.214154 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 24, summary_loss: 0.40662, final_score: 0.14984, time: 665.14754 +[RESULT]: Val. Epoch: 24, summary_loss: 0.62286, final_score: 0.22328, time: 178.52498 + +2021-04-26T15:31:21.068531 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 25, summary_loss: 0.39642, final_score: 0.15296, time: 676.32852 +[RESULT]: Val. Epoch: 25, summary_loss: 0.52393, final_score: 0.18132, time: 175.67741 + +2021-04-26T15:45:33.254889 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 26, summary_loss: 0.39451, final_score: 0.14709, time: 674.72835 +[RESULT]: Val. Epoch: 26, summary_loss: 0.62244, final_score: 0.19780, time: 177.22329 + +2021-04-26T15:59:45.374358 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 27, summary_loss: 0.38618, final_score: 0.13859, time: 662.86921 +[RESULT]: Val. Epoch: 27, summary_loss: 0.46132, final_score: 0.17932, time: 179.64371 + +2021-04-26T16:13:48.253184 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 28, summary_loss: 0.38674, final_score: 0.14046, time: 670.48612 +[RESULT]: Val. Epoch: 28, summary_loss: 0.66649, final_score: 0.18082, time: 177.38205 + +2021-04-26T16:27:56.316921 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 29, summary_loss: 0.37742, final_score: 0.13234, time: 666.18666 +[RESULT]: Val. Epoch: 29, summary_loss: 0.42151, final_score: 0.16733, time: 177.65247 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:40:31.493492 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.61027, final_score: 0.37041, time: 655.73743 +[RESULT]: Val. Epoch: 0, summary_loss: 0.81731, final_score: 0.40010, time: 179.77496 + +2021-04-26T09:54:27.374714 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.42485, final_score: 0.16608, time: 654.06191 +[RESULT]: Val. Epoch: 1, summary_loss: 0.74281, final_score: 0.37512, time: 178.15149 + +2021-04-26T10:08:19.993291 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40128, final_score: 0.15209, time: 652.15489 +[RESULT]: Val. Epoch: 2, summary_loss: 1.07863, final_score: 0.40809, time: 179.01198 + +2021-04-26T10:22:11.314666 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.44111, final_score: 0.18270, time: 650.13446 +[RESULT]: Val. Epoch: 3, summary_loss: 1.25907, final_score: 0.37712, time: 177.67006 + +2021-04-26T10:35:59.281163 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.42537, final_score: 0.17433, time: 655.96198 +[RESULT]: Val. Epoch: 4, summary_loss: 0.77291, final_score: 0.35015, time: 179.61991 + +2021-04-26T10:49:55.030262 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.44869, final_score: 0.18970, time: 649.24424 +[RESULT]: Val. Epoch: 5, summary_loss: 1.50323, final_score: 0.37712, time: 183.33534 + +2021-04-26T11:03:47.768145 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.36092, final_score: 0.12109, time: 652.61473 +[RESULT]: Val. Epoch: 6, summary_loss: 0.95117, final_score: 0.28222, time: 177.39571 + +2021-04-26T11:17:37.948150 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.33961, final_score: 0.10422, time: 659.76250 +[RESULT]: Val. Epoch: 7, summary_loss: 0.64073, final_score: 0.20679, time: 177.79524 + +2021-04-26T11:31:35.973029 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.27170, final_score: 0.06911, time: 658.29511 +[RESULT]: Val. Epoch: 8, summary_loss: 0.46548, final_score: 0.14286, time: 187.50166 + +2021-04-26T11:45:42.211403 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.30735, final_score: 0.09210, time: 656.35956 +[RESULT]: Val. Epoch: 9, summary_loss: 0.53658, final_score: 0.16034, time: 176.27714 + +2021-04-26T11:59:35.006886 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.27613, final_score: 0.07298, time: 655.83382 +[RESULT]: Val. Epoch: 10, summary_loss: 1.43560, final_score: 0.25425, time: 176.83301 + +2021-04-26T12:13:27.838024 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.30234, final_score: 0.08748, time: 673.69442 +[RESULT]: Val. Epoch: 11, summary_loss: 0.34318, final_score: 0.10240, time: 177.11018 + +2021-04-26T12:27:38.974567 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.29175, final_score: 0.08335, time: 667.40432 +[RESULT]: Val. Epoch: 12, summary_loss: 0.42782, final_score: 0.10340, time: 177.05084 + +2021-04-26T12:41:43.597233 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 13, summary_loss: 0.30404, final_score: 0.08910, time: 661.48874 +[RESULT]: Val. Epoch: 13, summary_loss: 1.05597, final_score: 0.22877, time: 179.09131 + +2021-04-26T12:55:44.329128 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 14, summary_loss: 0.28209, final_score: 0.07498, time: 666.35815 +[RESULT]: Val. Epoch: 14, summary_loss: 0.51096, final_score: 0.11888, time: 180.64558 + +2021-04-26T13:09:51.490958 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 15, summary_loss: 0.26052, final_score: 0.06361, time: 666.99624 +[RESULT]: Val. Epoch: 15, summary_loss: 0.43463, final_score: 0.10040, time: 181.58904 + +2021-04-26T13:24:00.226111 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 16, summary_loss: 0.25105, final_score: 0.05674, time: 663.77692 +[RESULT]: Val. Epoch: 16, summary_loss: 0.32543, final_score: 0.07493, time: 177.40409 + +2021-04-26T13:38:01.794945 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 17, summary_loss: 0.24437, final_score: 0.05261, time: 668.44578 +[RESULT]: Val. Epoch: 17, summary_loss: 0.65279, final_score: 0.10939, time: 177.31833 + +2021-04-26T13:52:07.710574 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 18, summary_loss: 0.24136, final_score: 0.05136, time: 662.46095 +[RESULT]: Val. Epoch: 18, summary_loss: 0.29055, final_score: 0.05594, time: 181.03122 + +2021-04-26T14:06:11.570632 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 19, summary_loss: 0.23408, final_score: 0.04811, time: 662.02845 +[RESULT]: Val. Epoch: 19, summary_loss: 0.51588, final_score: 0.09940, time: 177.61786 + +2021-04-26T14:20:11.377297 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 20, summary_loss: 0.23570, final_score: 0.04899, time: 661.73913 +[RESULT]: Val. Epoch: 20, summary_loss: 0.39668, final_score: 0.09141, time: 177.39045 + +2021-04-26T14:34:10.667777 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 21, summary_loss: 0.22120, final_score: 0.04024, time: 680.82303 +[RESULT]: Val. Epoch: 21, summary_loss: 0.51181, final_score: 0.09590, time: 178.24409 + +2021-04-26T14:48:29.900874 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 22, summary_loss: 0.21472, final_score: 0.03662, time: 673.32983 +[RESULT]: Val. Epoch: 22, summary_loss: 0.36562, final_score: 0.06494, time: 177.27054 + +2021-04-26T15:02:40.669427 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 23, summary_loss: 0.21087, final_score: 0.03487, time: 665.24968 +[RESULT]: Val. Epoch: 23, summary_loss: 0.33172, final_score: 0.05395, time: 178.39026 + +2021-04-26T15:16:44.474947 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 24, summary_loss: 0.20665, final_score: 0.03087, time: 671.25319 +[RESULT]: Val. Epoch: 24, summary_loss: 0.24121, final_score: 0.04945, time: 178.71725 + +2021-04-26T15:30:54.772666 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 25, summary_loss: 0.20640, final_score: 0.03074, time: 664.18154 +[RESULT]: Val. Epoch: 25, summary_loss: 0.46167, final_score: 0.07792, time: 177.85039 + +2021-04-26T15:44:56.968433 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 26, summary_loss: 0.20471, final_score: 0.03174, time: 666.18558 +[RESULT]: Val. Epoch: 26, summary_loss: 0.28373, final_score: 0.05095, time: 182.24367 + +2021-04-26T15:59:05.560133 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 27, summary_loss: 0.20273, final_score: 0.02974, time: 678.46432 +[RESULT]: Val. Epoch: 27, summary_loss: 0.45595, final_score: 0.07742, time: 183.55526 + +2021-04-26T16:13:27.777077 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 28, summary_loss: 0.20250, final_score: 0.03124, time: 669.03987 +[RESULT]: Val. Epoch: 28, summary_loss: 0.27101, final_score: 0.04945, time: 178.35006 + +2021-04-26T16:27:35.348112 +LR: 3.125e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 29, summary_loss: 0.19970, final_score: 0.02774, time: 657.75445 +[RESULT]: Val. Epoch: 29, summary_loss: 0.28777, final_score: 0.05245, time: 178.75266 +Fitter prepared. Device is cuda:0 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.5/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.5/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..1baf6d261190845bf18fd9a66f6159bc4f4096ba Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_0_0.5/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..9e790aaa107abf168c7b7b9d2ee2477c221866e6 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a15b578fde54ff6ddca8e68c82f0f59726e7465f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4753c067d2d7f3bc03f81cb897935374dcb9f14edbac37d298a09890f59281cc +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..5ccf54b65d4daee31fa83242acaf645d428b9747 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:58f0cb03b9a596a1f7479a6c0d8beea265742f91a31f78357fc84729e59ec322 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..0e4fa6f9a13b2239ff1303e4588915c80c356e05 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/log.txt @@ -0,0 +1,372 @@ +Fitter prepared. Device is cuda:0 + +2021-04-08T15:25:25.821945 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-08T18:19:10.735614 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-08T18:28:03.991863 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.73637, final_score: 0.49388, time: 418.87591 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69333, final_score: 0.49600, time: 114.48161 + +2021-04-08T18:36:57.763043 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69237, final_score: 0.48038, time: 423.50036 +[RESULT]: Val. Epoch: 1, summary_loss: 0.75700, final_score: 0.49650, time: 112.06245 + +2021-04-08T18:45:53.480275 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.50315, final_score: 0.23769, time: 420.57800 +[RESULT]: Val. Epoch: 2, summary_loss: 1.06121, final_score: 0.46803, time: 112.04360 + +2021-04-08T18:54:46.299194 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.41103, final_score: 0.15546, time: 420.23721 +[RESULT]: Val. Epoch: 3, summary_loss: 1.12613, final_score: 0.45355, time: 113.44286 + +2021-04-08T19:03:40.176506 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.39344, final_score: 0.14084, time: 424.15006 +[RESULT]: Val. Epoch: 4, summary_loss: 1.14484, final_score: 0.45305, time: 112.30277 + +2021-04-08T19:12:36.846610 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.42799, final_score: 0.16521, time: 430.15101 +[RESULT]: Val. Epoch: 5, summary_loss: 0.88711, final_score: 0.43307, time: 114.04028 + +2021-04-08T19:21:41.240916 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.41024, final_score: 0.15409, time: 427.46570 +[RESULT]: Val. Epoch: 6, summary_loss: 1.30806, final_score: 0.43656, time: 112.54500 + +2021-04-08T19:30:41.453606 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.45707, final_score: 0.19620, time: 430.03160 +[RESULT]: Val. Epoch: 7, summary_loss: 0.97400, final_score: 0.43457, time: 113.68637 + +2021-04-08T19:39:45.374516 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.45271, final_score: 0.19183, time: 430.91966 +[RESULT]: Val. Epoch: 8, summary_loss: 1.13867, final_score: 0.43706, time: 114.69528 + +2021-04-08T19:48:51.150836 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.49346, final_score: 0.22319, time: 438.54317 +[RESULT]: Val. Epoch: 9, summary_loss: 1.29880, final_score: 0.42258, time: 115.91124 + +2021-04-08T19:58:05.799682 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.48647, final_score: 0.22294, time: 436.55143 +[RESULT]: Val. Epoch: 10, summary_loss: 0.86388, final_score: 0.42757, time: 115.64890 + +2021-04-08T20:07:18.249894 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.53509, final_score: 0.26593, time: 439.60777 +[RESULT]: Val. Epoch: 11, summary_loss: 1.11881, final_score: 0.43806, time: 116.41200 + +2021-04-08T20:16:34.463497 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.53266, final_score: 0.26431, time: 449.14429 +[RESULT]: Val. Epoch: 12, summary_loss: 0.79112, final_score: 0.41009, time: 116.30961 + +2021-04-08T20:26:00.076245 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.56823, final_score: 0.29830, time: 452.32926 +[RESULT]: Val. Epoch: 13, summary_loss: 0.71619, final_score: 0.40460, time: 113.95180 + +2021-04-08T20:35:26.550109 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.56403, final_score: 0.29593, time: 443.89203 +[RESULT]: Val. Epoch: 14, summary_loss: 0.96033, final_score: 0.42408, time: 111.70263 + +2021-04-08T20:44:42.324748 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.60454, final_score: 0.33517, time: 448.64040 +[RESULT]: Val. Epoch: 15, summary_loss: 0.79303, final_score: 0.41708, time: 115.29968 + +2021-04-08T20:54:06.481328 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.59899, final_score: 0.33229, time: 447.09629 +[RESULT]: Val. Epoch: 16, summary_loss: 0.80359, final_score: 0.41708, time: 116.88012 + +2021-04-08T21:03:30.634904 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.63357, final_score: 0.36553, time: 444.16187 +[RESULT]: Val. Epoch: 17, summary_loss: 0.72985, final_score: 0.41109, time: 114.68325 + +2021-04-08T21:12:49.664397 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.62964, final_score: 0.36391, time: 443.97413 +[RESULT]: Val. Epoch: 18, summary_loss: 0.75446, final_score: 0.42408, time: 114.79872 + +2021-04-08T21:22:08.631264 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.64910, final_score: 0.39728, time: 449.40019 +[RESULT]: Val. Epoch: 19, summary_loss: 0.67363, final_score: 0.40310, time: 114.85733 + +2021-04-08T21:31:33.239067 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.64718, final_score: 0.38815, time: 450.34433 +[RESULT]: Val. Epoch: 20, summary_loss: 0.70942, final_score: 0.41658, time: 114.37689 + +2021-04-08T21:40:58.153836 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.65464, final_score: 0.40315, time: 449.39845 +[RESULT]: Val. Epoch: 21, summary_loss: 0.68353, final_score: 0.40210, time: 115.24847 + +2021-04-08T21:50:22.979737 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.65598, final_score: 0.40327, time: 449.37666 +[RESULT]: Val. Epoch: 22, summary_loss: 0.67881, final_score: 0.40809, time: 113.17959 + +2021-04-08T21:59:45.701033 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.65530, final_score: 0.40377, time: 450.90402 +[RESULT]: Val. Epoch: 23, summary_loss: 0.67495, final_score: 0.40709, time: 114.82843 + +2021-04-08T22:09:11.614315 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.65316, final_score: 0.40252, time: 447.13898 +[RESULT]: Val. Epoch: 24, summary_loss: 0.68771, final_score: 0.41159, time: 114.70509 + +2021-04-08T22:18:33.646547 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.65223, final_score: 0.40140, time: 452.25568 +[RESULT]: Val. Epoch: 25, summary_loss: 0.68723, final_score: 0.41409, time: 114.23343 + +2021-04-08T22:28:00.323586 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.64780, final_score: 0.39715, time: 445.51339 +[RESULT]: Val. Epoch: 26, summary_loss: 0.66029, final_score: 0.39810, time: 114.11795 + +2021-04-08T22:37:20.342280 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.64587, final_score: 0.39390, time: 447.68692 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69924, final_score: 0.40959, time: 112.77697 + +2021-04-08T22:46:40.971654 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.64168, final_score: 0.38978, time: 450.02730 +[RESULT]: Val. Epoch: 28, summary_loss: 0.67342, final_score: 0.39710, time: 114.13427 + +2021-04-08T22:56:05.342264 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.64130, final_score: 0.39090, time: 443.35036 +[RESULT]: Val. Epoch: 29, summary_loss: 0.65765, final_score: 0.39510, time: 113.81464 +Fitter prepared. Device is cuda:0 + +2021-04-12T18:00:58.460572 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69551, final_score: 0.47688, time: 456.61325 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69328, final_score: 0.48901, time: 120.16223 + +2021-04-12T18:10:35.827278 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.64196, final_score: 0.36041, time: 456.56209 +[RESULT]: Val. Epoch: 1, summary_loss: 0.78405, final_score: 0.44505, time: 122.05819 + +2021-04-12T18:20:14.643990 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.49161, final_score: 0.21332, time: 456.51360 +[RESULT]: Val. Epoch: 2, summary_loss: 1.08380, final_score: 0.43806, time: 121.56241 + +2021-04-12T18:29:53.004809 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.43554, final_score: 0.16958, time: 453.67247 +[RESULT]: Val. Epoch: 3, summary_loss: 0.83870, final_score: 0.40210, time: 119.35769 + +2021-04-12T18:39:26.238536 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.36831, final_score: 0.12659, time: 451.25833 +[RESULT]: Val. Epoch: 4, summary_loss: 2.16517, final_score: 0.43956, time: 119.99259 + +2021-04-12T18:48:57.671497 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.40226, final_score: 0.15109, time: 459.77517 +[RESULT]: Val. Epoch: 5, summary_loss: 1.59454, final_score: 0.41459, time: 119.15059 + +2021-04-12T18:58:37.002863 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.37112, final_score: 0.12659, time: 456.54841 +[RESULT]: Val. Epoch: 6, summary_loss: 1.19530, final_score: 0.38312, time: 119.45945 + +2021-04-12T19:08:13.235374 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.41865, final_score: 0.16108, time: 464.62627 +[RESULT]: Val. Epoch: 7, summary_loss: 1.20308, final_score: 0.37213, time: 119.17073 + +2021-04-12T19:17:57.282031 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.39679, final_score: 0.14709, time: 463.29160 +[RESULT]: Val. Epoch: 8, summary_loss: 0.87246, final_score: 0.37163, time: 120.05912 + +2021-04-12T19:27:40.921208 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.44326, final_score: 0.17821, time: 461.25101 +[RESULT]: Val. Epoch: 9, summary_loss: 0.91344, final_score: 0.36963, time: 118.23270 + +2021-04-12T19:37:20.740933 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.42505, final_score: 0.16721, time: 469.07313 +[RESULT]: Val. Epoch: 10, summary_loss: 1.83467, final_score: 0.40509, time: 121.53031 + +2021-04-12T19:47:11.639964 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.47209, final_score: 0.19995, time: 471.30607 +[RESULT]: Val. Epoch: 11, summary_loss: 0.81390, final_score: 0.33516, time: 119.46267 + +2021-04-12T19:57:02.608884 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.46037, final_score: 0.18858, time: 470.06095 +[RESULT]: Val. Epoch: 12, summary_loss: 0.62062, final_score: 0.31818, time: 118.12605 + +2021-04-12T20:06:51.305244 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.50848, final_score: 0.23557, time: 478.51331 +[RESULT]: Val. Epoch: 13, summary_loss: 0.60651, final_score: 0.28671, time: 119.97033 + +2021-04-12T20:16:50.231598 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.49507, final_score: 0.22507, time: 472.87883 +[RESULT]: Val. Epoch: 14, summary_loss: 0.70137, final_score: 0.28721, time: 120.64780 + +2021-04-12T20:26:43.977556 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.53100, final_score: 0.25531, time: 473.30531 +[RESULT]: Val. Epoch: 15, summary_loss: 0.88088, final_score: 0.32967, time: 118.82023 + +2021-04-12T20:36:36.355665 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.51614, final_score: 0.23619, time: 470.62622 +[RESULT]: Val. Epoch: 16, summary_loss: 0.59702, final_score: 0.26823, time: 126.12359 + +2021-04-12T20:46:33.496605 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.54515, final_score: 0.25844, time: 475.56047 +[RESULT]: Val. Epoch: 17, summary_loss: 1.19378, final_score: 0.36663, time: 122.94834 + +2021-04-12T20:56:32.218084 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.53845, final_score: 0.25506, time: 467.88993 +[RESULT]: Val. Epoch: 18, summary_loss: 0.77341, final_score: 0.31219, time: 121.46029 + +2021-04-12T21:06:21.772531 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.49522, final_score: 0.22132, time: 476.60380 +[RESULT]: Val. Epoch: 19, summary_loss: 0.56000, final_score: 0.25524, time: 125.45971 + +2021-04-12T21:16:24.236441 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.48897, final_score: 0.22119, time: 469.58388 +[RESULT]: Val. Epoch: 20, summary_loss: 0.60240, final_score: 0.22977, time: 121.38683 + +2021-04-12T21:26:15.434570 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.48529, final_score: 0.21432, time: 468.95159 +[RESULT]: Val. Epoch: 21, summary_loss: 0.60611, final_score: 0.25924, time: 122.21054 + +2021-04-12T21:36:06.825613 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.45803, final_score: 0.19345, time: 463.29829 +[RESULT]: Val. Epoch: 22, summary_loss: 0.55204, final_score: 0.22877, time: 122.96385 + +2021-04-12T21:45:53.496921 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.45225, final_score: 0.18758, time: 468.47885 +[RESULT]: Val. Epoch: 23, summary_loss: 0.77731, final_score: 0.25275, time: 125.64420 + +2021-04-12T21:55:47.830775 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.44916, final_score: 0.18758, time: 469.48221 +[RESULT]: Val. Epoch: 24, summary_loss: 0.54040, final_score: 0.21479, time: 123.58759 + +2021-04-12T22:05:41.322876 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.44261, final_score: 0.18070, time: 474.32084 +[RESULT]: Val. Epoch: 25, summary_loss: 0.77174, final_score: 0.24825, time: 121.73048 + +2021-04-12T22:15:37.570560 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.43857, final_score: 0.18208, time: 473.33846 +[RESULT]: Val. Epoch: 26, summary_loss: 0.56497, final_score: 0.21728, time: 121.53605 + +2021-04-12T22:25:32.676974 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.42691, final_score: 0.17296, time: 473.07838 +[RESULT]: Val. Epoch: 27, summary_loss: 0.54436, final_score: 0.20030, time: 115.58981 + +2021-04-12T22:35:21.788137 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.42066, final_score: 0.17083, time: 449.43934 +[RESULT]: Val. Epoch: 28, summary_loss: 0.58780, final_score: 0.20280, time: 114.94282 + +2021-04-12T22:44:46.468459 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.41225, final_score: 0.16458, time: 446.88114 +[RESULT]: Val. Epoch: 29, summary_loss: 0.55210, final_score: 0.19780, time: 114.90712 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..1e33e27a429943a6740d31c4b1cad872591d80df Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-017epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-017epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..1f62d71d6d063e50931cd597390873c6542505f1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-017epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c1fce6366da5d46fbe0b244f2e4314b62ceb0f31b7d717f78a61378d7dd4656a +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-019epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-019epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..7f1e755a648b9238865bb4f4761f3232928d53cd --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-019epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b97e32a36c7462bd45963d4c03bedeedffb5dfcaced890128eab0df7bf9862ac +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..ea794f5f264d485a65fa88f111db6ef338465dc4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:105e0b5f68739f83875b4832735de3afe4ce0ccfbd49650bb9dd7da9a4586ff8 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..d5aa224628f4db65570a6e2b7b06f659601e6ea5 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4a4441e4170603d5840bc489f6892780df1837e785195b285d18aa807744f422 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f4b81f334751f9511df0ba14453c0cd01382d8c4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-04-15T07:51:25.536806 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.68381, final_score: 0.46001, time: 417.18624 +[RESULT]: Val. Epoch: 0, summary_loss: 0.99897, final_score: 0.47652, time: 118.53487 + +2021-04-15T08:00:21.658880 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.45411, final_score: 0.18620, time: 426.04535 +[RESULT]: Val. Epoch: 1, summary_loss: 1.04369, final_score: 0.44955, time: 117.16619 + +2021-04-15T08:09:25.052965 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40604, final_score: 0.15421, time: 424.20458 +[RESULT]: Val. Epoch: 2, summary_loss: 0.94705, final_score: 0.44456, time: 117.15627 + +2021-04-15T08:18:26.788642 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.43871, final_score: 0.18333, time: 432.23802 +[RESULT]: Val. Epoch: 3, summary_loss: 1.03031, final_score: 0.45904, time: 114.53801 + +2021-04-15T08:27:33.730186 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.42621, final_score: 0.17658, time: 431.29549 +[RESULT]: Val. Epoch: 4, summary_loss: 1.24362, final_score: 0.45055, time: 115.09656 + +2021-04-15T08:36:40.295716 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.45964, final_score: 0.20470, time: 431.82737 +[RESULT]: Val. Epoch: 5, summary_loss: 0.92605, final_score: 0.43357, time: 118.41150 + +2021-04-15T08:45:50.881886 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.44286, final_score: 0.19170, time: 426.79293 +[RESULT]: Val. Epoch: 6, summary_loss: 1.15284, final_score: 0.42607, time: 113.41502 + +2021-04-15T08:54:51.267623 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.48163, final_score: 0.21245, time: 435.20564 +[RESULT]: Val. Epoch: 7, summary_loss: 1.03984, final_score: 0.39411, time: 115.91702 + +2021-04-15T09:04:02.561849 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.46031, final_score: 0.19308, time: 432.34281 +[RESULT]: Val. Epoch: 8, summary_loss: 0.78554, final_score: 0.40060, time: 114.34547 + +2021-04-15T09:13:09.671414 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.48949, final_score: 0.21807, time: 440.44556 +[RESULT]: Val. Epoch: 9, summary_loss: 0.91809, final_score: 0.40160, time: 114.24620 + +2021-04-15T09:22:24.541985 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.47688, final_score: 0.20820, time: 436.08639 +[RESULT]: Val. Epoch: 10, summary_loss: 1.04176, final_score: 0.40110, time: 113.90484 + +2021-04-15T09:31:34.706842 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.51041, final_score: 0.23144, time: 441.33294 +[RESULT]: Val. Epoch: 11, summary_loss: 0.82565, final_score: 0.36863, time: 114.97367 + +2021-04-15T09:40:51.189478 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.50171, final_score: 0.21707, time: 438.48996 +[RESULT]: Val. Epoch: 12, summary_loss: 0.90418, final_score: 0.37313, time: 113.72656 + +2021-04-15T09:50:03.579920 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.54714, final_score: 0.25581, time: 446.74121 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69735, final_score: 0.34665, time: 113.06368 + +2021-04-15T09:59:23.730927 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.54419, final_score: 0.25819, time: 439.13356 +[RESULT]: Val. Epoch: 14, summary_loss: 0.84919, final_score: 0.37063, time: 113.50483 + +2021-04-15T10:08:36.536722 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.58565, final_score: 0.29855, time: 443.72852 +[RESULT]: Val. Epoch: 15, summary_loss: 0.63800, final_score: 0.33766, time: 113.15895 + +2021-04-15T10:17:53.773227 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.57894, final_score: 0.29393, time: 437.51857 +[RESULT]: Val. Epoch: 16, summary_loss: 0.70765, final_score: 0.35015, time: 116.13230 + +2021-04-15T10:27:07.588648 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.60700, final_score: 0.31930, time: 445.28824 +[RESULT]: Val. Epoch: 17, summary_loss: 0.62143, final_score: 0.32118, time: 114.07289 + +2021-04-15T10:36:27.297567 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.59536, final_score: 0.30717, time: 430.60745 +[RESULT]: Val. Epoch: 18, summary_loss: 0.63833, final_score: 0.33417, time: 113.66371 + +2021-04-15T10:45:31.730703 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.59359, final_score: 0.30817, time: 442.34186 +[RESULT]: Val. Epoch: 19, summary_loss: 0.60874, final_score: 0.32168, time: 119.08967 + +2021-04-15T10:54:53.539608 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.59045, final_score: 0.30480, time: 441.60999 +[RESULT]: Val. Epoch: 20, summary_loss: 0.62518, final_score: 0.32667, time: 118.18312 + +2021-04-15T11:04:13.494220 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.59114, final_score: 0.30017, time: 441.20304 +[RESULT]: Val. Epoch: 21, summary_loss: 0.62674, final_score: 0.31319, time: 117.55641 + +2021-04-15T11:13:32.423264 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.56975, final_score: 0.29030, time: 445.95249 +[RESULT]: Val. Epoch: 22, summary_loss: 0.68857, final_score: 0.32068, time: 114.77930 + +2021-04-15T11:22:53.316545 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.56662, final_score: 0.28193, time: 437.15040 +[RESULT]: Val. Epoch: 23, summary_loss: 0.62555, final_score: 0.30270, time: 113.69356 + +2021-04-15T11:32:04.332473 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.55038, final_score: 0.27118, time: 438.07794 +[RESULT]: Val. Epoch: 24, summary_loss: 0.59027, final_score: 0.29570, time: 114.73303 + +2021-04-15T11:41:17.479710 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.53953, final_score: 0.25769, time: 437.66602 +[RESULT]: Val. Epoch: 25, summary_loss: 0.65553, final_score: 0.28871, time: 119.44697 + +2021-04-15T11:50:34.775354 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.54671, final_score: 0.26956, time: 440.53963 +[RESULT]: Val. Epoch: 26, summary_loss: 0.66141, final_score: 0.30619, time: 113.93504 + +2021-04-15T11:59:49.449887 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.53187, final_score: 0.25319, time: 439.53530 +[RESULT]: Val. Epoch: 27, summary_loss: 0.62442, final_score: 0.28921, time: 113.88042 + +2021-04-15T12:09:03.023219 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.52874, final_score: 0.25319, time: 442.33549 +[RESULT]: Val. Epoch: 28, summary_loss: 0.63587, final_score: 0.29121, time: 114.32046 + +2021-04-15T12:18:19.877655 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.51994, final_score: 0.25056, time: 442.08568 +[RESULT]: Val. Epoch: 29, summary_loss: 0.62328, final_score: 0.29271, time: 114.47361 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..4f4fb802d65a8b398338377a3f6be3b85ecd1db6 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_2/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..d0d1a7046835ee6e901f95e7bca3e2b73cdbe626 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:63d8a96439926bc0fff3beb0e0e68f117d5eefa4028424650402a4e428bc7ce9 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..cdf0026e0d6b83fe3e91691a1ff65312aa7deb60 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bad2d805de7f418f4d0da5b50bc4471f932a907c348b60d7f9d8680d3a474ea8 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..288d8888da339727b5444ba3f45212ac5fa5e3b5 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6d6607e2693f2f1a9e48195dd02886bea60061bfb95208abea7dcd5c23b0c74d +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..ea5325ec09a503143de42a87c31388410f45cf38 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bf6dfdbb1a02b87d2ddd1abb2243a66fc769adbe56ad81bcbd6f19abfe8ad35e +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..355a734b25b97abdc9011f64e3e7742e439e3cac --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/log.txt @@ -0,0 +1,234 @@ +Fitter prepared. Device is cuda:0 + +2021-04-19T06:46:53.680322 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.65214, final_score: 0.41415, time: 669.89903 +[RESULT]: Val. Epoch: 0, summary_loss: 0.75791, final_score: 0.44855, time: 190.05520 + +2021-04-19T07:01:13.990522 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.44637, final_score: 0.17883, time: 672.46017 +[RESULT]: Val. Epoch: 1, summary_loss: 0.79984, final_score: 0.43407, time: 187.69035 + +2021-04-19T07:15:34.366749 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40469, final_score: 0.15859, time: 675.15325 +[RESULT]: Val. Epoch: 2, summary_loss: 0.97278, final_score: 0.43856, time: 185.46024 + +2021-04-19T07:29:55.160593 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.44490, final_score: 0.18820, time: 670.88680 +[RESULT]: Val. Epoch: 3, summary_loss: 0.99078, final_score: 0.44605, time: 184.85304 + +2021-04-19T07:44:11.066407 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.42215, final_score: 0.17133, time: 679.21078 +[RESULT]: Val. Epoch: 4, summary_loss: 1.61688, final_score: 0.47403, time: 187.00031 + +2021-04-19T07:58:37.456468 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.46027, final_score: 0.20395, time: 665.43423 +[RESULT]: Val. Epoch: 5, summary_loss: 1.20755, final_score: 0.45704, time: 189.13224 + +2021-04-19T08:12:52.205858 +LR: 0.001 +Emb_rate: 0.7290000000000001 +Fitter prepared. Device is cuda:0 + +2021-04-19T18:51:10.624848 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69458, final_score: 0.47663, time: 685.19793 +[RESULT]: Val. Epoch: 0, summary_loss: 0.78449, final_score: 0.49650, time: 193.55499 + +2021-04-19T19:05:49.847100 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.66158, final_score: 0.38740, time: 696.31820 +[RESULT]: Val. Epoch: 1, summary_loss: 0.92474, final_score: 0.48152, time: 208.44739 + +2021-04-19T19:20:54.828997 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.57058, final_score: 0.27956, time: 687.57345 +[RESULT]: Val. Epoch: 2, summary_loss: 0.93435, final_score: 0.44755, time: 187.30023 + +2021-04-19T19:35:29.886374 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.55152, final_score: 0.26206, time: 683.72736 +[RESULT]: Val. Epoch: 3, summary_loss: 0.85363, final_score: 0.43457, time: 183.87658 + +2021-04-19T19:49:57.687831 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.50946, final_score: 0.22782, time: 695.87743 +[RESULT]: Val. Epoch: 4, summary_loss: 0.97209, final_score: 0.42158, time: 184.91200 + +2021-04-19T20:04:38.785785 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.54168, final_score: 0.25319, time: 686.64689 +[RESULT]: Val. Epoch: 5, summary_loss: 0.86880, final_score: 0.45455, time: 188.44301 + +2021-04-19T20:19:14.044837 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.51427, final_score: 0.22857, time: 785.61958 +[RESULT]: Val. Epoch: 6, summary_loss: 0.75217, final_score: 0.42158, time: 183.64870 + +2021-04-19T20:35:23.745648 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.53929, final_score: 0.25569, time: 691.98202 +[RESULT]: Val. Epoch: 7, summary_loss: 1.88390, final_score: 0.46404, time: 184.07193 + +2021-04-19T20:49:59.970825 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.53041, final_score: 0.24769, time: 681.94153 +[RESULT]: Val. Epoch: 8, summary_loss: 0.84018, final_score: 0.40709, time: 185.90111 + +2021-04-19T21:04:27.994920 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55354, final_score: 0.27556, time: 700.52923 +[RESULT]: Val. Epoch: 9, summary_loss: 1.25691, final_score: 0.42657, time: 183.01394 + +2021-04-19T21:19:11.763663 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.54424, final_score: 0.26406, time: 699.59120 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69813, final_score: 0.39810, time: 182.34079 + +2021-04-19T21:33:54.044899 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.56459, final_score: 0.28718, time: 776.20207 +[RESULT]: Val. Epoch: 11, summary_loss: 0.92731, final_score: 0.41708, time: 198.18874 + +2021-04-19T21:50:08.618575 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.55620, final_score: 0.27343, time: 829.40013 +[RESULT]: Val. Epoch: 12, summary_loss: 1.67628, final_score: 0.43257, time: 189.76756 + +2021-04-19T22:07:07.942924 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.58472, final_score: 0.30530, time: 833.17618 +[RESULT]: Val. Epoch: 13, summary_loss: 0.72252, final_score: 0.37013, time: 208.51788 + +2021-04-19T22:24:29.803729 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.57807, final_score: 0.29793, time: 756.53598 +[RESULT]: Val. Epoch: 14, summary_loss: 0.84848, final_score: 0.38511, time: 203.44472 + +2021-04-19T22:40:29.959778 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.60268, final_score: 0.32667, time: 912.35914 +[RESULT]: Val. Epoch: 15, summary_loss: 0.65031, final_score: 0.36114, time: 197.44858 + +2021-04-19T22:59:00.115929 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.59187, final_score: 0.31405, time: 696.14183 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69004, final_score: 0.34515, time: 191.63213 + +2021-04-19T23:13:48.073520 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.61267, final_score: 0.33729, time: 754.37306 +[RESULT]: Val. Epoch: 17, summary_loss: 0.90292, final_score: 0.39061, time: 207.37195 + +2021-04-19T23:29:49.985423 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.60834, final_score: 0.33679, time: 772.87558 +[RESULT]: Val. Epoch: 18, summary_loss: 0.73761, final_score: 0.33666, time: 183.64431 + +2021-04-19T23:45:46.703279 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.58262, final_score: 0.30842, time: 760.83454 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69740, final_score: 0.33666, time: 178.53729 + +2021-04-20T00:01:26.288429 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.57692, final_score: 0.30430, time: 762.15499 +[RESULT]: Val. Epoch: 20, summary_loss: 0.61747, final_score: 0.31469, time: 179.34718 + +2021-04-20T00:17:08.192793 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.57396, final_score: 0.29643, time: 800.87536 +[RESULT]: Val. Epoch: 21, summary_loss: 0.59079, final_score: 0.30819, time: 220.06163 + +2021-04-20T00:34:09.463458 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.56047, final_score: 0.28980, time: 900.01891 +[RESULT]: Val. Epoch: 22, summary_loss: 0.58529, final_score: 0.28372, time: 180.62319 + +2021-04-20T00:52:10.455066 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.55635, final_score: 0.28130, time: 813.21702 +[RESULT]: Val. Epoch: 23, summary_loss: 0.57493, final_score: 0.29520, time: 187.95324 + +2021-04-20T01:08:52.024448 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.53794, final_score: 0.25894, time: 781.64614 +[RESULT]: Val. Epoch: 24, summary_loss: 0.57102, final_score: 0.27073, time: 233.23719 + +2021-04-20T01:25:47.292892 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.52039, final_score: 0.24406, time: 773.18709 +[RESULT]: Val. Epoch: 25, summary_loss: 0.89062, final_score: 0.30519, time: 196.25798 + +2021-04-20T01:41:56.934342 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.50513, final_score: 0.22844, time: 890.68627 +[RESULT]: Val. Epoch: 26, summary_loss: 0.67403, final_score: 0.26623, time: 191.67633 + +2021-04-20T01:59:59.504014 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.48152, final_score: 0.21170, time: 802.07873 +[RESULT]: Val. Epoch: 27, summary_loss: 0.53617, final_score: 0.24226, time: 217.32167 + +2021-04-20T02:16:59.257136 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.46260, final_score: 0.20095, time: 874.77895 +[RESULT]: Val. Epoch: 28, summary_loss: 0.57650, final_score: 0.24026, time: 187.18829 + +2021-04-20T02:34:41.474583 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.46000, final_score: 0.19658, time: 737.15089 +[RESULT]: Val. Epoch: 29, summary_loss: 0.50614, final_score: 0.21479, time: 235.40755 +Fitter prepared. Device is cuda:0 + +2021-04-28T09:33:47.118204 +LR: 0.00025 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.50791, final_score: 0.23057, time: 715.07439 +[RESULT]: Val. Epoch: 30, summary_loss: 0.65981, final_score: 0.26823, time: 185.24147 + +2021-04-28T09:48:47.605535 +LR: 0.00025 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 31, summary_loss: 0.48202, final_score: 0.21107, time: 707.70052 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..e79fe0b7e2b29dc0f71a4d37e6a58ee85a373f2c Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..00dd95b8446eeb98e925fe67d61384bf83cafb6e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ef3be19d19bfe863999ef617a3be7064c80a1e835dfccc80ed95403af04572da +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f0f93fbabc9dac706483e480a0635f0492129395 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ea38d0012ff1516d37af2f65c71ed153f6827d7f15645bee267ffad7475c1007 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-030epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-030epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c83d9e35f189b674b66c036a9ac0a3b3dcf6d8f7 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/best-checkpoint-030epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:51f6209069b86650191cf4dfe4274d79fda1419135169e69b97ce165300bab86 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..a1a0422ff91717ec0c38985ec9fe6997e05bd4b6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:11dc222cc9303c32cfb376a700d2d261a9b08ca5c7f80e5bfdadb5e519d8f8dc +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f4396c391e0a0dc94f04107b0059eee346c78cf1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/log.txt @@ -0,0 +1,242 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:51:46.861209 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.68571, final_score: 0.46388, time: 715.50076 +[RESULT]: Val. Epoch: 0, summary_loss: 4.81629, final_score: 0.49800, time: 198.72982 + +2021-04-26T10:07:01.457558 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.51361, final_score: 0.23807, time: 731.11444 +[RESULT]: Val. Epoch: 1, summary_loss: 1.16492, final_score: 0.49351, time: 211.94761 + +2021-04-26T10:22:44.843556 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40370, final_score: 0.15121, time: 725.08104 +[RESULT]: Val. Epoch: 2, summary_loss: 0.87547, final_score: 0.49550, time: 209.38826 + +2021-04-26T10:38:19.630028 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.44002, final_score: 0.18170, time: 723.68304 +[RESULT]: Val. Epoch: 3, summary_loss: 0.81510, final_score: 0.49800, time: 193.34700 + +2021-04-26T10:53:36.978107 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.42229, final_score: 0.17371, time: 723.70827 +[RESULT]: Val. Epoch: 4, summary_loss: 2.10697, final_score: 0.49850, time: 220.41211 + +2021-04-26T11:09:21.256520 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.46392, final_score: 0.20957, time: 743.29855 +[RESULT]: Val. Epoch: 5, summary_loss: 0.87013, final_score: 0.49900, time: 195.04204 + +2021-04-26T11:24:59.763359 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.45236, final_score: 0.20470, time: 729.31862 +[RESULT]: Val. Epoch: 6, summary_loss: 1.57393, final_score: 0.49800, time: 210.52103 + +2021-04-26T11:40:39.763882 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.50956, final_score: 0.24631, time: 740.60907 +[RESULT]: Val. Epoch: 7, summary_loss: 1.01434, final_score: 0.49950, time: 206.28624 + +2021-04-26T11:56:26.838521 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.50514, final_score: 0.24469, time: 756.32901 +[RESULT]: Val. Epoch: 8, summary_loss: 0.82847, final_score: 0.49900, time: 198.66301 + +2021-04-26T12:12:21.993147 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55515, final_score: 0.28618, time: 728.83688 +[RESULT]: Val. Epoch: 9, summary_loss: 0.90585, final_score: 0.49850, time: 198.26447 + +2021-04-26T12:27:49.247018 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.54951, final_score: 0.28118, time: 730.39389 +[RESULT]: Val. Epoch: 10, summary_loss: 1.04572, final_score: 0.49850, time: 193.99017 + +2021-04-26T12:43:13.797183 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.59706, final_score: 0.33104, time: 745.99724 +[RESULT]: Val. Epoch: 11, summary_loss: 0.79906, final_score: 0.49900, time: 193.52890 + +2021-04-26T12:58:53.668929 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.59253, final_score: 0.32467, time: 694.65885 +[RESULT]: Val. Epoch: 12, summary_loss: 0.83168, final_score: 0.49950, time: 211.01090 + +2021-04-26T13:13:59.571780 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.62725, final_score: 0.36628, time: 750.74383 +[RESULT]: Val. Epoch: 13, summary_loss: 1.03735, final_score: 0.49900, time: 206.19511 + +2021-04-26T13:29:56.669097 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.62336, final_score: 0.35754, time: 754.13248 +[RESULT]: Val. Epoch: 14, summary_loss: 0.74969, final_score: 0.49850, time: 199.91649 + +2021-04-26T13:45:51.067394 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64801, final_score: 0.38840, time: 749.21122 +[RESULT]: Val. Epoch: 15, summary_loss: 0.76669, final_score: 0.49700, time: 220.40873 + +2021-04-26T14:02:00.866479 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64603, final_score: 0.38778, time: 728.27010 +[RESULT]: Val. Epoch: 16, summary_loss: 0.74733, final_score: 0.49700, time: 198.00750 + +2021-04-26T14:17:27.475248 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 17, summary_loss: 0.66511, final_score: 0.41490, time: 738.34497 +[RESULT]: Val. Epoch: 17, summary_loss: 0.74906, final_score: 0.49251, time: 196.57494 + +2021-04-26T14:33:02.600867 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.66237, final_score: 0.41165, time: 742.75023 +[RESULT]: Val. Epoch: 18, summary_loss: 0.73852, final_score: 0.48402, time: 223.63089 + +2021-04-26T14:49:09.334887 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.65810, final_score: 0.39240, time: 757.93194 +[RESULT]: Val. Epoch: 19, summary_loss: 1.02238, final_score: 0.39560, time: 209.65613 + +2021-04-26T15:05:17.141545 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.57356, final_score: 0.28230, time: 754.07631 +[RESULT]: Val. Epoch: 20, summary_loss: 1.12080, final_score: 0.33766, time: 212.86251 + +2021-04-26T15:21:24.249269 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 21, summary_loss: 0.49354, final_score: 0.21232, time: 745.10022 +[RESULT]: Val. Epoch: 21, summary_loss: 0.57805, final_score: 0.21628, time: 197.85875 + +2021-04-26T15:37:07.591816 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.45601, final_score: 0.18695, time: 743.72930 +[RESULT]: Val. Epoch: 22, summary_loss: 0.47711, final_score: 0.18581, time: 216.62135 + +2021-04-26T15:53:08.814963 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.43175, final_score: 0.16708, time: 760.02756 +[RESULT]: Val. Epoch: 23, summary_loss: 0.68999, final_score: 0.22827, time: 196.67368 + +2021-04-26T16:09:05.703550 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.40756, final_score: 0.15621, time: 743.39833 +[RESULT]: Val. Epoch: 24, summary_loss: 0.67484, final_score: 0.19231, time: 214.38909 + +2021-04-26T16:25:03.710001 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 25, summary_loss: 0.39697, final_score: 0.14521, time: 749.91101 +[RESULT]: Val. Epoch: 25, summary_loss: 0.86163, final_score: 0.24975, time: 216.61226 + +2021-04-26T16:41:10.524701 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.39045, final_score: 0.14346, time: 758.65091 +[RESULT]: Val. Epoch: 26, summary_loss: 0.46745, final_score: 0.16883, time: 208.68954 + +2021-04-26T16:57:18.230741 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 27, summary_loss: 0.37035, final_score: 0.13309, time: 753.37396 +[RESULT]: Val. Epoch: 27, summary_loss: 0.52648, final_score: 0.17083, time: 220.84204 + +2021-04-26T17:13:32.602232 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.36284, final_score: 0.12222, time: 758.32697 +[RESULT]: Val. Epoch: 28, summary_loss: 0.75886, final_score: 0.19880, time: 203.47092 + +2021-04-26T17:29:34.672433 +LR: 0.001 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 29, summary_loss: 0.35712, final_score: 0.12309, time: 724.82255 +[RESULT]: Val. Epoch: 29, summary_loss: 0.40834, final_score: 0.14236, time: 201.82272 +Fitter prepared. Device is cuda:0 + +2021-04-28T10:05:55.008212 +LR: 0.001 +Emb_rate: 0.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.35002, final_score: 0.11372, time: 684.77689 +[RESULT]: Val. Epoch: 30, summary_loss: 0.41806, final_score: 0.14486, time: 187.15895 + +2021-04-28T10:20:27.344127 +LR: 0.001 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 31, summary_loss: 0.35147, final_score: 0.11485, time: 731.53570 +[RESULT]: Val. Epoch: 31, summary_loss: 0.43426, final_score: 0.15485, time: 207.59508 + +2021-04-28T10:36:07.169758 +LR: 0.001 +Emb_rate: 0.18000000000000002 +[RESULT]: Train. Epoch: 32, summary_loss: 0.34441, final_score: 0.11335, time: 778.53532 +[RESULT]: Val. Epoch: 32, summary_loss: 0.43180, final_score: 0.15584, time: 209.99369 + +2021-04-28T10:52:35.893256 +LR: 0.001 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 33, summary_loss: 0.34483, final_score: 0.11235, time: 723.33780 +[RESULT]: Val. Epoch: 33, summary_loss: 0.82601, final_score: 0.19031, time: 181.76947 + +2021-04-28T11:07:41.194032 +LR: 0.001 +Emb_rate: 0.16200000000000003 +[RESULT]: Train. Epoch: 34, summary_loss: 0.34246, final_score: 0.10922, time: 698.58306 +[RESULT]: Val. Epoch: 34, summary_loss: 0.46994, final_score: 0.14685, time: 184.63130 + +2021-04-28T11:22:24.571743 +LR: 0.001 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 35, summary_loss: 0.34139, final_score: 0.11247, time: 700.20053 +[RESULT]: Val. Epoch: 35, summary_loss: 0.48610, final_score: 0.15085, time: 184.72035 + +2021-04-28T11:37:09.681140 +LR: 0.001 +Emb_rate: 0.14580000000000004 +[RESULT]: Train. Epoch: 36, summary_loss: 0.33517, final_score: 0.10647, time: 705.03761 +[RESULT]: Val. Epoch: 36, summary_loss: 0.43075, final_score: 0.14136, time: 184.07294 + +2021-04-28T11:51:58.944545 +LR: 0.001 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 37, summary_loss: 0.35062, final_score: 0.11572, time: 699.01917 +[RESULT]: Val. Epoch: 37, summary_loss: 0.43294, final_score: 0.14286, time: 187.38595 + +2021-04-28T12:06:45.530673 +LR: 0.001 +Emb_rate: 0.13122000000000003 +[RESULT]: Train. Epoch: 38, summary_loss: 0.33395, final_score: 0.10660, time: 703.15751 +[RESULT]: Val. Epoch: 38, summary_loss: 0.46073, final_score: 0.14885, time: 185.09640 + +2021-04-28T12:21:33.949892 +LR: 0.001 +Emb_rate: 0.11809800000000004 +[RESULT]: Train. Epoch: 39, summary_loss: 0.34286, final_score: 0.10960, time: 702.74255 +[RESULT]: Val. Epoch: 39, summary_loss: 0.93595, final_score: 0.20979, time: 181.22160 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..8bf30fe67a263febbcee5589c79840c19476af71 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c66ff20830b100f498c07f8b934a3f9bd17ce622 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:63f23082568d90007e29f7c104d2f16e021fb5eec61216b38b9c9a9a635621df +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a67c0c0d75401e2ce20585134fa8a7b67f35e3e1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:226ca9fcf83c934c93b0f2b2786c72966489c038832218882bddae4b19f7b95c +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-028epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-028epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..78a7168a45ccf34d816fe12c9e6af5dd764c2931 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/best-checkpoint-028epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ca4f004f65695bf0f0532ca1fcda26f1929b7f0fd5a1a23bf3a5ad9e9a5039c4 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..3b085f5f89cddd75235da667b427e717f12b7328 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cd603a3a6ce2d12fa937bdda0a1e8342a4eefb5060ee506e2b9951ad8dee1a0a +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..b92bfc8dd2f50ac05a4217850bb092526693b53a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_3_0.2/log.txt @@ -0,0 +1,187 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:29:32.082621 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-26T09:44:30.085178 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.53893, final_score: 0.28993, time: 685.94658 +[RESULT]: Val. Epoch: 0, summary_loss: 1.12533, final_score: 0.49500, time: 201.55580 + +2021-04-26T09:59:17.989803 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.41864, final_score: 0.16558, time: 717.59861 +[RESULT]: Val. Epoch: 1, summary_loss: 1.36204, final_score: 0.49251, time: 195.70018 + +2021-04-26T10:14:31.521235 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.38873, final_score: 0.14546, time: 711.11408 +[RESULT]: Val. Epoch: 2, summary_loss: 1.94617, final_score: 0.49451, time: 196.98797 + +2021-04-26T10:29:39.792892 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.41611, final_score: 0.16883, time: 724.77815 +[RESULT]: Val. Epoch: 3, summary_loss: 1.36275, final_score: 0.49550, time: 196.75172 + +2021-04-26T10:45:01.536935 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.40364, final_score: 0.16333, time: 716.55686 +[RESULT]: Val. Epoch: 4, summary_loss: 0.93112, final_score: 0.48951, time: 191.32007 + +2021-04-26T11:00:09.903808 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.46097, final_score: 0.20570, time: 717.12787 +[RESULT]: Val. Epoch: 5, summary_loss: 1.51040, final_score: 0.49401, time: 194.57210 + +2021-04-26T11:15:21.784707 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.45597, final_score: 0.20220, time: 719.27898 +[RESULT]: Val. Epoch: 6, summary_loss: 1.08604, final_score: 0.49600, time: 196.92647 + +2021-04-26T11:30:38.210694 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.50246, final_score: 0.24556, time: 719.77882 +[RESULT]: Val. Epoch: 7, summary_loss: 0.83537, final_score: 0.49351, time: 191.72809 + +2021-04-26T11:45:50.130916 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.50136, final_score: 0.24231, time: 729.66930 +[RESULT]: Val. Epoch: 8, summary_loss: 0.88861, final_score: 0.48901, time: 200.03184 + +2021-04-26T12:01:20.066503 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55209, final_score: 0.28455, time: 728.83554 +[RESULT]: Val. Epoch: 9, summary_loss: 0.86416, final_score: 0.49351, time: 196.23199 + +2021-04-26T12:16:45.317348 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.54903, final_score: 0.28393, time: 717.95837 +[RESULT]: Val. Epoch: 10, summary_loss: 0.79065, final_score: 0.49151, time: 195.70261 + +2021-04-26T12:31:59.484530 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.59584, final_score: 0.32429, time: 726.01984 +[RESULT]: Val. Epoch: 11, summary_loss: 0.99006, final_score: 0.49351, time: 188.95083 + +2021-04-26T12:47:14.676512 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.59161, final_score: 0.32429, time: 729.57562 +[RESULT]: Val. Epoch: 12, summary_loss: 0.84309, final_score: 0.49301, time: 188.45257 + +2021-04-26T13:02:32.929790 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.62419, final_score: 0.35804, time: 707.98091 +[RESULT]: Val. Epoch: 13, summary_loss: 0.81425, final_score: 0.48951, time: 197.00886 + +2021-04-26T13:17:38.133274 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.61885, final_score: 0.35654, time: 726.90623 +[RESULT]: Val. Epoch: 14, summary_loss: 0.75985, final_score: 0.48851, time: 196.62779 + +2021-04-26T13:33:02.100285 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64541, final_score: 0.38853, time: 724.53758 +[RESULT]: Val. Epoch: 15, summary_loss: 0.78547, final_score: 0.49151, time: 194.61764 + +2021-04-26T13:48:21.485806 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64069, final_score: 0.37928, time: 736.75413 +[RESULT]: Val. Epoch: 16, summary_loss: 0.76684, final_score: 0.48501, time: 192.19285 + +2021-04-26T14:03:50.719239 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 17, summary_loss: 0.66112, final_score: 0.41140, time: 737.57226 +[RESULT]: Val. Epoch: 17, summary_loss: 0.75297, final_score: 0.48501, time: 195.43841 + +2021-04-26T14:19:24.201732 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.65399, final_score: 0.39653, time: 736.82337 +[RESULT]: Val. Epoch: 18, summary_loss: 0.75455, final_score: 0.42557, time: 190.25748 + +2021-04-26T14:34:51.513630 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.59476, final_score: 0.30592, time: 734.39099 +[RESULT]: Val. Epoch: 19, summary_loss: 0.57209, final_score: 0.25075, time: 194.28352 + +2021-04-26T14:50:20.636572 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.50442, final_score: 0.22607, time: 730.38570 +[RESULT]: Val. Epoch: 20, summary_loss: 0.92610, final_score: 0.28222, time: 202.26039 + +2021-04-26T15:05:53.505518 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 21, summary_loss: 0.45707, final_score: 0.19070, time: 724.89712 +[RESULT]: Val. Epoch: 21, summary_loss: 0.52794, final_score: 0.20380, time: 198.93634 + +2021-04-26T15:21:17.738966 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.43552, final_score: 0.16958, time: 746.33844 +[RESULT]: Val. Epoch: 22, summary_loss: 0.58113, final_score: 0.19431, time: 199.12974 + +2021-04-26T15:37:03.443159 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 23, summary_loss: 0.40867, final_score: 0.15309, time: 731.04966 +[RESULT]: Val. Epoch: 23, summary_loss: 0.56203, final_score: 0.15435, time: 195.38820 + +2021-04-26T15:52:30.104821 +LR: 0.001 +Emb_rate: 0.28242953648100017 +[RESULT]: Train. Epoch: 24, summary_loss: 0.39843, final_score: 0.14634, time: 729.23097 +[RESULT]: Val. Epoch: 24, summary_loss: 0.65054, final_score: 0.17682, time: 195.70710 + +2021-04-26T16:07:55.277669 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 25, summary_loss: 0.38886, final_score: 0.14234, time: 748.25412 +[RESULT]: Val. Epoch: 25, summary_loss: 0.45011, final_score: 0.15035, time: 187.60316 + +2021-04-26T16:23:31.614124 +LR: 0.001 +Emb_rate: 0.25418658283290013 +[RESULT]: Train. Epoch: 26, summary_loss: 0.37756, final_score: 0.13522, time: 733.25089 +[RESULT]: Val. Epoch: 26, summary_loss: 0.42498, final_score: 0.13287, time: 184.63980 + +2021-04-26T16:38:49.915258 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 27, summary_loss: 0.36846, final_score: 0.12522, time: 736.74521 +[RESULT]: Val. Epoch: 27, summary_loss: 0.42629, final_score: 0.14985, time: 200.14931 + +2021-04-26T16:54:27.045528 +LR: 0.001 +Emb_rate: 0.22876792454961012 +[RESULT]: Train. Epoch: 28, summary_loss: 0.36100, final_score: 0.12322, time: 742.22306 +[RESULT]: Val. Epoch: 28, summary_loss: 0.41157, final_score: 0.13237, time: 195.12463 + +2021-04-26T17:10:04.760076 +LR: 0.001 +Emb_rate: 0.2058911320946491 +[RESULT]: Train. Epoch: 29, summary_loss: 0.35600, final_score: 0.12134, time: 719.77923 +[RESULT]: Val. Epoch: 29, summary_loss: 0.46212, final_score: 0.14386, time: 185.67349 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:28:49.583684 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-26T09:35:23.187357 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.63460, final_score: 0.39815, time: 691.76472 +[RESULT]: Val. Epoch: 0, summary_loss: 1.19085, final_score: 0.47652, time: 184.50017 + +2021-04-26T09:49:59.854817 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.42920, final_score: 0.16721, time: 725.31181 +[RESULT]: Val. Epoch: 1, summary_loss: 1.00425, final_score: 0.47003, time: 214.85215 + +2021-04-26T10:05:40.405825 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.39862, final_score: 0.15171, time: 694.65093 +[RESULT]: Val. Epoch: 2, summary_loss: 1.42040, final_score: 0.48751, time: 218.79357 + +2021-04-26T10:20:54.054864 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.42348, final_score: 0.17233, time: 697.70667 +[RESULT]: Val. Epoch: 3, summary_loss: 2.42396, final_score: 0.49051, time: 189.20342 + +2021-04-26T10:35:41.164897 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.41556, final_score: 0.17146, time: 738.96724 +[RESULT]: Val. Epoch: 4, summary_loss: 1.08787, final_score: 0.46903, time: 196.44475 + +2021-04-26T10:51:16.795263 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.46461, final_score: 0.20582, time: 733.67837 +[RESULT]: Val. Epoch: 5, summary_loss: 1.11974, final_score: 0.47453, time: 189.63662 + +2021-04-26T11:06:40.334116 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.45265, final_score: 0.20032, time: 721.49953 +[RESULT]: Val. Epoch: 6, summary_loss: 1.48312, final_score: 0.48751, time: 211.78160 + +2021-04-26T11:22:13.833431 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.51474, final_score: 0.24481, time: 740.32091 +[RESULT]: Val. Epoch: 7, summary_loss: 1.22615, final_score: 0.48252, time: 218.14056 + +2021-04-26T11:38:12.486771 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.50092, final_score: 0.24394, time: 713.79634 +[RESULT]: Val. Epoch: 8, summary_loss: 0.96292, final_score: 0.46703, time: 211.50906 + +2021-04-26T11:53:38.126687 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55510, final_score: 0.28668, time: 755.50121 +[RESULT]: Val. Epoch: 9, summary_loss: 0.75476, final_score: 0.46503, time: 205.60422 + +2021-04-26T12:09:39.587404 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.55140, final_score: 0.28430, time: 712.24113 +[RESULT]: Val. Epoch: 10, summary_loss: 0.85827, final_score: 0.47103, time: 185.42057 + +2021-04-26T12:24:37.412312 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.59210, final_score: 0.32492, time: 699.32449 +[RESULT]: Val. Epoch: 11, summary_loss: 0.83255, final_score: 0.47453, time: 200.57896 + +2021-04-26T12:39:37.477903 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.59404, final_score: 0.32642, time: 764.82937 +[RESULT]: Val. Epoch: 12, summary_loss: 0.82206, final_score: 0.47552, time: 184.42137 + +2021-04-26T12:55:26.931688 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.62344, final_score: 0.35916, time: 710.97892 +[RESULT]: Val. Epoch: 13, summary_loss: 0.91938, final_score: 0.47552, time: 213.65227 + +2021-04-26T13:10:51.742049 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.62282, final_score: 0.35529, time: 740.38624 +[RESULT]: Val. Epoch: 14, summary_loss: 0.73880, final_score: 0.46404, time: 185.90483 + +2021-04-26T13:26:18.351632 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64569, final_score: 0.38315, time: 755.25783 +[RESULT]: Val. Epoch: 15, summary_loss: 0.70928, final_score: 0.46454, time: 198.60708 + +2021-04-26T13:42:12.647005 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64091, final_score: 0.37966, time: 745.84879 +[RESULT]: Val. Epoch: 16, summary_loss: 0.72206, final_score: 0.45305, time: 215.85961 + +2021-04-26T13:58:14.519434 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 17, summary_loss: 0.66041, final_score: 0.41152, time: 765.55841 +[RESULT]: Val. Epoch: 17, summary_loss: 0.72392, final_score: 0.46503, time: 184.10414 + +2021-04-26T14:14:04.389843 +LR: 0.001 +Emb_rate: 0.38742048900000015 +[RESULT]: Train. Epoch: 18, summary_loss: 0.66283, final_score: 0.41202, time: 742.70467 +[RESULT]: Val. Epoch: 18, summary_loss: 0.73590, final_score: 0.46454, time: 188.90805 + +2021-04-26T14:29:36.213319 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 19, summary_loss: 0.67496, final_score: 0.43702, time: 752.95845 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69190, final_score: 0.45405, time: 211.64558 + +2021-04-26T14:45:41.232873 +LR: 0.001 +Emb_rate: 0.34867844010000015 +[RESULT]: Train. Epoch: 20, summary_loss: 0.67090, final_score: 0.42764, time: 775.06090 +[RESULT]: Val. Epoch: 20, summary_loss: 0.73617, final_score: 0.45654, time: 196.14247 + +2021-04-26T15:01:52.625287 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 21, summary_loss: 0.67844, final_score: 0.43689, time: 726.19821 +[RESULT]: Val. Epoch: 21, summary_loss: 0.71709, final_score: 0.43157, time: 202.94966 + +2021-04-26T15:17:21.982596 +LR: 0.001 +Emb_rate: 0.31381059609000017 +[RESULT]: Train. Epoch: 22, summary_loss: 0.62820, final_score: 0.35141, time: 770.89866 +[RESULT]: Val. Epoch: 22, summary_loss: 0.55777, final_score: 0.24725, time: 222.17651 + +2021-04-26T15:33:55.367322 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 23, summary_loss: 0.52325, final_score: 0.23619, time: 750.74651 +[RESULT]: Val. Epoch: 23, summary_loss: 0.54507, final_score: 0.22977, time: 208.27996 + +2021-04-26T15:49:54.775662 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 24, summary_loss: 0.46154, final_score: 0.19158, time: 744.39665 +[RESULT]: Val. Epoch: 24, summary_loss: 0.51685, final_score: 0.18581, time: 183.77523 + +2021-04-26T16:05:23.297804 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 25, summary_loss: 0.44362, final_score: 0.18233, time: 737.16087 +[RESULT]: Val. Epoch: 25, summary_loss: 0.55939, final_score: 0.19530, time: 187.33655 + +2021-04-26T16:20:48.056454 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 26, summary_loss: 0.42108, final_score: 0.16221, time: 819.34592 +[RESULT]: Val. Epoch: 26, summary_loss: 0.51774, final_score: 0.18981, time: 221.13672 + +2021-04-26T16:38:08.717581 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 27, summary_loss: 0.39865, final_score: 0.14696, time: 746.00580 +[RESULT]: Val. Epoch: 27, summary_loss: 0.74408, final_score: 0.19481, time: 201.33170 + +2021-04-26T16:53:56.231355 +LR: 0.0005 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 28, summary_loss: 0.39038, final_score: 0.14259, time: 750.66440 +[RESULT]: Val. Epoch: 28, summary_loss: 0.56817, final_score: 0.17433, time: 193.61742 + +2021-04-26T17:09:40.698192 +LR: 0.00025 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 29, summary_loss: 0.37609, final_score: 0.13334, time: 941.07722 +[RESULT]: Val. Epoch: 29, summary_loss: 0.71209, final_score: 0.18731, time: 189.55742 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:34:01.862678 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-26T09:34:46.492174 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69707, final_score: 0.49000, time: 719.77373 +[RESULT]: Val. Epoch: 0, summary_loss: 0.72082, final_score: 0.49750, time: 196.81023 + +2021-04-26T09:50:03.475680 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.68726, final_score: 0.45801, time: 772.48185 +[RESULT]: Val. Epoch: 1, summary_loss: 0.82043, final_score: 0.47103, time: 216.96237 + +2021-04-26T10:06:33.124114 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.68861, final_score: 0.45926, time: 800.41726 +[RESULT]: Val. Epoch: 2, summary_loss: 0.72185, final_score: 0.48801, time: 234.24038 + +2021-04-26T10:23:47.971353 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.66846, final_score: 0.40527, time: 735.74342 +[RESULT]: Val. Epoch: 3, summary_loss: 0.86980, final_score: 0.48501, time: 223.24549 + +2021-04-26T10:39:47.177567 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.61945, final_score: 0.33304, time: 714.03418 +[RESULT]: Val. Epoch: 4, summary_loss: 1.01832, final_score: 0.47602, time: 202.98260 + +2021-04-26T10:55:04.377192 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.62049, final_score: 0.34216, time: 778.92891 +[RESULT]: Val. Epoch: 5, summary_loss: 0.80051, final_score: 0.40460, time: 219.11712 + +2021-04-26T11:11:42.607498 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.60705, final_score: 0.32004, time: 779.38093 +[RESULT]: Val. Epoch: 6, summary_loss: 0.76574, final_score: 0.41259, time: 219.22035 + +2021-04-26T11:28:21.372259 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.61817, final_score: 0.33879, time: 821.03574 +[RESULT]: Val. Epoch: 7, summary_loss: 0.70790, final_score: 0.40110, time: 207.99961 + +2021-04-26T11:45:30.801650 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.60058, final_score: 0.32429, time: 788.52862 +[RESULT]: Val. Epoch: 8, summary_loss: 0.90226, final_score: 0.42408, time: 201.05897 + +2021-04-26T12:02:00.551600 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.61407, final_score: 0.33629, time: 698.47590 +[RESULT]: Val. Epoch: 9, summary_loss: 0.88051, final_score: 0.39111, time: 222.85231 + +2021-04-26T12:17:22.074495 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.61004, final_score: 0.33217, time: 872.89039 +[RESULT]: Val. Epoch: 10, summary_loss: 0.70871, final_score: 0.40559, time: 222.07895 + +2021-04-26T12:35:37.248937 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.62771, final_score: 0.35529, time: 868.35973 +[RESULT]: Val. Epoch: 11, summary_loss: 0.68183, final_score: 0.36813, time: 213.80985 + +2021-04-26T12:53:39.770362 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.61777, final_score: 0.34204, time: 833.50087 +[RESULT]: Val. Epoch: 12, summary_loss: 1.02616, final_score: 0.43057, time: 222.17575 + +2021-04-26T13:11:15.656506 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 13, summary_loss: 0.62492, final_score: 0.35279, time: 872.08347 +[RESULT]: Val. Epoch: 13, summary_loss: 1.40808, final_score: 0.41259, time: 243.32187 + +2021-04-26T13:29:51.240785 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 14, summary_loss: 0.62226, final_score: 0.35304, time: 801.65164 +[RESULT]: Val. Epoch: 14, summary_loss: 1.00022, final_score: 0.37662, time: 218.39248 + +2021-04-26T13:46:51.474077 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 15, summary_loss: 0.61695, final_score: 0.34491, time: 851.96626 +[RESULT]: Val. Epoch: 15, summary_loss: 0.63506, final_score: 0.35714, time: 221.06723 + +2021-04-26T14:04:44.895334 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 16, summary_loss: 0.61262, final_score: 0.33954, time: 857.64946 +[RESULT]: Val. Epoch: 16, summary_loss: 0.67952, final_score: 0.34466, time: 221.45635 + +2021-04-26T14:22:44.196399 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 17, summary_loss: 0.60672, final_score: 0.33554, time: 777.21898 +[RESULT]: Val. Epoch: 17, summary_loss: 0.62342, final_score: 0.33816, time: 211.96220 + +2021-04-26T14:39:13.843862 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 18, summary_loss: 0.59844, final_score: 0.32867, time: 856.24270 +[RESULT]: Val. Epoch: 18, summary_loss: 0.65147, final_score: 0.37063, time: 232.62245 + +2021-04-26T14:57:22.896947 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 19, summary_loss: 0.59576, final_score: 0.32654, time: 754.23960 +[RESULT]: Val. Epoch: 19, summary_loss: 0.63092, final_score: 0.34316, time: 229.43963 + +2021-04-26T15:13:46.789528 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 20, summary_loss: 0.58195, final_score: 0.30780, time: 861.75581 +[RESULT]: Val. Epoch: 20, summary_loss: 0.74689, final_score: 0.34715, time: 211.59442 + +2021-04-26T15:31:40.360787 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 21, summary_loss: 0.56998, final_score: 0.29480, time: 841.29687 +[RESULT]: Val. Epoch: 21, summary_loss: 0.61841, final_score: 0.32517, time: 242.45947 + +2021-04-26T15:49:44.463508 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 22, summary_loss: 0.57077, final_score: 0.29568, time: 823.56545 +[RESULT]: Val. Epoch: 22, summary_loss: 0.80369, final_score: 0.34066, time: 242.45419 + +2021-04-26T16:07:30.689083 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 23, summary_loss: 0.55931, final_score: 0.28780, time: 851.77157 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69510, final_score: 0.31818, time: 206.89915 + +2021-04-26T16:25:09.584388 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 24, summary_loss: 0.53959, final_score: 0.26406, time: 767.97170 +[RESULT]: Val. Epoch: 24, summary_loss: 0.55658, final_score: 0.28621, time: 224.61215 + +2021-04-26T16:41:42.544607 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 25, summary_loss: 0.53640, final_score: 0.26931, time: 811.64862 +[RESULT]: Val. Epoch: 25, summary_loss: 0.56385, final_score: 0.27273, time: 221.26032 + +2021-04-26T16:58:55.634640 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 26, summary_loss: 0.53151, final_score: 0.26256, time: 762.88616 +[RESULT]: Val. Epoch: 26, summary_loss: 0.83529, final_score: 0.32667, time: 235.73374 + +2021-04-26T17:15:34.479580 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 27, summary_loss: 0.51545, final_score: 0.24569, time: 848.44460 +[RESULT]: Val. Epoch: 27, summary_loss: 0.58723, final_score: 0.26773, time: 230.60560 + +2021-04-26T17:33:33.720703 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 28, summary_loss: 0.51191, final_score: 0.24019, time: 861.89311 +[RESULT]: Val. Epoch: 28, summary_loss: 0.56285, final_score: 0.26374, time: 196.80605 + +2021-04-26T17:51:12.645970 +LR: 6.25e-05 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 29, summary_loss: 0.50843, final_score: 0.24269, time: 863.55153 +[RESULT]: Val. Epoch: 29, summary_loss: 0.53974, final_score: 0.25774, time: 227.52278 +Fitter prepared. 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Device is cuda:0 + +2021-04-25T01:44:38.163600 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69518, final_score: 0.47726, time: 675.68924 +[RESULT]: Val. Epoch: 0, summary_loss: 0.71110, final_score: 0.49151, time: 191.07093 + +2021-04-25T01:59:05.264861 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.67252, final_score: 0.41740, time: 677.82193 +[RESULT]: Val. Epoch: 1, summary_loss: 0.89452, final_score: 0.48352, time: 185.22949 + +2021-04-25T02:13:28.480537 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.60081, final_score: 0.30867, time: 672.94543 +[RESULT]: Val. Epoch: 2, summary_loss: 1.66917, final_score: 0.45904, time: 184.77780 + +2021-04-25T02:27:46.467819 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.57700, final_score: 0.29055, time: 683.31863 +[RESULT]: Val. Epoch: 3, summary_loss: 4.21914, final_score: 0.47802, time: 191.00412 + +2021-04-25T02:42:20.966357 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.54863, final_score: 0.27118, time: 673.75329 +[RESULT]: Val. Epoch: 4, summary_loss: 1.66236, final_score: 0.47153, time: 185.58634 + +2021-04-25T02:56:40.469797 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.55702, final_score: 0.27943, time: 689.66671 +[RESULT]: Val. Epoch: 5, summary_loss: 1.03570, final_score: 0.44256, time: 183.97631 + +2021-04-25T03:11:14.283862 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.53529, final_score: 0.25619, time: 689.75579 +[RESULT]: Val. Epoch: 6, summary_loss: 1.05475, final_score: 0.42657, time: 183.54596 + +2021-04-25T03:25:47.747987 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.56604, final_score: 0.27806, time: 688.93440 +[RESULT]: Val. Epoch: 7, summary_loss: 0.83979, final_score: 0.41558, time: 186.51610 + +2021-04-25T03:40:23.412357 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.54858, final_score: 0.26381, time: 696.44283 +[RESULT]: Val. Epoch: 8, summary_loss: 1.17854, final_score: 0.45504, time: 188.15794 + +2021-04-25T03:55:08.191933 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.57108, final_score: 0.29030, time: 691.07296 +[RESULT]: Val. Epoch: 9, summary_loss: 0.92670, final_score: 0.44456, time: 184.25373 + +2021-04-25T04:09:43.709137 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.56599, final_score: 0.28105, time: 688.23615 +[RESULT]: Val. Epoch: 10, summary_loss: 1.02068, final_score: 0.41958, time: 182.90056 + +2021-04-25T04:24:15.029827 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.59519, final_score: 0.31492, time: 693.37692 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69780, final_score: 0.38811, time: 187.05660 + +2021-04-25T04:38:55.873579 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.59047, final_score: 0.31042, time: 691.94822 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69623, final_score: 0.40460, time: 188.78428 + +2021-04-25T04:53:36.926792 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.60975, final_score: 0.33542, time: 694.30544 +[RESULT]: Val. Epoch: 13, summary_loss: 0.79202, final_score: 0.40110, time: 184.28572 + +2021-04-25T05:08:15.698321 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.60771, final_score: 0.33367, time: 692.70178 +[RESULT]: Val. Epoch: 14, summary_loss: 0.74141, final_score: 0.41858, time: 182.64686 + +2021-04-25T05:22:51.207479 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.63275, final_score: 0.36141, time: 691.33279 +[RESULT]: Val. Epoch: 15, summary_loss: 0.65278, final_score: 0.37512, time: 183.52914 + +2021-04-25T05:37:26.471911 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.62357, final_score: 0.35116, time: 692.97023 +[RESULT]: Val. Epoch: 16, summary_loss: 0.66248, final_score: 0.38661, time: 184.10107 + +2021-04-25T05:52:03.733910 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.64150, final_score: 0.37803, time: 687.82607 +[RESULT]: Val. Epoch: 17, summary_loss: 0.68339, final_score: 0.38511, time: 184.46431 + +2021-04-25T06:06:36.205211 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.63890, final_score: 0.37291, time: 703.89257 +[RESULT]: Val. Epoch: 18, summary_loss: 0.66127, final_score: 0.38911, time: 184.40408 + +2021-04-25T06:21:24.705183 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.63738, final_score: 0.37166, time: 696.96062 +[RESULT]: Val. Epoch: 19, summary_loss: 0.75971, final_score: 0.41958, time: 187.37234 + +2021-04-25T06:36:09.245084 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.63414, final_score: 0.37028, time: 685.41807 +[RESULT]: Val. Epoch: 20, summary_loss: 0.70897, final_score: 0.39910, time: 187.22553 + +2021-04-25T06:50:42.091770 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.62765, final_score: 0.36453, time: 694.04870 +[RESULT]: Val. Epoch: 21, summary_loss: 0.65927, final_score: 0.36763, time: 187.03955 + +2021-04-25T07:05:23.440260 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.62478, final_score: 0.36253, time: 694.65933 +[RESULT]: Val. Epoch: 22, summary_loss: 0.63237, final_score: 0.35465, time: 187.54896 + +2021-04-25T07:20:06.987772 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.62271, final_score: 0.35804, time: 696.79832 +[RESULT]: Val. Epoch: 23, summary_loss: 0.82355, final_score: 0.38412, time: 186.42797 + +2021-04-25T07:34:50.413817 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.62056, final_score: 0.35766, time: 691.07377 +[RESULT]: Val. Epoch: 24, summary_loss: 0.63259, final_score: 0.36314, time: 185.44749 + +2021-04-25T07:49:27.188875 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.61186, final_score: 0.34766, time: 702.45209 +[RESULT]: Val. Epoch: 25, summary_loss: 0.63124, final_score: 0.35914, time: 181.53903 + +2021-04-25T08:04:11.542977 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.61115, final_score: 0.34641, time: 691.85984 +[RESULT]: Val. Epoch: 26, summary_loss: 0.64139, final_score: 0.35614, time: 185.36924 + +2021-04-25T08:18:48.966333 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.60869, final_score: 0.34354, time: 693.57406 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69519, final_score: 0.36763, time: 183.35184 + +2021-04-25T08:33:26.089987 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.60574, final_score: 0.34304, time: 698.59813 +[RESULT]: Val. Epoch: 28, summary_loss: 0.63709, final_score: 0.35015, time: 183.79262 + +2021-04-25T08:48:08.668080 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.59861, final_score: 0.32879, time: 696.18183 +[RESULT]: Val. Epoch: 29, summary_loss: 0.64939, final_score: 0.34865, time: 187.78848 +Fitter prepared. Device is cuda:0 + +2021-04-26T00:51:29.797069 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.67569, final_score: 0.43164, time: 669.36460 +[RESULT]: Val. Epoch: 0, summary_loss: 0.95341, final_score: 0.49301, time: 188.24878 + +2021-04-26T01:05:47.776275 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.61299, final_score: 0.32579, time: 678.77364 +[RESULT]: Val. Epoch: 1, summary_loss: 1.06983, final_score: 0.46204, time: 183.23988 + +2021-04-26T01:20:10.006167 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.54988, final_score: 0.26418, time: 674.04005 +[RESULT]: Val. Epoch: 2, summary_loss: 0.78919, final_score: 0.45105, time: 184.45867 + +2021-04-26T01:34:28.944754 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.53884, final_score: 0.25481, time: 679.42929 +[RESULT]: Val. Epoch: 3, summary_loss: 1.42443, final_score: 0.47353, time: 185.23689 + +2021-04-26T01:48:53.785842 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.51031, final_score: 0.22907, time: 687.51335 +[RESULT]: Val. Epoch: 4, summary_loss: 0.90069, final_score: 0.41808, time: 188.30495 + +2021-04-26T02:03:29.838778 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.47089, final_score: 0.21045, time: 692.56312 +[RESULT]: Val. Epoch: 5, summary_loss: 1.12170, final_score: 0.41658, time: 183.01406 + +2021-04-26T02:18:05.584012 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.44316, final_score: 0.18858, time: 682.33353 +[RESULT]: Val. Epoch: 6, summary_loss: 2.02542, final_score: 0.45155, time: 187.88963 + +2021-04-26T02:32:35.978887 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.48041, final_score: 0.21770, time: 688.72987 +[RESULT]: Val. Epoch: 7, summary_loss: 1.45879, final_score: 0.43856, time: 183.51708 + +2021-04-26T02:47:09.458178 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.47963, final_score: 0.21720, time: 691.55377 +[RESULT]: Val. Epoch: 8, summary_loss: 0.94822, final_score: 0.40210, time: 185.40715 + +2021-04-26T03:01:46.589282 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.51723, final_score: 0.24844, time: 685.76090 +[RESULT]: Val. Epoch: 9, summary_loss: 1.22815, final_score: 0.42607, time: 184.85009 + +2021-04-26T03:16:17.377593 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.51374, final_score: 0.23957, time: 685.03792 +[RESULT]: Val. Epoch: 10, summary_loss: 0.77600, final_score: 0.40160, time: 183.72702 + +2021-04-26T03:30:46.522251 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.55650, final_score: 0.27993, time: 694.92523 +[RESULT]: Val. Epoch: 11, summary_loss: 1.23190, final_score: 0.42158, time: 179.07634 + +2021-04-26T03:45:20.692742 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.55116, final_score: 0.27706, time: 689.47918 +[RESULT]: Val. Epoch: 12, summary_loss: 0.98761, final_score: 0.41658, time: 179.22046 + +2021-04-26T03:59:49.560466 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.59236, final_score: 0.31567, time: 698.24990 +[RESULT]: Val. Epoch: 13, summary_loss: 0.74542, final_score: 0.40260, time: 182.77055 + +2021-04-26T04:14:30.947886 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.58305, final_score: 0.31055, time: 693.84045 +[RESULT]: Val. Epoch: 14, summary_loss: 0.83538, final_score: 0.38312, time: 184.35211 + +2021-04-26T04:29:09.299042 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.61605, final_score: 0.33517, time: 691.35005 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69661, final_score: 0.38162, time: 183.24708 + +2021-04-26T04:43:44.222791 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.60846, final_score: 0.33392, time: 694.29735 +[RESULT]: Val. Epoch: 16, summary_loss: 0.64091, final_score: 0.36314, time: 187.55132 + +2021-04-26T04:58:26.463322 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.62928, final_score: 0.35879, time: 698.10603 +[RESULT]: Val. Epoch: 17, summary_loss: 0.65412, final_score: 0.36663, time: 184.53506 + +2021-04-26T05:13:09.277819 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.62529, final_score: 0.35004, time: 691.66942 +[RESULT]: Val. Epoch: 18, summary_loss: 0.66182, final_score: 0.36813, time: 183.81528 + +2021-04-26T05:27:44.958211 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.60989, final_score: 0.32829, time: 696.02556 +[RESULT]: Val. Epoch: 19, summary_loss: 0.65238, final_score: 0.33766, time: 182.79987 + +2021-04-26T05:42:23.958449 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.60573, final_score: 0.33404, time: 697.03679 +[RESULT]: Val. Epoch: 20, summary_loss: 0.66919, final_score: 0.34965, time: 183.44739 + +2021-04-26T05:57:04.636178 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.59372, final_score: 0.31742, time: 695.26012 +[RESULT]: Val. Epoch: 21, summary_loss: 0.67089, final_score: 0.32867, time: 182.96728 + +2021-04-26T06:11:43.169682 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.58885, final_score: 0.31142, time: 692.56195 +[RESULT]: Val. Epoch: 22, summary_loss: 0.60887, final_score: 0.30420, time: 183.17248 + +2021-04-26T06:26:19.426643 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.58158, final_score: 0.30417, time: 698.81053 +[RESULT]: Val. Epoch: 23, summary_loss: 0.61368, final_score: 0.29670, time: 183.77961 + +2021-04-26T06:41:02.196855 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.57674, final_score: 0.29580, time: 690.13016 +[RESULT]: Val. Epoch: 24, summary_loss: 0.61469, final_score: 0.29371, time: 183.51282 + +2021-04-26T06:55:36.047373 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.56893, final_score: 0.28918, time: 692.57721 +[RESULT]: Val. Epoch: 25, summary_loss: 0.58987, final_score: 0.27473, time: 184.26748 + +2021-04-26T07:10:13.290475 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.56233, final_score: 0.28530, time: 696.55498 +[RESULT]: Val. Epoch: 26, summary_loss: 0.64960, final_score: 0.30519, time: 182.06113 + +2021-04-26T07:24:52.094121 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.56169, final_score: 0.28318, time: 702.98710 +[RESULT]: Val. Epoch: 27, summary_loss: 0.57644, final_score: 0.27522, time: 186.25950 + +2021-04-26T07:39:41.857637 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.55383, final_score: 0.27806, time: 698.75688 +[RESULT]: Val. Epoch: 28, summary_loss: 0.56860, final_score: 0.27473, time: 183.01281 + +2021-04-26T07:54:23.979059 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.54986, final_score: 0.27068, time: 693.88561 +[RESULT]: Val. Epoch: 29, summary_loss: 0.59958, final_score: 0.28072, time: 183.68627 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_4/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_4/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..0d233541142323525352cfeddfa78be6a5e82e72 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_4/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..133c84abc673e8fc291649c7782c398e23adfad8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:59eece4c72bec28c2f3cf50725eeeb71506048ac9429ee6e7c4ab932b1212911 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..20ca984880633b697886c702461c75d39e06f999 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2ff731a96cc201bb6bc0683a82f881d8ab8c835a8f5fa175522a16e7abd5a0d8 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-028epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-028epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b8ab2bb7d6df4b92b7fc0c8c0b919f16a368c0a7 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/best-checkpoint-028epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ee2a5cff252bc1cbf0b2068621aa8940f59ca6b3c425e9e91a1ec5e933fd3aa9 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..f7e12567b0628f06e600fcae3c1ae90f2e995692 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dd5413e6ce57f561f2c24f22818ae149ca1f52ce3a4fe4f74e536104bec9624d +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..625cd67f98a520842ade37cc2abf29d6bf92b4f8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-04-28T09:17:03.039055 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69120, final_score: 0.46038, time: 673.72103 +[RESULT]: Val. Epoch: 0, summary_loss: 0.83286, final_score: 0.48601, time: 191.92316 + +2021-04-28T09:31:29.118815 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.65947, final_score: 0.38453, time: 680.14344 +[RESULT]: Val. Epoch: 1, summary_loss: 0.88634, final_score: 0.49001, time: 188.77037 + +2021-04-28T09:45:58.195370 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.48193, final_score: 0.21145, time: 679.58840 +[RESULT]: Val. Epoch: 2, summary_loss: 1.17088, final_score: 0.45604, time: 185.24895 + +2021-04-28T10:00:23.241858 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.46027, final_score: 0.19633, time: 674.55140 +[RESULT]: Val. Epoch: 3, summary_loss: 0.75781, final_score: 0.43157, time: 187.64411 + +2021-04-28T10:14:45.843455 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.43314, final_score: 0.17808, time: 690.69974 +[RESULT]: Val. Epoch: 4, summary_loss: 0.94664, final_score: 0.44505, time: 189.72032 + +2021-04-28T10:29:26.473220 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.48388, final_score: 0.22494, time: 687.49189 +[RESULT]: Val. Epoch: 5, summary_loss: 1.56707, final_score: 0.45904, time: 185.73663 + +2021-04-28T10:43:59.931377 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.47754, final_score: 0.22094, time: 678.21211 +[RESULT]: Val. Epoch: 6, summary_loss: 0.76468, final_score: 0.42757, time: 186.05779 + +2021-04-28T10:58:24.387855 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.51717, final_score: 0.25456, time: 692.52941 +[RESULT]: Val. Epoch: 7, summary_loss: 0.82250, final_score: 0.42557, time: 187.70294 + +2021-04-28T11:13:04.839183 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.51131, final_score: 0.24844, time: 682.54149 +[RESULT]: Val. Epoch: 8, summary_loss: 0.79267, final_score: 0.42158, time: 187.13281 + +2021-04-28T11:27:34.710728 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55898, final_score: 0.29168, time: 681.25408 +[RESULT]: Val. Epoch: 9, summary_loss: 0.75675, final_score: 0.42008, time: 188.68746 + +2021-04-28T11:42:05.018272 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.55981, final_score: 0.29330, time: 698.65979 +[RESULT]: Val. Epoch: 10, summary_loss: 0.70245, final_score: 0.41808, time: 182.00905 + +2021-04-28T11:56:46.049226 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.59426, final_score: 0.32767, time: 706.36948 +[RESULT]: Val. Epoch: 11, summary_loss: 0.76159, final_score: 0.42308, time: 181.94390 + +2021-04-28T12:11:34.558316 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.59596, final_score: 0.32729, time: 704.16437 +[RESULT]: Val. Epoch: 12, summary_loss: 0.85251, final_score: 0.43706, time: 186.45641 + +2021-04-28T12:26:25.394414 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.62481, final_score: 0.35816, time: 700.09373 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69523, final_score: 0.41409, time: 183.75766 + +2021-04-28T12:41:09.606251 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.62768, final_score: 0.36341, time: 705.93841 +[RESULT]: Val. Epoch: 14, summary_loss: 1.00670, final_score: 0.44755, time: 192.36120 + +2021-04-28T12:56:08.125973 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.65327, final_score: 0.39728, time: 705.47917 +[RESULT]: Val. Epoch: 15, summary_loss: 0.67989, final_score: 0.41359, time: 188.26148 + +2021-04-28T13:11:02.243746 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64706, final_score: 0.39265, time: 690.58154 +[RESULT]: Val. Epoch: 16, summary_loss: 0.68761, final_score: 0.40959, time: 187.72888 + +2021-04-28T13:25:40.714463 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.66136, final_score: 0.41240, time: 688.01917 +[RESULT]: Val. Epoch: 17, summary_loss: 0.67884, final_score: 0.41808, time: 181.10486 + +2021-04-28T13:40:10.225724 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.66202, final_score: 0.41252, time: 700.49083 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69395, final_score: 0.41958, time: 185.29525 + +2021-04-28T13:54:56.253652 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.66153, final_score: 0.41140, time: 706.68414 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69434, final_score: 0.41708, time: 187.79856 + +2021-04-28T14:09:50.911085 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.65793, final_score: 0.41190, time: 678.40341 +[RESULT]: Val. Epoch: 20, summary_loss: 0.66809, final_score: 0.40909, time: 193.15804 + +2021-04-28T14:24:22.865441 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.65229, final_score: 0.40390, time: 689.59019 +[RESULT]: Val. Epoch: 21, summary_loss: 0.68734, final_score: 0.41608, time: 191.40743 + +2021-04-28T14:39:04.064287 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.65722, final_score: 0.40815, time: 697.61092 +[RESULT]: Val. Epoch: 22, summary_loss: 0.70191, final_score: 0.41159, time: 186.34484 + +2021-04-28T14:53:48.172006 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.64936, final_score: 0.40102, time: 705.98758 +[RESULT]: Val. Epoch: 23, summary_loss: 0.70908, final_score: 0.41758, time: 186.86131 + +2021-04-28T15:08:41.221194 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.64837, final_score: 0.40202, time: 720.94903 +[RESULT]: Val. Epoch: 24, summary_loss: 0.69093, final_score: 0.40909, time: 195.40607 + +2021-04-28T15:23:57.758478 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.64428, final_score: 0.39415, time: 733.39929 +[RESULT]: Val. Epoch: 25, summary_loss: 0.66479, final_score: 0.40060, time: 199.77938 + +2021-04-28T15:39:31.491835 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.64823, final_score: 0.39753, time: 736.82147 +[RESULT]: Val. Epoch: 26, summary_loss: 0.65820, final_score: 0.39610, time: 194.25484 + +2021-04-28T15:55:02.925455 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.64595, final_score: 0.39665, time: 719.28831 +[RESULT]: Val. Epoch: 27, summary_loss: 0.66794, final_score: 0.40010, time: 188.24552 + +2021-04-28T16:10:10.635394 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.64496, final_score: 0.39853, time: 700.59070 +[RESULT]: Val. Epoch: 28, summary_loss: 0.65671, final_score: 0.39161, time: 184.23340 + +2021-04-28T16:24:55.862689 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.64249, final_score: 0.39203, time: 707.37978 +[RESULT]: Val. Epoch: 29, summary_loss: 0.65977, final_score: 0.39760, time: 188.81951 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..9692da412b6a8a29bebd19ae476a6130d5e93602 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_5/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..015681eb0402974780cde54403ce3df51af65382 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:060e2a00acb1014fb3c0dea9ee7acb7ed9fc9b5e5afaf39244e90e3b227c385b +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..43975199e5efd15469be53fbcbc7684a4df3925d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7e42a808bad8020031d58bee89236a629b55916b84243ba0bdb23fd5fe74eeea +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..65dc103d232ac166ca6c1873ad464fa7299bd15b --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ef5f4043c69512ce5dbb5fa3c6127251d599386506ace77c7af99eab5276130b +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..3cecd59209a9e2d5506b2271474a5a13e3c183cc --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:90abe9a137d5f9e4c5b93ffb66bf2ab5c46a56a650da11e5b95c29783f66d0da +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..5e3918ec38eebdd404fecfd3be318a9fc92ba4fc --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-10T19:19:47.144092 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.68731, final_score: 0.45514, time: 677.08043 +[RESULT]: Val. Epoch: 0, summary_loss: 3.27126, final_score: 0.49251, time: 188.21371 + +2021-06-10T19:34:12.879213 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.50298, final_score: 0.22707, time: 682.58422 +[RESULT]: Val. Epoch: 1, summary_loss: 0.96637, final_score: 0.43257, time: 185.80895 + +2021-06-10T19:48:42.671201 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40013, final_score: 0.15596, time: 675.05807 +[RESULT]: Val. Epoch: 2, summary_loss: 1.52525, final_score: 0.44705, time: 186.24561 + +2021-06-10T20:03:04.187907 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.43356, final_score: 0.18145, time: 682.81344 +[RESULT]: Val. Epoch: 3, summary_loss: 0.85419, final_score: 0.42158, time: 187.44044 + +2021-06-10T20:17:34.837615 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.41802, final_score: 0.17421, time: 685.80909 +[RESULT]: Val. Epoch: 4, summary_loss: 0.86067, final_score: 0.42557, time: 193.27600 + +2021-06-10T20:32:14.180709 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.46686, final_score: 0.21132, time: 694.69328 +[RESULT]: Val. Epoch: 5, summary_loss: 0.86891, final_score: 0.41858, time: 187.88971 + +2021-06-10T20:46:56.947211 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.45822, final_score: 0.20857, time: 685.40362 +[RESULT]: Val. Epoch: 6, summary_loss: 0.79272, final_score: 0.41808, time: 188.27934 + +2021-06-10T21:01:31.166274 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.50827, final_score: 0.24856, time: 690.56607 +[RESULT]: Val. Epoch: 7, summary_loss: 0.73001, final_score: 0.41758, time: 190.57430 + +2021-06-10T21:16:12.702328 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.50718, final_score: 0.24756, time: 690.19730 +[RESULT]: Val. Epoch: 8, summary_loss: 0.73617, final_score: 0.40859, time: 189.24308 + +2021-06-10T21:30:52.330073 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55591, final_score: 0.28830, time: 700.33402 +[RESULT]: Val. Epoch: 9, summary_loss: 0.68520, final_score: 0.40909, time: 194.03127 + +2021-06-10T21:45:47.067990 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.54580, final_score: 0.27881, time: 701.44615 +[RESULT]: Val. Epoch: 10, summary_loss: 0.70717, final_score: 0.41508, time: 187.21244 + +2021-06-10T22:00:35.971298 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.59303, final_score: 0.32542, time: 697.04667 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69791, final_score: 0.40809, time: 186.43429 + +2021-06-10T22:15:19.635009 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.58670, final_score: 0.31830, time: 695.58123 +[RESULT]: Val. Epoch: 12, summary_loss: 0.71739, final_score: 0.40559, time: 186.58981 + +2021-06-10T22:30:02.021764 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.62161, final_score: 0.35954, time: 696.32514 +[RESULT]: Val. Epoch: 13, summary_loss: 0.78059, final_score: 0.41259, time: 185.83294 + +2021-06-10T22:44:44.380907 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.62060, final_score: 0.35854, time: 696.72542 +[RESULT]: Val. Epoch: 14, summary_loss: 0.67023, final_score: 0.40260, time: 186.69610 + +2021-06-10T22:59:28.166339 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64812, final_score: 0.38703, time: 691.99194 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69258, final_score: 0.41059, time: 184.74545 + +2021-06-10T23:14:05.134744 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64894, final_score: 0.38915, time: 703.67975 +[RESULT]: Val. Epoch: 16, summary_loss: 0.67335, final_score: 0.40160, time: 190.52221 + +2021-06-10T23:28:59.528901 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.65881, final_score: 0.40602, time: 693.63919 +[RESULT]: Val. Epoch: 17, summary_loss: 0.67554, final_score: 0.40559, time: 186.26223 + +2021-06-10T23:43:39.651070 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.65816, final_score: 0.40740, time: 697.84232 +[RESULT]: Val. Epoch: 18, summary_loss: 0.71612, final_score: 0.41758, time: 186.69843 + +2021-06-10T23:58:24.391056 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.65421, final_score: 0.40552, time: 694.39797 +[RESULT]: Val. Epoch: 19, summary_loss: 0.65954, final_score: 0.39910, time: 192.90936 + +2021-06-11T00:13:12.170881 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.65044, final_score: 0.39928, time: 693.30720 +[RESULT]: Val. Epoch: 20, summary_loss: 0.87252, final_score: 0.42258, time: 189.15027 + +2021-06-11T00:27:54.817642 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.65252, final_score: 0.40177, time: 704.17414 +[RESULT]: Val. Epoch: 21, summary_loss: 0.66115, final_score: 0.39860, time: 188.80439 + +2021-06-11T00:42:48.015513 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.64745, final_score: 0.39215, time: 701.08243 +[RESULT]: Val. Epoch: 22, summary_loss: 0.65652, final_score: 0.40010, time: 187.23476 + +2021-06-11T00:57:36.903341 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.64858, final_score: 0.39815, time: 694.43013 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69695, final_score: 0.40260, time: 187.22537 + +2021-06-11T01:12:18.749684 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.64840, final_score: 0.39403, time: 703.13372 +[RESULT]: Val. Epoch: 24, summary_loss: 0.65689, final_score: 0.39510, time: 185.79853 + +2021-06-11T01:27:07.875209 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.64005, final_score: 0.38878, time: 695.86677 +[RESULT]: Val. Epoch: 25, summary_loss: 0.67700, final_score: 0.39710, time: 190.29328 + +2021-06-11T01:41:54.250348 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.64505, final_score: 0.39690, time: 701.36822 +[RESULT]: Val. Epoch: 26, summary_loss: 0.65173, final_score: 0.38511, time: 185.37624 + +2021-06-11T01:56:41.384912 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.64348, final_score: 0.39053, time: 696.08961 +[RESULT]: Val. Epoch: 27, summary_loss: 0.67011, final_score: 0.39610, time: 185.37327 + +2021-06-11T02:11:23.047955 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.64366, final_score: 0.39278, time: 702.21345 +[RESULT]: Val. Epoch: 28, summary_loss: 0.65673, final_score: 0.38362, time: 187.15324 + +2021-06-11T02:26:12.694778 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.64200, final_score: 0.38878, time: 711.19274 +[RESULT]: Val. Epoch: 29, summary_loss: 0.64960, final_score: 0.38911, time: 186.69439 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..91da9182ae1cf9c5f227ea647d3b030a28d648e5 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_6/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..45f94939d7ed5cb93c79a4854a313403e25ec3a6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:82cdc05ed402e24f2948e79fbf7e53fdf951811a2962118e03cab31b2de9a925 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-023epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-023epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f931b2c9d8062d970dfd3b12da1296777d7dfbd9 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-023epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4df13e13c4fc912ac4cdfa7749c8b688454972b680786c6018ed872dfccc27f8 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b8628a16e3fcb3015c203266c87814c165a86db0 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7c078989d6ddd793a18484a15dfb679d3bf6c30ff7e23df0dd2eec57b821aad4 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..7788689160e4544dc47f56246a8b49ed7332824e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:46fdc46c4d3b11f65439c853cd12e8b1442209f9ca2251243efa06f29a84f3ea +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d07f7e6b04a2be2adf970ef53fdd3f257371f333 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_7/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-11T15:46:08.722870 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69604, final_score: 0.48600, time: 684.04594 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69612, final_score: 0.49600, time: 189.63013 + +2021-06-11T16:00:42.787677 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.52816, final_score: 0.26418, time: 683.65382 +[RESULT]: Val. Epoch: 1, summary_loss: 0.96657, final_score: 0.45055, time: 189.69005 + +2021-06-11T16:15:16.292832 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.40615, final_score: 0.15246, time: 676.66003 +[RESULT]: Val. Epoch: 2, summary_loss: 1.66709, final_score: 0.46903, time: 183.80052 + +2021-06-11T16:29:36.957299 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.44143, final_score: 0.18770, time: 679.32107 +[RESULT]: Val. Epoch: 3, summary_loss: 1.62327, final_score: 0.46404, time: 188.99581 + +2021-06-11T16:44:05.456583 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.41763, final_score: 0.16908, time: 675.32129 +[RESULT]: Val. Epoch: 4, summary_loss: 0.90274, final_score: 0.44256, time: 183.72909 + +2021-06-11T16:58:24.676424 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.46539, final_score: 0.21207, time: 683.25130 +[RESULT]: Val. Epoch: 5, summary_loss: 0.77540, final_score: 0.42258, time: 182.92042 + +2021-06-11T17:12:51.040787 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.46391, final_score: 0.20932, time: 681.10466 +[RESULT]: Val. Epoch: 6, summary_loss: 0.90173, final_score: 0.44905, time: 182.67492 + +2021-06-11T17:27:15.019028 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.51016, final_score: 0.24469, time: 693.68207 +[RESULT]: Val. Epoch: 7, summary_loss: 1.16790, final_score: 0.46953, time: 185.28172 + +2021-06-11T17:41:54.151886 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.50271, final_score: 0.23869, time: 689.33626 +[RESULT]: Val. Epoch: 8, summary_loss: 1.51355, final_score: 0.46603, time: 183.92731 + +2021-06-11T17:56:27.584674 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.55205, final_score: 0.27868, time: 690.60421 +[RESULT]: Val. Epoch: 9, summary_loss: 0.74199, final_score: 0.41259, time: 183.66027 + +2021-06-11T18:11:02.030065 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.53915, final_score: 0.26918, time: 699.89606 +[RESULT]: Val. Epoch: 10, summary_loss: 0.73270, final_score: 0.42208, time: 183.04418 + +2021-06-11T18:25:45.156882 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.58692, final_score: 0.30967, time: 702.70385 +[RESULT]: Val. Epoch: 11, summary_loss: 1.05335, final_score: 0.43057, time: 183.13528 + +2021-06-11T18:40:31.154083 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.58596, final_score: 0.30580, time: 697.01429 +[RESULT]: Val. Epoch: 12, summary_loss: 0.94769, final_score: 0.44755, time: 186.07912 + +2021-06-11T18:55:14.397553 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.61886, final_score: 0.34504, time: 704.92018 +[RESULT]: Val. Epoch: 13, summary_loss: 0.68109, final_score: 0.42557, time: 182.75472 + +2021-06-11T19:10:02.452452 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.61853, final_score: 0.34129, time: 692.48179 +[RESULT]: Val. Epoch: 14, summary_loss: 0.71877, final_score: 0.40360, time: 186.52400 + +2021-06-11T19:24:41.620981 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64583, final_score: 0.38065, time: 698.90109 +[RESULT]: Val. Epoch: 15, summary_loss: 0.67868, final_score: 0.39910, time: 184.80719 + +2021-06-11T19:39:25.673643 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64277, final_score: 0.37803, time: 693.92450 +[RESULT]: Val. Epoch: 16, summary_loss: 0.68258, final_score: 0.40360, time: 183.94090 + +2021-06-11T19:54:03.706543 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.65978, final_score: 0.40627, time: 706.98273 +[RESULT]: Val. Epoch: 17, summary_loss: 0.69041, final_score: 0.40010, time: 182.95148 + +2021-06-11T20:08:53.795001 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.65698, final_score: 0.39840, time: 693.09564 +[RESULT]: Val. Epoch: 18, summary_loss: 0.67917, final_score: 0.39461, time: 184.15152 + +2021-06-11T20:23:31.224445 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.65800, final_score: 0.40140, time: 701.36281 +[RESULT]: Val. Epoch: 19, summary_loss: 0.73187, final_score: 0.40410, time: 188.18391 + +2021-06-11T20:38:20.959053 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.65745, final_score: 0.39765, time: 701.12851 +[RESULT]: Val. Epoch: 20, summary_loss: 0.68988, final_score: 0.40310, time: 184.76770 + +2021-06-11T20:53:07.021980 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.65420, final_score: 0.39290, time: 691.35102 +[RESULT]: Val. Epoch: 21, summary_loss: 0.67993, final_score: 0.40559, time: 189.79220 + +2021-06-11T21:07:48.322515 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.65080, final_score: 0.39228, time: 702.64375 +[RESULT]: Val. Epoch: 22, summary_loss: 0.66712, final_score: 0.39061, time: 183.19960 + +2021-06-11T21:22:34.494025 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.64914, final_score: 0.38615, time: 686.91285 +[RESULT]: Val. Epoch: 23, summary_loss: 0.65860, final_score: 0.39261, time: 182.76339 + +2021-06-11T21:37:04.587477 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.64787, final_score: 0.38753, time: 688.42979 +[RESULT]: Val. Epoch: 24, summary_loss: 0.71183, final_score: 0.39311, time: 184.45518 + +2021-06-11T21:51:37.628549 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.64705, final_score: 0.38478, time: 700.07746 +[RESULT]: Val. Epoch: 25, summary_loss: 0.67023, final_score: 0.40210, time: 185.39128 + +2021-06-11T22:06:23.255680 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.64588, final_score: 0.37891, time: 698.95333 +[RESULT]: Val. Epoch: 26, summary_loss: 0.66024, final_score: 0.38362, time: 191.53146 + +2021-06-11T22:21:13.899317 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.64053, final_score: 0.37478, time: 702.80761 +[RESULT]: Val. Epoch: 27, summary_loss: 0.68248, final_score: 0.38262, time: 186.23175 + +2021-06-11T22:36:03.121787 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.63630, final_score: 0.36978, time: 693.64341 +[RESULT]: Val. Epoch: 28, summary_loss: 0.66054, final_score: 0.37962, time: 182.51617 + +2021-06-11T22:50:39.470912 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.63652, final_score: 0.37228, time: 691.25406 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T17:49:02.428237 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69727, final_score: 0.49813, time: 292.86171 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.49550, time: 27.75810 + +2021-06-25T17:54:23.385561 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69314, final_score: 0.49750, time: 289.78386 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69314, final_score: 0.49351, time: 25.38252 + +2021-06-25T17:59:38.872938 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69314, final_score: 0.49650, time: 289.60142 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69321, final_score: 0.49201, time: 28.61540 + +2021-06-25T18:04:57.280499 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69334, final_score: 0.49313, time: 290.00163 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69325, final_score: 0.49251, time: 27.11310 + +2021-06-25T18:10:14.558267 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69322, final_score: 0.48925, time: 289.89929 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69274, final_score: 0.48152, time: 27.81536 + +2021-06-25T18:15:32.639574 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.68072, final_score: 0.43077, time: 289.73918 +[RESULT]: Val. Epoch: 5, summary_loss: 1.36291, final_score: 0.45654, time: 26.60440 + +2021-06-25T18:20:49.189846 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.65094, final_score: 0.36853, time: 289.61738 +[RESULT]: Val. Epoch: 6, summary_loss: 0.71531, final_score: 0.34865, time: 27.77381 + +2021-06-25T18:26:06.750356 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.63272, final_score: 0.33704, time: 289.68461 +[RESULT]: Val. Epoch: 7, summary_loss: 0.73914, final_score: 0.34865, time: 26.97391 + +2021-06-25T18:31:23.595249 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.61944, final_score: 0.31455, time: 289.99606 +[RESULT]: Val. Epoch: 8, summary_loss: 0.67919, final_score: 0.32318, time: 26.47827 + +2021-06-25T18:36:40.494099 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.60797, final_score: 0.30742, time: 290.04007 +[RESULT]: Val. Epoch: 9, summary_loss: 0.65731, final_score: 0.31419, time: 26.75961 + +2021-06-25T18:41:57.644455 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.59792, final_score: 0.28793, time: 289.85661 +[RESULT]: Val. Epoch: 10, summary_loss: 0.94868, final_score: 0.35964, time: 26.27805 + +2021-06-25T18:47:13.975248 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.58634, final_score: 0.28305, time: 289.83156 +[RESULT]: Val. Epoch: 11, summary_loss: 0.66303, final_score: 0.29471, time: 26.30541 + +2021-06-25T18:52:30.278037 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.57640, final_score: 0.26843, time: 289.87555 +[RESULT]: Val. Epoch: 12, summary_loss: 0.61465, final_score: 0.25824, time: 26.10344 + +2021-06-25T18:57:46.596315 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.56466, final_score: 0.26556, time: 290.30883 +[RESULT]: Val. Epoch: 13, summary_loss: 0.61715, final_score: 0.28422, time: 25.69262 + +2021-06-25T19:03:02.761951 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.55181, final_score: 0.25556, time: 289.57868 +[RESULT]: Val. Epoch: 14, summary_loss: 0.62465, final_score: 0.26474, time: 26.57881 + +2021-06-25T19:08:19.089254 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54724, final_score: 0.24856, time: 289.46383 +[RESULT]: Val. Epoch: 15, summary_loss: 0.59202, final_score: 0.26523, time: 26.83469 + +2021-06-25T19:13:35.701635 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.53948, final_score: 0.24456, time: 289.58824 +[RESULT]: Val. Epoch: 16, summary_loss: 0.56776, final_score: 0.24775, time: 27.11090 + +2021-06-25T19:18:52.774146 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.53056, final_score: 0.24394, time: 289.70150 +[RESULT]: Val. Epoch: 17, summary_loss: 0.58061, final_score: 0.25475, time: 26.41062 + +2021-06-25T19:24:09.088919 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.52216, final_score: 0.22432, time: 289.69115 +[RESULT]: Val. Epoch: 18, summary_loss: 0.59488, final_score: 0.25624, time: 25.42840 + +2021-06-25T19:29:24.437772 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.50498, final_score: 0.21682, time: 290.24320 +[RESULT]: Val. Epoch: 19, summary_loss: 0.54470, final_score: 0.23427, time: 25.85747 + +2021-06-25T19:34:40.916190 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.49314, final_score: 0.21020, time: 289.96560 +[RESULT]: Val. Epoch: 20, summary_loss: 0.54617, final_score: 0.24076, time: 28.58628 + +2021-06-25T19:39:59.651676 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.49175, final_score: 0.20882, time: 289.58894 +[RESULT]: Val. Epoch: 21, summary_loss: 0.60868, final_score: 0.24426, time: 26.70542 + +2021-06-25T19:45:16.108563 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.47203, final_score: 0.19783, time: 290.07902 +[RESULT]: Val. Epoch: 22, summary_loss: 0.56568, final_score: 0.21728, time: 26.08703 + +2021-06-25T19:50:32.441905 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.46786, final_score: 0.18945, time: 290.06886 +[RESULT]: Val. Epoch: 23, summary_loss: 0.52529, final_score: 0.21528, time: 26.59213 + +2021-06-25T19:55:49.543079 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.46405, final_score: 0.19108, time: 289.76876 +[RESULT]: Val. Epoch: 24, summary_loss: 0.54552, final_score: 0.22128, time: 25.26996 + +2021-06-25T20:01:04.764438 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.45629, final_score: 0.18520, time: 289.96113 +[RESULT]: Val. Epoch: 25, summary_loss: 0.53980, final_score: 0.21778, time: 26.25574 + +2021-06-25T20:06:21.158428 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.45569, final_score: 0.18308, time: 290.11026 +[RESULT]: Val. Epoch: 26, summary_loss: 0.56285, final_score: 0.21728, time: 25.67554 + +2021-06-25T20:11:37.102755 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.44331, final_score: 0.17333, time: 289.81444 +[RESULT]: Val. Epoch: 27, summary_loss: 0.57966, final_score: 0.22028, time: 26.44009 + +2021-06-25T20:16:53.550162 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.44404, final_score: 0.17333, time: 290.48909 +[RESULT]: Val. Epoch: 28, summary_loss: 0.54456, final_score: 0.21329, time: 26.22491 + +2021-06-25T20:22:10.449592 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.44118, final_score: 0.17508, time: 289.74960 +[RESULT]: Val. Epoch: 29, summary_loss: 0.56672, final_score: 0.21179, time: 28.22401 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:23.028649 +LR: 0.00025 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 25, summary_loss: 0.45189, final_score: 0.18733, time: 291.81960 +[RESULT]: Val. Epoch: 25, summary_loss: 0.65449, final_score: 0.24725, time: 24.87709 + +2021-06-26T08:58:39.904877 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 26, summary_loss: 0.44770, final_score: 0.18783, time: 292.14375 +[RESULT]: Val. Epoch: 26, summary_loss: 0.60313, final_score: 0.22478, time: 24.19452 + +2021-06-26T09:03:56.401760 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 27, summary_loss: 0.44270, final_score: 0.18258, time: 292.54626 +[RESULT]: Val. Epoch: 27, summary_loss: 0.66302, final_score: 0.22228, time: 25.36440 + +2021-06-26T09:09:14.502503 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 28, summary_loss: 0.44137, final_score: 0.18245, time: 292.94754 +[RESULT]: Val. Epoch: 28, summary_loss: 0.65210, final_score: 0.23177, time: 25.06140 + +2021-06-26T09:14:32.663993 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 29, summary_loss: 0.43608, final_score: 0.17583, time: 293.07006 +[RESULT]: Val. Epoch: 29, summary_loss: 0.73702, final_score: 0.24276, time: 25.30536 + +2021-06-26T09:19:51.189770 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 30, summary_loss: 0.43338, final_score: 0.17258, time: 293.47956 +[RESULT]: Val. Epoch: 30, summary_loss: 0.60193, final_score: 0.22178, time: 24.77353 + +2021-06-26T09:25:09.614416 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.42722, final_score: 0.17246, time: 293.12160 +[RESULT]: Val. Epoch: 31, summary_loss: 0.52979, final_score: 0.20130, time: 24.64053 + +2021-06-26T09:30:27.719624 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.42615, final_score: 0.17308, time: 292.30374 +[RESULT]: Val. Epoch: 32, summary_loss: 0.49679, final_score: 0.19031, time: 25.24043 + +2021-06-26T09:35:45.622464 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.41764, final_score: 0.16921, time: 292.49725 +[RESULT]: Val. Epoch: 33, summary_loss: 0.50450, final_score: 0.19331, time: 25.10311 + +2021-06-26T09:41:03.499548 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 34, summary_loss: 0.41413, final_score: 0.16071, time: 292.49773 +[RESULT]: Val. Epoch: 34, summary_loss: 0.51745, final_score: 0.19980, time: 24.77981 + +2021-06-26T09:46:20.954637 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 35, summary_loss: 0.40650, final_score: 0.15609, time: 293.33376 +[RESULT]: Val. Epoch: 35, summary_loss: 0.60940, final_score: 0.21279, time: 24.63485 + +2021-06-26T09:51:39.076201 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 36, summary_loss: 0.40990, final_score: 0.15996, time: 292.82747 +[RESULT]: Val. Epoch: 36, summary_loss: 0.55569, final_score: 0.20180, time: 24.94271 + +2021-06-26T09:56:56.998003 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.40557, final_score: 0.15846, time: 293.78376 +[RESULT]: Val. Epoch: 37, summary_loss: 0.51606, final_score: 0.19780, time: 24.83757 + +2021-06-26T10:02:15.814147 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 38, summary_loss: 0.40171, final_score: 0.15584, time: 292.65451 +[RESULT]: Val. Epoch: 38, summary_loss: 0.54043, final_score: 0.19031, time: 24.83443 + +2021-06-26T10:07:33.504435 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 39, summary_loss: 0.39606, final_score: 0.15509, time: 292.79666 +[RESULT]: Val. Epoch: 39, summary_loss: 0.50692, final_score: 0.17932, time: 24.10612 + +2021-06-26T10:12:50.592648 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 40, summary_loss: 0.39795, final_score: 0.14996, time: 292.70829 +[RESULT]: Val. Epoch: 40, summary_loss: 0.49092, final_score: 0.18282, time: 25.38920 + +2021-06-26T10:18:09.056758 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 41, summary_loss: 0.39255, final_score: 0.14859, time: 292.75326 +[RESULT]: Val. Epoch: 41, summary_loss: 0.52156, final_score: 0.17932, time: 24.77357 + +2021-06-26T10:23:26.752735 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 42, summary_loss: 0.39351, final_score: 0.14746, time: 292.85319 +[RESULT]: Val. Epoch: 42, summary_loss: 0.47958, final_score: 0.17682, time: 25.36328 + +2021-06-26T10:28:45.325783 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 43, summary_loss: 0.39403, final_score: 0.15071, time: 292.88364 +[RESULT]: Val. Epoch: 43, summary_loss: 0.74496, final_score: 0.22827, time: 25.35344 + +2021-06-26T10:34:03.756642 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 44, summary_loss: 0.38451, final_score: 0.14084, time: 293.61539 +[RESULT]: Val. Epoch: 44, summary_loss: 0.49627, final_score: 0.18332, time: 24.94457 + +2021-06-26T10:39:22.510951 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 45, summary_loss: 0.37020, final_score: 0.13534, time: 292.56209 +[RESULT]: Val. Epoch: 45, summary_loss: 0.48730, final_score: 0.17283, time: 24.18207 + +2021-06-26T10:44:39.412829 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.36732, final_score: 0.13309, time: 292.33883 +[RESULT]: Val. Epoch: 46, summary_loss: 0.60967, final_score: 0.19680, time: 24.94191 + +2021-06-26T10:49:56.884807 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.36026, final_score: 0.12822, time: 293.03908 +[RESULT]: Val. Epoch: 47, summary_loss: 0.49320, final_score: 0.16583, time: 25.04548 + +2021-06-26T10:55:15.153712 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.35337, final_score: 0.12259, time: 292.85231 +[RESULT]: Val. Epoch: 48, summary_loss: 0.53850, final_score: 0.17133, time: 24.54796 + +2021-06-26T11:00:32.729820 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.35165, final_score: 0.12272, time: 293.49351 +[RESULT]: Val. Epoch: 49, summary_loss: 0.56016, final_score: 0.17782, time: 24.81000 + +2021-06-26T11:05:51.210238 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.35658, final_score: 0.12359, time: 292.92830 +[RESULT]: Val. Epoch: 50, summary_loss: 0.54388, final_score: 0.17483, time: 25.27919 + +2021-06-26T11:11:09.604416 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.35439, final_score: 0.12572, time: 292.62036 +[RESULT]: Val. Epoch: 51, summary_loss: 0.51559, final_score: 0.17582, time: 24.73404 + +2021-06-26T11:16:27.142723 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.34945, final_score: 0.12222, time: 293.01267 +[RESULT]: Val. Epoch: 52, summary_loss: 0.52111, final_score: 0.16833, time: 25.36918 + +2021-06-26T11:21:45.682587 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.34669, final_score: 0.11422, time: 293.68585 +[RESULT]: Val. Epoch: 53, summary_loss: 0.54120, final_score: 0.17183, time: 24.49170 + +2021-06-26T11:27:04.008325 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.34957, final_score: 0.12159, time: 292.84288 +[RESULT]: Val. Epoch: 54, summary_loss: 0.55379, final_score: 0.17333, time: 24.30216 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..cdf9da4513d18f7dc6a06fc767a81a0747fc1fc8 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/best-checkpoint-000epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/best-checkpoint-000epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..8a2d4afd229a4111601b08a65e6ab6d10ef11788 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/best-checkpoint-000epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a444d4d1f51f448d3d8f4a6e58dd1ca7c447a7e51d682150118f25cff4ecdfb8 +size 57505280 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/best-checkpoint-002epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/best-checkpoint-002epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..9ca6d6c2d9f51a29045b076518d3960c30d3be99 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/best-checkpoint-002epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8491c5fe26baebca13f27c0228823d588af410df763ce6982a675778859a1a11 +size 57505408 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..20c51e2af59388e2de0b1d95aede28ae16675099 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8b5884d7c38be1c4d432e16c043dd2608bc11b4de82e372a12e8b0f2946f45d8 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..c43ff8a96453d6e14a2a1d94e92eb2a3a1443a13 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_2/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T17:48:31.217710 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69745, final_score: 0.49800, time: 297.77635 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.49550, time: 25.05583 + +2021-06-25T17:53:54.386642 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69315, final_score: 0.49713, time: 299.63052 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69315, final_score: 0.49451, time: 26.33651 + +2021-06-25T17:59:20.521064 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69315, final_score: 0.49700, time: 299.90197 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69314, final_score: 0.49451, time: 25.51630 + +2021-06-25T18:04:46.243832 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69329, final_score: 0.49688, time: 300.23060 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69314, final_score: 0.49401, time: 26.58505 + +2021-06-25T18:10:13.213922 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69315, final_score: 0.49550, time: 299.79131 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69320, final_score: 0.49401, time: 26.55114 + +2021-06-25T18:15:39.724061 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69351, final_score: 0.49763, time: 299.80171 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69315, final_score: 0.49600, time: 25.76542 + +2021-06-25T18:21:05.475230 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69384, final_score: 0.49913, time: 304.73306 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69315, final_score: 0.49750, time: 25.24654 + +2021-06-25T18:26:35.614447 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69317, final_score: 0.49875, time: 305.79557 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69315, final_score: 0.49750, time: 26.48679 + +2021-06-25T18:32:08.068812 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69315, final_score: 0.49863, time: 305.76004 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69316, final_score: 0.49750, time: 25.64165 + +2021-06-25T18:37:39.634469 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69315, final_score: 0.49850, time: 302.48866 +[RESULT]: Val. Epoch: 9, summary_loss: 0.69315, final_score: 0.49650, time: 25.04062 + +2021-06-25T18:43:07.359731 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69315, final_score: 0.49838, time: 302.05898 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69315, final_score: 0.49550, time: 25.08117 + +2021-06-25T18:48:34.652711 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69315, final_score: 0.49813, time: 302.23824 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69314, final_score: 0.49650, time: 24.91378 + +2021-06-25T18:54:02.004774 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69319, final_score: 0.49838, time: 302.62885 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69314, final_score: 0.49550, time: 25.37326 + +2021-06-25T18:59:30.162593 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69326, final_score: 0.49825, time: 302.44568 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69389, final_score: 0.49800, time: 25.57453 + +2021-06-25T19:04:58.355060 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69320, final_score: 0.49913, time: 301.85359 +[RESULT]: Val. Epoch: 14, summary_loss: 0.69317, final_score: 0.49700, time: 25.79353 + +2021-06-25T19:10:26.181201 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69322, final_score: 0.49913, time: 301.54334 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69346, final_score: 0.49800, time: 25.39791 + +2021-06-25T19:15:53.289444 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69373, final_score: 0.49775, time: 302.46469 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69316, final_score: 0.49650, time: 26.48563 + +2021-06-25T19:21:22.432802 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69334, final_score: 0.49838, time: 301.40566 +[RESULT]: Val. Epoch: 17, summary_loss: 0.69315, final_score: 0.49800, time: 26.05330 + +2021-06-25T19:26:50.055258 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.69315, final_score: 0.49838, time: 301.91614 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69315, final_score: 0.49750, time: 26.10945 + +2021-06-25T19:32:18.265979 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.69315, final_score: 0.49838, time: 302.53241 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69315, final_score: 0.49700, time: 25.07806 + +2021-06-25T19:37:46.041431 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.69315, final_score: 0.49800, time: 303.11217 +[RESULT]: Val. Epoch: 20, summary_loss: 0.69315, final_score: 0.49650, time: 24.68546 + +2021-06-25T19:43:14.009441 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.69315, final_score: 0.49800, time: 302.40423 +[RESULT]: Val. Epoch: 21, summary_loss: 0.69315, final_score: 0.49750, time: 25.15155 + +2021-06-25T19:48:41.736861 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.69315, final_score: 0.49813, time: 300.70125 +[RESULT]: Val. Epoch: 22, summary_loss: 0.69315, final_score: 0.49700, time: 25.41788 + +2021-06-25T19:54:08.021505 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.69315, final_score: 0.49813, time: 301.95056 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69315, final_score: 0.49700, time: 25.46449 + +2021-06-25T19:59:35.589328 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.69315, final_score: 0.49813, time: 301.70326 +[RESULT]: Val. Epoch: 24, summary_loss: 0.69315, final_score: 0.49600, time: 24.93053 + +2021-06-25T20:05:02.389566 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.69315, final_score: 0.49800, time: 301.72895 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69315, final_score: 0.49650, time: 25.29340 + +2021-06-25T20:10:29.560755 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.69315, final_score: 0.49788, time: 301.78525 +[RESULT]: Val. Epoch: 26, summary_loss: 0.69315, final_score: 0.49650, time: 25.68990 + +2021-06-25T20:15:57.209656 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.69315, final_score: 0.49788, time: 301.84649 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69315, final_score: 0.49650, time: 25.82748 + +2021-06-25T20:21:25.039149 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.69315, final_score: 0.49763, time: 301.44269 +[RESULT]: Val. Epoch: 28, summary_loss: 0.69315, final_score: 0.49650, time: 25.30243 + +2021-06-25T20:26:51.964828 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.69315, final_score: 0.49800, time: 300.17405 +[RESULT]: Val. Epoch: 29, summary_loss: 0.69315, final_score: 0.49600, time: 24.71757 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:23.143091 +LR: 0.00025 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 25, summary_loss: 0.58494, final_score: 0.30430, time: 290.39114 +[RESULT]: Val. Epoch: 25, summary_loss: 0.71861, final_score: 0.33666, time: 24.04264 + +2021-06-26T08:58:37.747010 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 26, summary_loss: 0.57855, final_score: 0.29293, time: 288.30276 +[RESULT]: Val. Epoch: 26, summary_loss: 0.64103, final_score: 0.31868, time: 24.97516 + +2021-06-26T09:03:51.202745 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 27, summary_loss: 0.57573, final_score: 0.29518, time: 288.63282 +[RESULT]: Val. Epoch: 27, summary_loss: 0.65663, final_score: 0.32168, time: 24.26863 + +2021-06-26T09:09:04.296806 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 28, summary_loss: 0.57196, final_score: 0.29605, time: 288.92252 +[RESULT]: Val. Epoch: 28, summary_loss: 0.62509, final_score: 0.31469, time: 24.00353 + +2021-06-26T09:14:17.414020 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 29, summary_loss: 0.56679, final_score: 0.28843, time: 288.38598 +[RESULT]: Val. Epoch: 29, summary_loss: 0.63100, final_score: 0.30969, time: 24.37561 + +2021-06-26T09:19:30.347516 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 30, summary_loss: 0.56538, final_score: 0.28818, time: 288.48957 +[RESULT]: Val. Epoch: 30, summary_loss: 0.65272, final_score: 0.32368, time: 25.17458 + +2021-06-26T09:24:44.190876 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.56446, final_score: 0.28343, time: 288.66005 +[RESULT]: Val. Epoch: 31, summary_loss: 0.62100, final_score: 0.31319, time: 26.02526 + +2021-06-26T09:29:59.037249 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.55936, final_score: 0.27956, time: 289.36662 +[RESULT]: Val. Epoch: 32, summary_loss: 0.65219, final_score: 0.30869, time: 25.58507 + +2021-06-26T09:35:14.162854 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.55494, final_score: 0.28168, time: 288.63822 +[RESULT]: Val. Epoch: 33, summary_loss: 0.66529, final_score: 0.31219, time: 25.56809 + +2021-06-26T09:40:28.539891 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 34, summary_loss: 0.55653, final_score: 0.28005, time: 288.32584 +[RESULT]: Val. Epoch: 34, summary_loss: 0.63708, final_score: 0.30769, time: 24.79344 + +2021-06-26T09:45:41.814405 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 35, summary_loss: 0.55466, final_score: 0.27806, time: 288.88304 +[RESULT]: Val. Epoch: 35, summary_loss: 0.76923, final_score: 0.31818, time: 25.99315 + +2021-06-26T09:50:56.857111 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 36, summary_loss: 0.55165, final_score: 0.27506, time: 288.76505 +[RESULT]: Val. Epoch: 36, summary_loss: 0.60886, final_score: 0.29870, time: 26.09736 + +2021-06-26T09:56:11.881444 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.54506, final_score: 0.26931, time: 288.44022 +[RESULT]: Val. Epoch: 37, summary_loss: 0.67431, final_score: 0.30769, time: 26.64926 + +2021-06-26T10:01:27.128952 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 38, summary_loss: 0.54657, final_score: 0.27256, time: 288.83869 +[RESULT]: Val. Epoch: 38, summary_loss: 0.70606, final_score: 0.30769, time: 24.95013 + +2021-06-26T10:06:41.073360 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 39, summary_loss: 0.54282, final_score: 0.26981, time: 288.51576 +[RESULT]: Val. Epoch: 39, summary_loss: 0.66947, final_score: 0.30470, time: 26.80444 + +2021-06-26T10:11:56.561592 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 40, summary_loss: 0.54038, final_score: 0.26606, time: 288.84403 +[RESULT]: Val. Epoch: 40, summary_loss: 0.67522, final_score: 0.30270, time: 26.73357 + +2021-06-26T10:17:12.291081 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 41, summary_loss: 0.53677, final_score: 0.25981, time: 289.35638 +[RESULT]: Val. Epoch: 41, summary_loss: 0.63719, final_score: 0.29520, time: 25.40404 + +2021-06-26T10:22:27.207270 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 42, summary_loss: 0.53658, final_score: 0.26456, time: 289.14606 +[RESULT]: Val. Epoch: 42, summary_loss: 0.70938, final_score: 0.31868, time: 25.76129 + +2021-06-26T10:27:42.303903 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 43, summary_loss: 0.52691, final_score: 0.25656, time: 288.31115 +[RESULT]: Val. Epoch: 43, summary_loss: 0.65800, final_score: 0.30470, time: 26.23945 + +2021-06-26T10:32:57.028276 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 44, summary_loss: 0.52296, final_score: 0.25106, time: 288.82872 +[RESULT]: Val. Epoch: 44, summary_loss: 0.67882, final_score: 0.29620, time: 26.20563 + +2021-06-26T10:38:12.236349 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 45, summary_loss: 0.51558, final_score: 0.24494, time: 288.39281 +[RESULT]: Val. Epoch: 45, summary_loss: 0.61709, final_score: 0.27722, time: 25.78885 + +2021-06-26T10:43:26.610369 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.51593, final_score: 0.24281, time: 288.84720 +[RESULT]: Val. Epoch: 46, summary_loss: 0.62719, final_score: 0.28422, time: 26.19072 + +2021-06-26T10:48:41.809155 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.50872, final_score: 0.24094, time: 288.54682 +[RESULT]: Val. Epoch: 47, summary_loss: 0.64387, final_score: 0.29021, time: 25.89935 + +2021-06-26T10:53:56.422057 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.51042, final_score: 0.24381, time: 288.64769 +[RESULT]: Val. Epoch: 48, summary_loss: 0.62992, final_score: 0.28971, time: 26.73910 + +2021-06-26T10:59:11.968904 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.51437, final_score: 0.24456, time: 290.50412 +[RESULT]: Val. Epoch: 49, summary_loss: 0.73169, final_score: 0.30170, time: 25.97064 + +2021-06-26T11:04:28.611627 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.50824, final_score: 0.24144, time: 288.53379 +[RESULT]: Val. Epoch: 50, summary_loss: 0.75939, final_score: 0.30569, time: 24.64775 + +2021-06-26T11:09:41.963148 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.50970, final_score: 0.24356, time: 288.75376 +[RESULT]: Val. Epoch: 51, summary_loss: 0.66159, final_score: 0.29371, time: 25.01791 + +2021-06-26T11:14:55.898812 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.50877, final_score: 0.24344, time: 289.02399 +[RESULT]: Val. Epoch: 52, summary_loss: 0.63309, final_score: 0.28472, time: 25.60560 + +2021-06-26T11:20:10.716645 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.50465, final_score: 0.23569, time: 289.00216 +[RESULT]: Val. Epoch: 53, summary_loss: 0.64282, final_score: 0.28671, time: 25.23739 + +2021-06-26T11:25:25.134448 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.50617, final_score: 0.23982, time: 288.83170 +[RESULT]: Val. Epoch: 54, summary_loss: 0.66310, final_score: 0.29121, time: 24.51194 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..7d972797503db00ce42b99b0a3c78f7a739e9e8a Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-037epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-037epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c40eb789b2ea388f0a522761eee23a8ceedecc9a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-037epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:297de7f2b6a2068ac7799780473b5ca973f85a0e8594235ab7a2183db2270d07 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-050epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-050epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..5b7535f9cf92e7d8342c0d3b3261590ffa5adf51 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-050epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:786f35e785f381ea5dd84fa3b6cdb1eb5f3e0ffcb0fbf16baa2fb4b6dc9b4d29 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-053epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-053epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..075256a1d87c83da0b0f498ae225c6954c83a163 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/best-checkpoint-053epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:511cf03e098fbeed17c1c0b6b3c45a3ede12883e6294826e274d14f6cecaf20d +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..8556f16da87c8a395a220bd232f084c6806dcd42 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cbaf29a304bb693cd05b3f4ae81d07a02f6021f31067511653a31b857fa93130 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..bbad9d1347f4b8f132d3199e68943a872c5126a2 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_3/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T17:48:11.636763 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69746, final_score: 0.49825, time: 291.94513 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.49600, time: 25.42104 + +2021-06-25T17:53:29.361689 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69315, final_score: 0.49688, time: 289.00746 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69314, final_score: 0.49550, time: 26.24294 + +2021-06-25T17:58:45.013365 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69316, final_score: 0.49688, time: 288.76408 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69320, final_score: 0.49500, time: 25.51897 + +2021-06-25T18:03:59.487362 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69314, final_score: 0.49263, time: 289.29428 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69308, final_score: 0.48851, time: 25.37411 + +2021-06-25T18:09:14.521479 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.65720, final_score: 0.39440, time: 288.77914 +[RESULT]: Val. Epoch: 4, summary_loss: 1.03556, final_score: 0.40709, time: 25.69881 + +2021-06-25T18:14:29.189520 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.57341, final_score: 0.27518, time: 288.64303 +[RESULT]: Val. Epoch: 5, summary_loss: 1.08173, final_score: 0.33816, time: 25.61916 + +2021-06-25T18:19:43.637312 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.52046, final_score: 0.23357, time: 289.66893 +[RESULT]: Val. Epoch: 6, summary_loss: 0.54046, final_score: 0.21728, time: 26.61799 + +2021-06-25T18:25:00.288410 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.49936, final_score: 0.21432, time: 288.69589 +[RESULT]: Val. Epoch: 7, summary_loss: 0.64092, final_score: 0.23726, time: 25.57025 + +2021-06-25T18:30:14.762206 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.48851, final_score: 0.20857, time: 289.05702 +[RESULT]: Val. Epoch: 8, summary_loss: 0.55174, final_score: 0.19630, time: 26.40599 + +2021-06-25T18:35:30.400012 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.46669, final_score: 0.18920, time: 289.21946 +[RESULT]: Val. Epoch: 9, summary_loss: 0.50671, final_score: 0.18581, time: 25.86880 + +2021-06-25T18:40:45.856201 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.45261, final_score: 0.18645, time: 288.91077 +[RESULT]: Val. Epoch: 10, summary_loss: 0.71702, final_score: 0.23377, time: 25.50982 + +2021-06-25T18:46:00.453523 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.44764, final_score: 0.17908, time: 288.85661 +[RESULT]: Val. Epoch: 11, summary_loss: 0.46593, final_score: 0.16484, time: 24.83850 + +2021-06-25T18:51:14.464023 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.43535, final_score: 0.17046, time: 288.95731 +[RESULT]: Val. Epoch: 12, summary_loss: 0.98075, final_score: 0.25674, time: 24.94680 + +2021-06-25T18:56:28.564543 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.43479, final_score: 0.16746, time: 289.05475 +[RESULT]: Val. Epoch: 13, summary_loss: 0.66871, final_score: 0.20130, time: 24.43527 + +2021-06-25T19:01:42.230715 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.42354, final_score: 0.16171, time: 288.99014 +[RESULT]: Val. Epoch: 14, summary_loss: 0.85356, final_score: 0.25225, time: 25.81189 + +2021-06-25T19:06:57.183507 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.42051, final_score: 0.16171, time: 288.77890 +[RESULT]: Val. Epoch: 15, summary_loss: 1.54129, final_score: 0.30420, time: 25.46503 + +2021-06-25T19:12:11.587251 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.41703, final_score: 0.15696, time: 289.24333 +[RESULT]: Val. Epoch: 16, summary_loss: 0.58134, final_score: 0.16633, time: 25.67546 + +2021-06-25T19:17:26.665643 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.40523, final_score: 0.14521, time: 288.78958 +[RESULT]: Val. Epoch: 17, summary_loss: 0.49341, final_score: 0.18082, time: 25.17928 + +2021-06-25T19:22:40.796240 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.40218, final_score: 0.14834, time: 289.08124 +[RESULT]: Val. Epoch: 18, summary_loss: 0.49564, final_score: 0.16434, time: 25.85758 + +2021-06-25T19:27:55.891828 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.39514, final_score: 0.14609, time: 288.78096 +[RESULT]: Val. Epoch: 19, summary_loss: 0.60902, final_score: 0.18482, time: 26.17722 + +2021-06-25T19:33:11.010075 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.37681, final_score: 0.12959, time: 289.31677 +[RESULT]: Val. Epoch: 20, summary_loss: 0.50790, final_score: 0.16034, time: 25.03281 + +2021-06-25T19:38:25.511559 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.37470, final_score: 0.13372, time: 288.86358 +[RESULT]: Val. Epoch: 21, summary_loss: 0.57948, final_score: 0.16484, time: 25.13630 + +2021-06-25T19:43:39.676116 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.36491, final_score: 0.12047, time: 289.11972 +[RESULT]: Val. Epoch: 22, summary_loss: 0.41114, final_score: 0.14136, time: 24.85088 + +2021-06-25T19:48:53.978536 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.35590, final_score: 0.11997, time: 289.29306 +[RESULT]: Val. Epoch: 23, summary_loss: 0.83401, final_score: 0.21179, time: 25.85043 + +2021-06-25T19:54:09.282467 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.35907, final_score: 0.11722, time: 288.92390 +[RESULT]: Val. Epoch: 24, summary_loss: 0.47862, final_score: 0.15285, time: 24.63896 + +2021-06-25T19:59:23.003379 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.35271, final_score: 0.11560, time: 289.01366 +[RESULT]: Val. Epoch: 25, summary_loss: 0.41410, final_score: 0.13536, time: 25.37052 + +2021-06-25T20:04:37.577076 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.35196, final_score: 0.11460, time: 289.02023 +[RESULT]: Val. Epoch: 26, summary_loss: 0.41212, final_score: 0.13337, time: 24.96239 + +2021-06-25T20:09:51.718868 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.34436, final_score: 0.10985, time: 288.97766 +[RESULT]: Val. Epoch: 27, summary_loss: 0.40804, final_score: 0.13337, time: 26.11494 + +2021-06-25T20:15:07.144715 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.34554, final_score: 0.11172, time: 289.15877 +[RESULT]: Val. Epoch: 28, summary_loss: 0.41870, final_score: 0.13387, time: 25.72692 + +2021-06-25T20:20:22.208468 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.34349, final_score: 0.10897, time: 288.59982 +[RESULT]: Val. Epoch: 29, summary_loss: 0.41448, final_score: 0.13237, time: 24.90283 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:12.539451 +LR: 0.00025 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 30, summary_loss: 0.45483, final_score: 0.18958, time: 290.49948 +[RESULT]: Val. Epoch: 30, summary_loss: 0.51610, final_score: 0.21878, time: 25.30877 + +2021-06-26T08:58:28.522650 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.44388, final_score: 0.18283, time: 288.74801 +[RESULT]: Val. Epoch: 31, summary_loss: 0.49123, final_score: 0.19830, time: 24.73262 + +2021-06-26T09:03:42.355810 +LR: 0.00025 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 32, summary_loss: 0.43539, final_score: 0.17946, time: 289.03029 +[RESULT]: Val. Epoch: 32, summary_loss: 0.64339, final_score: 0.22677, time: 24.68512 + +2021-06-26T09:08:56.241870 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.43299, final_score: 0.17583, time: 289.23808 +[RESULT]: Val. Epoch: 33, summary_loss: 0.48417, final_score: 0.19580, time: 24.67748 + +2021-06-26T09:14:10.540124 +LR: 0.00025 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 34, summary_loss: 0.41869, final_score: 0.16396, time: 289.56248 +[RESULT]: Val. Epoch: 34, summary_loss: 0.60080, final_score: 0.22078, time: 25.96087 + +2021-06-26T09:19:26.230036 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.42269, final_score: 0.16821, time: 289.46693 +[RESULT]: Val. Epoch: 35, summary_loss: 0.47907, final_score: 0.18681, time: 26.04769 + +2021-06-26T09:24:42.075746 +LR: 0.00025 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.41108, final_score: 0.16008, time: 288.87167 +[RESULT]: Val. Epoch: 36, summary_loss: 0.47296, final_score: 0.18082, time: 26.32358 + +2021-06-26T09:29:57.605026 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.40791, final_score: 0.15871, time: 288.83418 +[RESULT]: Val. Epoch: 37, summary_loss: 0.45774, final_score: 0.18282, time: 25.08118 + +2021-06-26T09:35:11.841286 +LR: 0.00025 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.40627, final_score: 0.15696, time: 289.22283 +[RESULT]: Val. Epoch: 38, summary_loss: 0.48007, final_score: 0.18332, time: 26.57276 + +2021-06-26T09:40:27.789585 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.40102, final_score: 0.15484, time: 289.80519 +[RESULT]: Val. Epoch: 39, summary_loss: 0.51863, final_score: 0.18631, time: 25.27951 + +2021-06-26T09:45:43.035066 +LR: 0.00025 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.39183, final_score: 0.14559, time: 288.80940 +[RESULT]: Val. Epoch: 40, summary_loss: 0.49778, final_score: 0.18981, time: 25.42358 + +2021-06-26T09:50:57.445365 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.39209, final_score: 0.14596, time: 289.63610 +[RESULT]: Val. Epoch: 41, summary_loss: 0.62237, final_score: 0.19630, time: 26.79217 + +2021-06-26T09:56:14.030058 +LR: 0.00025 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 42, summary_loss: 0.39368, final_score: 0.14546, time: 289.30573 +[RESULT]: Val. Epoch: 42, summary_loss: 0.45806, final_score: 0.18232, time: 25.87332 + +2021-06-26T10:01:29.417419 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.38153, final_score: 0.13947, time: 288.92187 +[RESULT]: Val. Epoch: 43, summary_loss: 0.46354, final_score: 0.17682, time: 27.01325 + +2021-06-26T10:06:45.523267 +LR: 0.00025 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 44, summary_loss: 0.37763, final_score: 0.13547, time: 288.91438 +[RESULT]: Val. Epoch: 44, summary_loss: 0.49720, final_score: 0.18032, time: 26.61985 + +2021-06-26T10:12:01.222989 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.37597, final_score: 0.13047, time: 288.85780 +[RESULT]: Val. Epoch: 45, summary_loss: 0.47681, final_score: 0.17183, time: 26.33811 + +2021-06-26T10:17:16.579769 +LR: 0.00025 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 46, summary_loss: 0.37447, final_score: 0.13384, time: 289.56753 +[RESULT]: Val. Epoch: 46, summary_loss: 0.45977, final_score: 0.16484, time: 26.08859 + +2021-06-26T10:22:32.413597 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.36938, final_score: 0.12934, time: 289.56224 +[RESULT]: Val. Epoch: 47, summary_loss: 0.52719, final_score: 0.17433, time: 26.13771 + +2021-06-26T10:27:48.301672 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.36690, final_score: 0.13209, time: 289.37205 +[RESULT]: Val. Epoch: 48, summary_loss: 0.47657, final_score: 0.16484, time: 25.68566 + +2021-06-26T10:33:03.535665 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.35228, final_score: 0.11960, time: 289.13164 +[RESULT]: Val. Epoch: 49, summary_loss: 0.55034, final_score: 0.18581, time: 25.05629 + +2021-06-26T10:38:17.893056 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.35351, final_score: 0.11722, time: 288.99634 +[RESULT]: Val. Epoch: 50, summary_loss: 0.43094, final_score: 0.15185, time: 25.92185 + +2021-06-26T10:43:33.162627 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.34212, final_score: 0.11210, time: 289.44773 +[RESULT]: Val. Epoch: 51, summary_loss: 0.51672, final_score: 0.17033, time: 26.26450 + +2021-06-26T10:48:49.102311 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.34523, final_score: 0.11097, time: 289.91516 +[RESULT]: Val. Epoch: 52, summary_loss: 0.44896, final_score: 0.15984, time: 26.34780 + +2021-06-26T10:54:05.531060 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.33860, final_score: 0.11035, time: 289.18889 +[RESULT]: Val. Epoch: 53, summary_loss: 0.42455, final_score: 0.14935, time: 26.07578 + +2021-06-26T10:59:21.173754 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.33733, final_score: 0.10822, time: 288.71290 +[RESULT]: Val. Epoch: 54, summary_loss: 0.42903, final_score: 0.15185, time: 25.79776 + +2021-06-26T11:04:35.867871 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.33453, final_score: 0.10797, time: 289.49450 +[RESULT]: Val. Epoch: 55, summary_loss: 0.43803, final_score: 0.15534, time: 26.84624 + +2021-06-26T11:09:52.367090 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.33703, final_score: 0.10810, time: 289.03393 +[RESULT]: Val. Epoch: 56, summary_loss: 0.44328, final_score: 0.15135, time: 26.18859 + +2021-06-26T11:15:07.776962 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.33256, final_score: 0.10647, time: 288.68396 +[RESULT]: Val. Epoch: 57, summary_loss: 0.43079, final_score: 0.14935, time: 25.68997 + +2021-06-26T11:20:22.320454 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.33049, final_score: 0.10685, time: 289.46764 +[RESULT]: Val. Epoch: 58, summary_loss: 0.43370, final_score: 0.15235, time: 27.37393 + +2021-06-26T11:25:39.359641 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.32597, final_score: 0.09985, time: 289.05511 +[RESULT]: Val. Epoch: 59, summary_loss: 0.42946, final_score: 0.14685, time: 25.65280 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..d137eb79c76777105bede4347672812aab373ab0 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-052epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-052epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..227ca65b82b228031310eb4cddcaf303d2d35d6f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-052epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:05587c8e264e71ebab6e7fc251a077d86d5e2ecc7509383be407135a1383fd6c +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-053epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-053epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..06560eb273ff09fc9d2f3c1de397f69f61cbdf6c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-053epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3ac2e484a4d0c1788f2a7230a716b4f5da35fab4a8a7cd54b8f2c4cddf67d096 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-054epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-054epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..2d384b56b014e8e4a618ddc7429dfbc382ac3dc4 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/best-checkpoint-054epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fb7f6a4f84f80b7306002a8d245775bf0a19d350accd0148019df6ece125ecf4 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..7ef1796b39329a34412fe4af55ad6915fc81873d --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4ddead55e32e0c1ca58c4973514c3d1480ef98d79d4a8ab0a9a9f95afd12952c +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..1c02be828836fb167285d1b2ed882cca8659694b --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_4/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T17:47:55.759315 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69743, final_score: 0.49750, time: 294.13639 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69316, final_score: 0.49550, time: 25.15020 + +2021-06-25T17:53:15.383849 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69314, final_score: 0.49625, time: 289.81060 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69314, final_score: 0.49401, time: 26.19676 + +2021-06-25T17:58:31.788025 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69315, final_score: 0.49588, time: 288.82275 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69318, final_score: 0.49301, time: 25.58069 + +2021-06-25T18:03:46.364882 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69368, final_score: 0.49788, time: 288.70381 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69317, final_score: 0.49700, time: 26.07359 + +2021-06-25T18:09:01.326264 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69315, final_score: 0.49838, time: 288.58870 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69340, final_score: 0.49650, time: 25.54838 + +2021-06-25T18:14:15.696831 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69321, final_score: 0.49838, time: 288.70958 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69738, final_score: 0.49800, time: 25.63989 + +2021-06-25T18:19:30.230909 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69321, final_score: 0.49838, time: 288.94842 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69315, final_score: 0.49600, time: 25.29542 + +2021-06-25T18:24:44.650925 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69315, final_score: 0.49750, time: 288.32199 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69314, final_score: 0.49451, time: 25.28877 + +2021-06-25T18:29:58.430540 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69316, final_score: 0.49688, time: 288.61758 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69314, final_score: 0.49351, time: 25.15136 + +2021-06-25T18:35:12.617108 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69334, final_score: 0.49800, time: 288.76409 +[RESULT]: Val. Epoch: 9, summary_loss: 0.69315, final_score: 0.49650, time: 24.70693 + +2021-06-25T18:40:26.262718 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69315, final_score: 0.49513, time: 288.34278 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69308, final_score: 0.48102, time: 24.99325 + +2021-06-25T18:45:39.946435 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69442, final_score: 0.49850, time: 288.62335 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69318, final_score: 0.49600, time: 25.05566 + +2021-06-25T18:50:53.823413 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69315, final_score: 0.49800, time: 288.55046 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69314, final_score: 0.49451, time: 24.68703 + +2021-06-25T18:56:07.218714 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69314, final_score: 0.49675, time: 289.26669 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69314, final_score: 0.49401, time: 24.77699 + +2021-06-25T19:01:21.434463 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69307, final_score: 0.49275, time: 289.13870 +[RESULT]: Val. Epoch: 14, summary_loss: 0.69312, final_score: 0.48801, time: 24.50391 + +2021-06-25T19:06:35.259828 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69320, final_score: 0.48688, time: 288.80267 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69370, final_score: 0.49201, time: 24.87809 + +2021-06-25T19:11:49.129499 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69263, final_score: 0.47951, time: 288.51060 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69259, final_score: 0.47003, time: 24.92324 + +2021-06-25T19:17:02.922226 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69166, final_score: 0.47538, time: 289.28744 +[RESULT]: Val. Epoch: 17, summary_loss: 0.70587, final_score: 0.46953, time: 25.16020 + +2021-06-25T19:22:17.546981 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.68832, final_score: 0.45514, time: 288.88021 +[RESULT]: Val. Epoch: 18, summary_loss: 0.68891, final_score: 0.44406, time: 24.99198 + +2021-06-25T19:27:31.751516 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.68266, final_score: 0.43077, time: 289.10099 +[RESULT]: Val. Epoch: 19, summary_loss: 0.81667, final_score: 0.45654, time: 24.59648 + +2021-06-25T19:32:45.644267 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.66668, final_score: 0.39465, time: 288.79111 +[RESULT]: Val. Epoch: 20, summary_loss: 0.70594, final_score: 0.38511, time: 24.51054 + +2021-06-25T19:37:59.102792 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.63495, final_score: 0.34104, time: 289.49799 +[RESULT]: Val. Epoch: 21, summary_loss: 0.71303, final_score: 0.32967, time: 24.96357 + +2021-06-25T19:43:13.757634 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.61633, final_score: 0.32154, time: 288.61598 +[RESULT]: Val. Epoch: 22, summary_loss: 0.69451, final_score: 0.31718, time: 25.07955 + +2021-06-25T19:48:27.627924 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.59319, final_score: 0.29755, time: 288.73115 +[RESULT]: Val. Epoch: 23, summary_loss: 0.59847, final_score: 0.29720, time: 24.85407 + +2021-06-25T19:53:41.561179 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.58075, final_score: 0.28205, time: 288.84167 +[RESULT]: Val. Epoch: 24, summary_loss: 0.59255, final_score: 0.28422, time: 24.15536 + +2021-06-25T19:58:54.902664 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.57349, final_score: 0.27593, time: 288.77771 +[RESULT]: Val. Epoch: 25, summary_loss: 0.59148, final_score: 0.27722, time: 24.43550 + +2021-06-25T20:04:08.449292 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.57320, final_score: 0.27481, time: 288.95619 +[RESULT]: Val. Epoch: 26, summary_loss: 0.67754, final_score: 0.28621, time: 24.85486 + +2021-06-25T20:09:22.457333 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.56692, final_score: 0.26706, time: 288.88524 +[RESULT]: Val. Epoch: 27, summary_loss: 0.64685, final_score: 0.29820, time: 24.37432 + +2021-06-25T20:14:35.875432 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.55721, final_score: 0.26068, time: 288.50141 +[RESULT]: Val. Epoch: 28, summary_loss: 0.62479, final_score: 0.27572, time: 24.90933 + +2021-06-25T20:19:49.478506 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.55260, final_score: 0.25906, time: 289.24005 +[RESULT]: Val. Epoch: 29, summary_loss: 0.60665, final_score: 0.26573, time: 23.94477 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:23.216931 +LR: 0.000125 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 29, summary_loss: 0.57501, final_score: 0.29055, time: 301.94857 +[RESULT]: Val. Epoch: 29, summary_loss: 0.64269, final_score: 0.29620, time: 24.70968 + +2021-06-26T08:58:50.048916 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 30, summary_loss: 0.56986, final_score: 0.28205, time: 302.31716 +[RESULT]: Val. Epoch: 30, summary_loss: 0.61107, final_score: 0.29171, time: 26.08241 + +2021-06-26T09:04:18.599554 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.56563, final_score: 0.27906, time: 302.38380 +[RESULT]: Val. Epoch: 31, summary_loss: 0.59122, final_score: 0.28372, time: 25.66632 + +2021-06-26T09:09:46.816891 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 32, summary_loss: 0.56085, final_score: 0.27368, time: 301.95629 +[RESULT]: Val. Epoch: 32, summary_loss: 0.59814, final_score: 0.28771, time: 24.89875 + +2021-06-26T09:15:13.823685 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.55501, final_score: 0.26631, time: 302.06615 +[RESULT]: Val. Epoch: 33, summary_loss: 0.57329, final_score: 0.27922, time: 26.26239 + +2021-06-26T09:20:42.316202 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.54983, final_score: 0.26831, time: 302.10382 +[RESULT]: Val. Epoch: 34, summary_loss: 0.59127, final_score: 0.28072, time: 24.25232 + +2021-06-26T09:26:08.834099 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.55088, final_score: 0.26431, time: 300.99150 +[RESULT]: Val. Epoch: 35, summary_loss: 0.57447, final_score: 0.27273, time: 25.24451 + +2021-06-26T09:31:35.225527 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.53949, final_score: 0.25756, time: 302.10183 +[RESULT]: Val. Epoch: 36, summary_loss: 0.59134, final_score: 0.26773, time: 24.89416 + +2021-06-26T09:37:02.390361 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.53792, final_score: 0.25456, time: 301.04548 +[RESULT]: Val. Epoch: 37, summary_loss: 0.56699, final_score: 0.26673, time: 24.80575 + +2021-06-26T09:42:28.689390 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 38, summary_loss: 0.53559, final_score: 0.24881, time: 301.64944 +[RESULT]: Val. Epoch: 38, summary_loss: 0.58481, final_score: 0.25774, time: 25.72928 + +2021-06-26T09:47:56.231405 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.53079, final_score: 0.25081, time: 302.21279 +[RESULT]: Val. Epoch: 39, summary_loss: 0.55965, final_score: 0.26374, time: 25.98517 + +2021-06-26T09:53:24.751261 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.53202, final_score: 0.24881, time: 302.70408 +[RESULT]: Val. Epoch: 40, summary_loss: 0.60512, final_score: 0.26474, time: 25.80433 + +2021-06-26T09:58:53.416605 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.52633, final_score: 0.24894, time: 301.80772 +[RESULT]: Val. Epoch: 41, summary_loss: 0.56188, final_score: 0.26224, time: 25.22810 + +2021-06-26T10:04:20.637125 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 42, summary_loss: 0.52224, final_score: 0.24206, time: 301.75259 +[RESULT]: Val. Epoch: 42, summary_loss: 0.61748, final_score: 0.25924, time: 25.66426 + +2021-06-26T10:09:48.209277 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.51927, final_score: 0.24044, time: 301.56811 +[RESULT]: Val. Epoch: 43, summary_loss: 0.60381, final_score: 0.26374, time: 25.78464 + +2021-06-26T10:15:15.732266 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 44, summary_loss: 0.51879, final_score: 0.23682, time: 302.63295 +[RESULT]: Val. Epoch: 44, summary_loss: 0.56282, final_score: 0.25225, time: 25.53359 + +2021-06-26T10:20:44.065442 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.51315, final_score: 0.23782, time: 302.83343 +[RESULT]: Val. Epoch: 45, summary_loss: 0.60766, final_score: 0.25475, time: 25.09474 + +2021-06-26T10:26:12.159766 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.51359, final_score: 0.23157, time: 301.98553 +[RESULT]: Val. Epoch: 46, summary_loss: 0.56027, final_score: 0.24476, time: 24.67714 + +2021-06-26T10:31:38.995211 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.51144, final_score: 0.22982, time: 302.07511 +[RESULT]: Val. Epoch: 47, summary_loss: 0.59659, final_score: 0.26873, time: 24.65615 + +2021-06-26T10:37:05.887591 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.50749, final_score: 0.22782, time: 302.37119 +[RESULT]: Val. Epoch: 48, summary_loss: 0.72042, final_score: 0.27473, time: 25.46674 + +2021-06-26T10:42:33.877434 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.50097, final_score: 0.22432, time: 302.48559 +[RESULT]: Val. Epoch: 49, summary_loss: 0.55133, final_score: 0.24326, time: 25.33759 + +2021-06-26T10:48:02.048320 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.49747, final_score: 0.22144, time: 302.86008 +[RESULT]: Val. Epoch: 50, summary_loss: 0.55025, final_score: 0.24476, time: 24.73691 + +2021-06-26T10:53:29.965336 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.49557, final_score: 0.22169, time: 302.31217 +[RESULT]: Val. Epoch: 51, summary_loss: 0.56537, final_score: 0.24376, time: 24.65539 + +2021-06-26T10:58:57.089397 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.49428, final_score: 0.21720, time: 301.86336 +[RESULT]: Val. Epoch: 52, summary_loss: 0.54205, final_score: 0.24675, time: 25.40771 + +2021-06-26T11:04:24.705014 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.49514, final_score: 0.22069, time: 303.48304 +[RESULT]: Val. Epoch: 53, summary_loss: 0.54168, final_score: 0.24326, time: 24.74567 + +2021-06-26T11:09:53.236039 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.49298, final_score: 0.21720, time: 301.87351 +[RESULT]: Val. Epoch: 54, summary_loss: 0.54005, final_score: 0.24476, time: 25.14737 + +2021-06-26T11:15:20.632266 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.49171, final_score: 0.21895, time: 302.88440 +[RESULT]: Val. Epoch: 55, summary_loss: 0.55456, final_score: 0.23776, time: 25.32581 + +2021-06-26T11:20:49.005424 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.48999, final_score: 0.21557, time: 302.63417 +[RESULT]: Val. Epoch: 56, summary_loss: 0.58346, final_score: 0.25025, time: 23.97911 + +2021-06-26T11:26:15.802864 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.48379, final_score: 0.21107, time: 302.09430 +[RESULT]: Val. Epoch: 57, summary_loss: 0.55889, final_score: 0.24026, time: 24.78404 + +2021-06-26T11:31:42.852403 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.48732, final_score: 0.21307, time: 302.96564 +[RESULT]: Val. Epoch: 58, summary_loss: 0.56626, final_score: 0.23876, time: 25.41841 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..06baccfa310e96bbd9629436de636d39bd967428 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..8ee7f3cb3a86d55914f4b7cd9fd7c9d0ad9d7478 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6e15aeaca3c0a841834e26128db123c4338aee979dca880ea5822d84bc6ba84c +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..6e95590ea82853d99101084beaeaff14e525f0ae --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:41ba74c528dbc1325e631e80d538558776a20504ca39a9982af616c85b13ac9f +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f3f4c750333555bc0b75c69ceef48318f398d6a1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:79c74d93dba487bf8e8fc9582a88b6c1b8c92b416edbf51815642197fe13e3f6 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..849bbfa63b15a926b1b18c7efaad6c12f090d6ae --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9bc4e26121fcbeec8a10b382a5e848f880bade6fa367187e1396a65f885baca1 +size 57505472 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..370475662c0cad221af917a5011b349f748f77b1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_srnet_stego_5/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T17:46:49.878062 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69644, final_score: 0.49838, time: 291.68530 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.49550, time: 24.87296 + +2021-06-25T17:52:06.775860 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69315, final_score: 0.49750, time: 289.82286 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69315, final_score: 0.49451, time: 24.04304 + +2021-06-25T17:57:20.799414 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69318, final_score: 0.49763, time: 289.46353 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69331, final_score: 0.49800, time: 24.66244 + +2021-06-25T18:02:35.118642 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69316, final_score: 0.49775, time: 289.00259 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69314, final_score: 0.49401, time: 25.29589 + +2021-06-25T18:07:49.762896 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69353, final_score: 0.49825, time: 289.42295 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69318, final_score: 0.49750, time: 24.90045 + +2021-06-25T18:13:04.247726 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69320, final_score: 0.49888, time: 289.11978 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69316, final_score: 0.49700, time: 25.75945 + +2021-06-25T18:18:19.293352 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69315, final_score: 0.49825, time: 289.48796 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69315, final_score: 0.49650, time: 24.32468 + +2021-06-25T18:23:33.266581 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69315, final_score: 0.49750, time: 289.93677 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69315, final_score: 0.49500, time: 24.70468 + +2021-06-25T18:28:48.062204 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69315, final_score: 0.49600, time: 289.43861 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69313, final_score: 0.49251, time: 24.56551 + +2021-06-25T18:34:02.481315 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69326, final_score: 0.49775, time: 289.42586 +[RESULT]: Val. Epoch: 9, summary_loss: 0.69348, final_score: 0.49700, time: 25.49248 + +2021-06-25T18:39:17.574146 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69327, final_score: 0.49800, time: 289.05777 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69317, final_score: 0.49600, time: 24.85239 + +2021-06-25T18:44:31.648935 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69318, final_score: 0.49713, time: 289.97413 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69314, final_score: 0.49351, time: 25.42905 + +2021-06-25T18:49:47.213755 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69312, final_score: 0.49363, time: 289.30718 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69316, final_score: 0.49201, time: 23.62546 + +2021-06-25T18:55:00.314396 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69327, final_score: 0.49613, time: 288.94148 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69314, final_score: 0.49451, time: 24.12914 + +2021-06-25T19:00:13.554158 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69311, final_score: 0.49300, time: 289.50296 +[RESULT]: Val. Epoch: 14, summary_loss: 0.69299, final_score: 0.48501, time: 24.60687 + +2021-06-25T19:05:28.004293 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69305, final_score: 0.48950, time: 289.97728 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69327, final_score: 0.48252, time: 24.61390 + +2021-06-25T19:10:42.750438 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69266, final_score: 0.48363, time: 290.54197 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69561, final_score: 0.49051, time: 25.20508 + +2021-06-25T19:15:58.673812 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69208, final_score: 0.47863, time: 289.51147 +[RESULT]: Val. Epoch: 17, summary_loss: 0.69714, final_score: 0.47952, time: 24.67629 + +2021-06-25T19:21:13.027093 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.69127, final_score: 0.47138, time: 289.29404 +[RESULT]: Val. Epoch: 18, summary_loss: 0.70194, final_score: 0.48202, time: 24.40080 + +2021-06-25T19:26:26.883162 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.68974, final_score: 0.46738, time: 289.26416 +[RESULT]: Val. Epoch: 19, summary_loss: 0.70994, final_score: 0.47303, time: 25.91382 + +2021-06-25T19:31:42.220892 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.68891, final_score: 0.46401, time: 289.57384 +[RESULT]: Val. Epoch: 20, summary_loss: 0.80961, final_score: 0.48501, time: 25.26493 + +2021-06-25T19:36:57.226941 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.68720, final_score: 0.45676, time: 289.82154 +[RESULT]: Val. Epoch: 21, summary_loss: 0.69563, final_score: 0.46204, time: 24.58968 + +2021-06-25T19:42:11.801086 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.68609, final_score: 0.45376, time: 290.35529 +[RESULT]: Val. Epoch: 22, summary_loss: 0.68946, final_score: 0.45105, time: 24.58167 + +2021-06-25T19:47:27.066793 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.68565, final_score: 0.44939, time: 289.69667 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69138, final_score: 0.44456, time: 24.72748 + +2021-06-25T19:52:41.641803 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.68539, final_score: 0.45064, time: 289.08125 +[RESULT]: Val. Epoch: 24, summary_loss: 0.68759, final_score: 0.44855, time: 24.83579 + +2021-06-25T19:57:55.898072 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.68413, final_score: 0.44364, time: 289.12540 +[RESULT]: Val. Epoch: 25, summary_loss: 0.79491, final_score: 0.47602, time: 24.97195 + +2021-06-25T20:03:10.158101 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.68391, final_score: 0.44601, time: 289.29464 +[RESULT]: Val. Epoch: 26, summary_loss: 0.70752, final_score: 0.45704, time: 24.11890 + +2021-06-25T20:08:23.737611 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.68231, final_score: 0.44226, time: 289.03410 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69898, final_score: 0.44755, time: 25.38748 + +2021-06-25T20:13:38.352537 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.68193, final_score: 0.43952, time: 289.76530 +[RESULT]: Val. Epoch: 28, summary_loss: 0.68819, final_score: 0.43656, time: 24.61196 + +2021-06-25T20:18:52.892030 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.68038, final_score: 0.43739, time: 289.72242 +[RESULT]: Val. Epoch: 29, summary_loss: 0.68673, final_score: 0.43806, time: 25.07666 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:23.041111 +LR: 0.000125 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 29, summary_loss: 0.68019, final_score: 0.44576, time: 310.72210 +[RESULT]: Val. Epoch: 29, summary_loss: 0.68838, final_score: 0.44555, time: 25.51249 + +2021-06-26T08:58:59.449026 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 30, summary_loss: 0.67787, final_score: 0.44201, time: 312.17457 +[RESULT]: Val. Epoch: 30, summary_loss: 0.70298, final_score: 0.43856, time: 25.50292 + +2021-06-26T09:04:37.303764 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.67616, final_score: 0.44264, time: 311.60425 +[RESULT]: Val. Epoch: 31, summary_loss: 0.68815, final_score: 0.44106, time: 26.39391 + +2021-06-26T09:10:15.481898 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 32, summary_loss: 0.67597, final_score: 0.43927, time: 313.06644 +[RESULT]: Val. Epoch: 32, summary_loss: 0.68966, final_score: 0.44056, time: 26.51779 + +2021-06-26T09:15:55.232568 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.67501, final_score: 0.43427, time: 312.94777 +[RESULT]: Val. Epoch: 33, summary_loss: 0.69066, final_score: 0.44256, time: 24.50148 + +2021-06-26T09:21:32.833680 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.67405, final_score: 0.43539, time: 311.94283 +[RESULT]: Val. Epoch: 34, summary_loss: 0.69422, final_score: 0.43107, time: 25.16791 + +2021-06-26T09:27:10.114388 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.67314, final_score: 0.43252, time: 312.22203 +[RESULT]: Val. Epoch: 35, summary_loss: 0.69867, final_score: 0.43856, time: 25.87427 + +2021-06-26T09:32:48.378944 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.67304, final_score: 0.42989, time: 312.98739 +[RESULT]: Val. Epoch: 36, summary_loss: 0.79289, final_score: 0.43556, time: 25.99306 + +2021-06-26T09:38:27.524366 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.67094, final_score: 0.42727, time: 312.90695 +[RESULT]: Val. Epoch: 37, summary_loss: 0.69000, final_score: 0.43357, time: 25.27120 + +2021-06-26T09:44:05.857805 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 38, summary_loss: 0.66905, final_score: 0.42364, time: 312.08114 +[RESULT]: Val. Epoch: 38, summary_loss: 0.69353, final_score: 0.42857, time: 25.96986 + +2021-06-26T09:49:44.074483 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.66592, final_score: 0.41765, time: 313.22106 +[RESULT]: Val. Epoch: 39, summary_loss: 0.71504, final_score: 0.43257, time: 24.90493 + +2021-06-26T09:55:22.375423 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.66370, final_score: 0.41740, time: 312.93754 +[RESULT]: Val. Epoch: 40, summary_loss: 0.67666, final_score: 0.42308, time: 25.72917 + +2021-06-26T10:01:01.213431 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.66427, final_score: 0.41502, time: 312.62907 +[RESULT]: Val. Epoch: 41, summary_loss: 0.67944, final_score: 0.42058, time: 24.25918 + +2021-06-26T10:06:38.284022 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 42, summary_loss: 0.66137, final_score: 0.41327, time: 312.52740 +[RESULT]: Val. Epoch: 42, summary_loss: 0.68736, final_score: 0.41459, time: 24.99468 + +2021-06-26T10:12:15.969879 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.66050, final_score: 0.41577, time: 312.08746 +[RESULT]: Val. Epoch: 43, summary_loss: 0.69516, final_score: 0.42208, time: 25.09857 + +2021-06-26T10:17:53.343812 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 44, summary_loss: 0.65860, final_score: 0.41215, time: 313.72018 +[RESULT]: Val. Epoch: 44, summary_loss: 0.75298, final_score: 0.41259, time: 25.33311 + +2021-06-26T10:23:32.560781 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.65443, final_score: 0.40902, time: 312.65746 +[RESULT]: Val. Epoch: 45, summary_loss: 0.70177, final_score: 0.41309, time: 25.05862 + +2021-06-26T10:29:10.448288 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 46, summary_loss: 0.65397, final_score: 0.40240, time: 312.74634 +[RESULT]: Val. Epoch: 46, summary_loss: 0.72997, final_score: 0.41658, time: 25.85567 + +2021-06-26T10:34:49.216155 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.65368, final_score: 0.40477, time: 312.51862 +[RESULT]: Val. Epoch: 47, summary_loss: 0.68400, final_score: 0.41608, time: 24.73775 + +2021-06-26T10:40:26.648374 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.65185, final_score: 0.40202, time: 312.66794 +[RESULT]: Val. Epoch: 48, summary_loss: 0.69154, final_score: 0.41259, time: 26.35328 + +2021-06-26T10:46:05.830964 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.65055, final_score: 0.40090, time: 313.14917 +[RESULT]: Val. Epoch: 49, summary_loss: 0.67420, final_score: 0.40859, time: 25.29118 + +2021-06-26T10:51:44.427813 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.64973, final_score: 0.39790, time: 312.96628 +[RESULT]: Val. Epoch: 50, summary_loss: 0.67872, final_score: 0.41209, time: 26.27276 + +2021-06-26T10:57:23.873610 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.64882, final_score: 0.39990, time: 313.42082 +[RESULT]: Val. Epoch: 51, summary_loss: 0.68126, final_score: 0.40659, time: 25.36232 + +2021-06-26T11:03:02.857135 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.64857, final_score: 0.40027, time: 313.54309 +[RESULT]: Val. Epoch: 52, summary_loss: 0.68300, final_score: 0.40609, time: 25.83679 + +2021-06-26T11:08:42.398129 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.65070, final_score: 0.40152, time: 313.34798 +[RESULT]: Val. Epoch: 53, summary_loss: 0.70059, final_score: 0.40909, time: 26.00179 + +2021-06-26T11:14:21.914301 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.64805, final_score: 0.39753, time: 313.38741 +[RESULT]: Val. Epoch: 54, summary_loss: 0.68293, final_score: 0.40709, time: 25.06577 + +2021-06-26T11:20:00.546673 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.64820, final_score: 0.39753, time: 312.76315 +[RESULT]: Val. Epoch: 55, summary_loss: 0.67397, final_score: 0.40360, time: 25.55777 + +2021-06-26T11:25:39.062853 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.64800, final_score: 0.40077, time: 311.95584 +[RESULT]: Val. Epoch: 56, summary_loss: 0.68046, final_score: 0.40460, time: 26.89759 + +2021-06-26T11:31:18.085384 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.64664, final_score: 0.39653, time: 312.56782 +[RESULT]: Val. Epoch: 57, summary_loss: 0.69756, final_score: 0.40959, time: 26.49057 + +2021-06-26T11:36:57.348535 +LR: 9.765625e-07 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.64775, final_score: 0.39390, time: 312.15015 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T17:46:27.330139 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69708, final_score: 0.49875, time: 289.68161 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.49600, time: 24.96695 + +2021-06-25T17:51:42.392539 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69316, final_score: 0.49825, time: 288.27674 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69319, final_score: 0.49650, time: 24.11795 + +2021-06-25T17:56:54.943358 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69319, final_score: 0.49775, time: 288.01891 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69336, final_score: 0.49750, time: 23.93105 + +2021-06-25T18:02:07.048952 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69321, final_score: 0.49813, time: 288.02662 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69315, final_score: 0.49600, time: 25.71682 + +2021-06-25T18:07:21.136256 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69316, final_score: 0.49738, time: 288.38762 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69320, final_score: 0.49650, time: 25.45180 + +2021-06-25T18:12:35.180922 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69319, final_score: 0.49775, time: 288.46017 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69316, final_score: 0.49650, time: 25.30085 + +2021-06-25T18:17:49.116543 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69344, final_score: 0.49850, time: 288.48466 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69316, final_score: 0.49700, time: 24.42381 + +2021-06-25T18:23:02.177677 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69316, final_score: 0.49825, time: 288.28411 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69317, final_score: 0.49700, time: 24.38853 + +2021-06-25T18:28:15.031421 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69325, final_score: 0.49825, time: 287.78465 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69315, final_score: 0.49650, time: 24.65695 + +2021-06-25T18:33:27.883995 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69317, final_score: 0.49775, time: 287.95655 +[RESULT]: Val. Epoch: 9, summary_loss: 0.69317, final_score: 0.49800, time: 24.27110 + +2021-06-25T18:38:40.262088 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69317, final_score: 0.49725, time: 288.50186 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69362, final_score: 0.49500, time: 23.19104 + +2021-06-25T18:43:52.145714 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69327, final_score: 0.49875, time: 287.72121 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69315, final_score: 0.49650, time: 25.02348 + +2021-06-25T18:49:05.093793 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69315, final_score: 0.49800, time: 287.71245 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69319, final_score: 0.49700, time: 24.12644 + +2021-06-25T18:54:17.091351 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69315, final_score: 0.49750, time: 288.77027 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69382, final_score: 0.49650, time: 24.12935 + +2021-06-25T18:59:30.158693 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69316, final_score: 0.49625, time: 287.67766 +[RESULT]: Val. Epoch: 14, summary_loss: 0.69342, final_score: 0.49600, time: 25.26725 + +2021-06-25T19:04:43.256872 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69397, final_score: 0.49838, time: 288.22744 +[RESULT]: Val. Epoch: 15, summary_loss: 0.69319, final_score: 0.49800, time: 24.25020 + +2021-06-25T19:09:55.892044 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69315, final_score: 0.49888, time: 288.43882 +[RESULT]: Val. Epoch: 16, summary_loss: 0.69315, final_score: 0.49700, time: 25.44599 + +2021-06-25T19:15:09.952039 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69315, final_score: 0.49863, time: 288.32462 +[RESULT]: Val. Epoch: 17, summary_loss: 0.69316, final_score: 0.49800, time: 24.88681 + +2021-06-25T19:20:23.345329 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.69327, final_score: 0.49875, time: 287.86797 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69315, final_score: 0.49800, time: 24.88504 + +2021-06-25T19:25:36.255583 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.69315, final_score: 0.49800, time: 288.52182 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69315, final_score: 0.49600, time: 23.90480 + +2021-06-25T19:30:48.850702 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.69315, final_score: 0.49788, time: 287.63780 +[RESULT]: Val. Epoch: 20, summary_loss: 0.69315, final_score: 0.49650, time: 24.04874 + +2021-06-25T19:36:00.717389 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.69315, final_score: 0.49825, time: 287.60920 +[RESULT]: Val. Epoch: 21, summary_loss: 0.69315, final_score: 0.49700, time: 24.23381 + +2021-06-25T19:41:12.742832 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.69315, final_score: 0.49813, time: 288.53724 +[RESULT]: Val. Epoch: 22, summary_loss: 0.69315, final_score: 0.49600, time: 24.08100 + +2021-06-25T19:46:25.707047 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.69315, final_score: 0.49775, time: 288.53011 +[RESULT]: Val. Epoch: 23, summary_loss: 0.69315, final_score: 0.49650, time: 23.80656 + +2021-06-25T19:51:38.382572 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.69315, final_score: 0.49788, time: 288.16412 +[RESULT]: Val. Epoch: 24, summary_loss: 0.69315, final_score: 0.49600, time: 24.34197 + +2021-06-25T19:56:51.080297 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.69314, final_score: 0.49750, time: 288.04389 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69315, final_score: 0.49550, time: 24.80998 + +2021-06-25T20:02:04.290457 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.69315, final_score: 0.49725, time: 288.06401 +[RESULT]: Val. Epoch: 26, summary_loss: 0.69315, final_score: 0.49650, time: 24.25134 + +2021-06-25T20:07:16.945613 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.69314, final_score: 0.49738, time: 287.65165 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69314, final_score: 0.49650, time: 24.77702 + +2021-06-25T20:12:29.709003 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.69314, final_score: 0.49738, time: 288.66296 +[RESULT]: Val. Epoch: 28, summary_loss: 0.69314, final_score: 0.49550, time: 25.17369 + +2021-06-25T20:17:43.730529 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.69314, final_score: 0.49725, time: 287.57325 +[RESULT]: Val. Epoch: 29, summary_loss: 0.69314, final_score: 0.49550, time: 23.97508 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:23.154397 +LR: 6.25e-05 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 30, summary_loss: 0.68040, final_score: 0.43914, time: 293.83106 +[RESULT]: Val. Epoch: 30, summary_loss: 0.69105, final_score: 0.43556, time: 24.52047 + +2021-06-26T08:58:41.680704 +LR: 6.25e-05 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.67754, final_score: 0.43952, time: 289.64027 +[RESULT]: Val. Epoch: 31, summary_loss: 0.69025, final_score: 0.43457, time: 24.52143 + +2021-06-26T09:03:56.009596 +LR: 6.25e-05 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 32, summary_loss: 0.67653, final_score: 0.43464, time: 289.54698 +[RESULT]: Val. Epoch: 32, summary_loss: 0.69829, final_score: 0.44006, time: 24.49855 + +2021-06-26T09:09:10.224989 +LR: 6.25e-05 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.67743, final_score: 0.43727, time: 290.36748 +[RESULT]: Val. Epoch: 33, summary_loss: 0.69216, final_score: 0.43656, time: 24.59436 + +2021-06-26T09:14:25.368839 +LR: 6.25e-05 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 34, summary_loss: 0.67592, final_score: 0.43552, time: 290.18189 +[RESULT]: Val. Epoch: 34, summary_loss: 0.70358, final_score: 0.43556, time: 25.08866 + +2021-06-26T09:19:40.797288 +LR: 6.25e-05 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.67570, final_score: 0.43264, time: 289.91381 +[RESULT]: Val. Epoch: 35, summary_loss: 0.69099, final_score: 0.43257, time: 24.39368 + +2021-06-26T09:24:55.305077 +LR: 6.25e-05 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.67508, final_score: 0.43302, time: 289.90709 +[RESULT]: Val. Epoch: 36, summary_loss: 0.70291, final_score: 0.43457, time: 24.27704 + +2021-06-26T09:30:09.638902 +LR: 6.25e-05 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.67604, final_score: 0.43502, time: 290.67546 +[RESULT]: Val. Epoch: 37, summary_loss: 0.69263, final_score: 0.43307, time: 24.50284 + +2021-06-26T09:35:24.989949 +LR: 6.25e-05 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.67461, final_score: 0.43114, time: 289.60655 +[RESULT]: Val. Epoch: 38, summary_loss: 0.69565, final_score: 0.43756, time: 24.39206 + +2021-06-26T09:40:39.156357 +LR: 6.25e-05 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.67450, final_score: 0.43064, time: 289.77961 +[RESULT]: Val. Epoch: 39, summary_loss: 0.72026, final_score: 0.44505, time: 24.72527 + +2021-06-26T09:45:53.814962 +LR: 6.25e-05 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.67311, final_score: 0.42789, time: 290.09189 +[RESULT]: Val. Epoch: 40, summary_loss: 0.69449, final_score: 0.43856, time: 23.99109 + +2021-06-26T09:51:08.054912 +LR: 6.25e-05 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.67306, final_score: 0.42877, time: 289.59982 +[RESULT]: Val. Epoch: 41, summary_loss: 0.68876, final_score: 0.43307, time: 24.68036 + +2021-06-26T09:56:22.499797 +LR: 6.25e-05 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 42, summary_loss: 0.67238, final_score: 0.42702, time: 289.56591 +[RESULT]: Val. Epoch: 42, summary_loss: 0.70058, final_score: 0.43307, time: 24.16224 + +2021-06-26T10:01:36.386136 +LR: 6.25e-05 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.67228, final_score: 0.42514, time: 290.01551 +[RESULT]: Val. Epoch: 43, summary_loss: 0.69612, final_score: 0.43606, time: 24.54584 + +2021-06-26T10:06:51.121276 +LR: 6.25e-05 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 44, summary_loss: 0.67212, final_score: 0.42689, time: 290.03731 +[RESULT]: Val. Epoch: 44, summary_loss: 0.68852, final_score: 0.43157, time: 24.39611 + +2021-06-26T10:12:05.741452 +LR: 6.25e-05 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.67114, final_score: 0.42502, time: 289.60545 +[RESULT]: Val. Epoch: 45, summary_loss: 0.70207, final_score: 0.43157, time: 24.10692 + +2021-06-26T10:17:19.606091 +LR: 6.25e-05 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 46, summary_loss: 0.67159, final_score: 0.42602, time: 290.00711 +[RESULT]: Val. Epoch: 46, summary_loss: 0.69763, final_score: 0.42807, time: 24.87703 + +2021-06-26T10:22:34.667040 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.67119, final_score: 0.41965, time: 290.39703 +[RESULT]: Val. Epoch: 47, summary_loss: 0.69223, final_score: 0.42907, time: 24.04299 + +2021-06-26T10:27:49.275716 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.66874, final_score: 0.41990, time: 289.31104 +[RESULT]: Val. Epoch: 48, summary_loss: 0.70329, final_score: 0.43606, time: 24.64867 + +2021-06-26T10:33:03.416260 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.66801, final_score: 0.41677, time: 290.19310 +[RESULT]: Val. Epoch: 49, summary_loss: 0.69389, final_score: 0.42557, time: 24.14543 + +2021-06-26T10:38:17.916626 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.66776, final_score: 0.42002, time: 290.30083 +[RESULT]: Val. Epoch: 50, summary_loss: 0.69201, final_score: 0.42757, time: 24.99131 + +2021-06-26T10:43:33.373500 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.66802, final_score: 0.42027, time: 289.90567 +[RESULT]: Val. Epoch: 51, summary_loss: 0.69143, final_score: 0.42408, time: 23.89436 + +2021-06-26T10:48:47.365886 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.66795, final_score: 0.41915, time: 289.74354 +[RESULT]: Val. Epoch: 52, summary_loss: 0.69491, final_score: 0.42258, time: 24.76724 + +2021-06-26T10:54:02.034749 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.66884, final_score: 0.41815, time: 289.50951 +[RESULT]: Val. Epoch: 53, summary_loss: 0.69178, final_score: 0.42208, time: 23.69208 + +2021-06-26T10:59:15.405095 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.66708, final_score: 0.41865, time: 289.40283 +[RESULT]: Val. Epoch: 54, summary_loss: 0.69091, final_score: 0.42258, time: 24.33643 + +2021-06-26T11:04:29.300721 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.66768, final_score: 0.41977, time: 289.86436 +[RESULT]: Val. Epoch: 55, summary_loss: 0.69491, final_score: 0.42957, time: 24.32310 + +2021-06-26T11:09:43.659767 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.66816, final_score: 0.41890, time: 289.38269 +[RESULT]: Val. Epoch: 56, summary_loss: 0.69735, final_score: 0.41808, time: 23.53825 + +2021-06-26T11:14:56.742731 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.66791, final_score: 0.41827, time: 290.60386 +[RESULT]: Val. Epoch: 57, summary_loss: 0.68987, final_score: 0.42158, time: 25.55060 + +2021-06-26T11:20:13.069353 +LR: 9.765625e-07 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.66790, final_score: 0.41402, time: 289.51180 +[RESULT]: Val. Epoch: 58, summary_loss: 0.69616, final_score: 0.43107, time: 24.27878 + +2021-06-26T11:25:27.029287 +LR: 9.765625e-07 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.66784, final_score: 0.41640, time: 289.93669 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T17:46:12.343305 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.69648, final_score: 0.49825, time: 292.17719 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69317, final_score: 0.49650, time: 25.99518 + +2021-06-25T17:51:30.917453 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69315, final_score: 0.49763, time: 289.75499 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69315, final_score: 0.49451, time: 26.55927 + +2021-06-25T17:56:47.630522 +LR: 0.001 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69316, final_score: 0.49750, time: 290.32649 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69316, final_score: 0.49550, time: 26.18510 + +2021-06-25T18:02:04.351520 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69322, final_score: 0.49725, time: 289.94486 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69537, final_score: 0.49800, time: 27.20191 + +2021-06-25T18:07:21.696229 +LR: 0.001 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69365, final_score: 0.49863, time: 289.71475 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69315, final_score: 0.49700, time: 26.46421 + +2021-06-25T18:12:38.294405 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69315, final_score: 0.49813, time: 289.66586 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69315, final_score: 0.49650, time: 26.26747 + +2021-06-25T18:17:54.432866 +LR: 0.001 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69315, final_score: 0.49763, time: 289.83635 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69315, final_score: 0.49550, time: 26.64166 + +2021-06-25T18:23:11.321062 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69314, final_score: 0.49588, time: 289.79730 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69314, final_score: 0.49351, time: 26.41756 + +2021-06-25T18:28:27.934093 +LR: 0.001 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69344, final_score: 0.49750, time: 289.75355 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69435, final_score: 0.49700, time: 27.32688 + +2021-06-25T18:33:45.227831 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69315, final_score: 0.49738, time: 290.01024 +[RESULT]: Val. Epoch: 9, summary_loss: 0.69316, final_score: 0.49600, time: 27.84318 + +2021-06-25T18:39:03.287547 +LR: 0.001 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69315, final_score: 0.49650, time: 290.02088 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69328, final_score: 0.49301, time: 26.76614 + +2021-06-25T18:44:20.269240 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 11, summary_loss: 0.69320, final_score: 0.49438, time: 290.36343 +[RESULT]: Val. Epoch: 11, summary_loss: 0.70783, final_score: 0.49451, time: 27.09935 + +2021-06-25T18:49:37.927532 +LR: 0.001 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 12, summary_loss: 0.69322, final_score: 0.49363, time: 290.39677 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69364, final_score: 0.49650, time: 26.06296 + +2021-06-25T18:54:54.589997 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 13, summary_loss: 0.69319, final_score: 0.49338, time: 289.85985 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69453, final_score: 0.49101, time: 26.50144 + +2021-06-25T19:00:11.143540 +LR: 0.001 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 14, summary_loss: 0.69278, final_score: 0.48400, time: 290.48120 +[RESULT]: Val. Epoch: 14, summary_loss: 0.70923, final_score: 0.49051, time: 27.32710 + +2021-06-25T19:05:29.145739 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 15, summary_loss: 0.69279, final_score: 0.48188, time: 290.34648 +[RESULT]: Val. Epoch: 15, summary_loss: 0.72934, final_score: 0.48452, time: 27.00842 + +2021-06-25T19:10:46.691846 +LR: 0.001 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 16, summary_loss: 0.69222, final_score: 0.47801, time: 290.62732 +[RESULT]: Val. Epoch: 16, summary_loss: 0.71577, final_score: 0.48202, time: 26.29042 + +2021-06-25T19:16:03.813876 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 17, summary_loss: 0.69152, final_score: 0.47063, time: 289.74300 +[RESULT]: Val. Epoch: 17, summary_loss: 0.72600, final_score: 0.47453, time: 26.64398 + +2021-06-25T19:21:20.427091 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 18, summary_loss: 0.69014, final_score: 0.46438, time: 290.34121 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69426, final_score: 0.46404, time: 26.56189 + +2021-06-25T19:26:37.538711 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 19, summary_loss: 0.68941, final_score: 0.45776, time: 290.36824 +[RESULT]: Val. Epoch: 19, summary_loss: 1.01435, final_score: 0.48452, time: 26.86901 + +2021-06-25T19:31:54.974317 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 20, summary_loss: 0.68805, final_score: 0.45614, time: 290.39433 +[RESULT]: Val. Epoch: 20, summary_loss: 0.68921, final_score: 0.44755, time: 26.98099 + +2021-06-25T19:37:12.776104 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.68628, final_score: 0.44451, time: 290.05708 +[RESULT]: Val. Epoch: 21, summary_loss: 0.70696, final_score: 0.45854, time: 27.25468 + +2021-06-25T19:42:30.284527 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.68538, final_score: 0.44201, time: 290.24966 +[RESULT]: Val. Epoch: 22, summary_loss: 0.73172, final_score: 0.45904, time: 26.35402 + +2021-06-25T19:47:47.077609 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.68164, final_score: 0.43564, time: 289.72865 +[RESULT]: Val. Epoch: 23, summary_loss: 0.68767, final_score: 0.43856, time: 26.98362 + +2021-06-25T19:53:04.206088 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.67906, final_score: 0.42977, time: 289.80881 +[RESULT]: Val. Epoch: 24, summary_loss: 0.70631, final_score: 0.44306, time: 27.91368 + +2021-06-25T19:58:22.122935 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.67811, final_score: 0.42914, time: 290.49617 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69279, final_score: 0.43107, time: 26.08681 + +2021-06-25T20:03:38.904502 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.67247, final_score: 0.41140, time: 290.11420 +[RESULT]: Val. Epoch: 26, summary_loss: 0.68666, final_score: 0.43107, time: 25.72232 + +2021-06-25T20:08:55.157922 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.67058, final_score: 0.41252, time: 289.86451 +[RESULT]: Val. Epoch: 27, summary_loss: 0.69909, final_score: 0.41658, time: 27.68244 + +2021-06-25T20:14:12.900400 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.66876, final_score: 0.40890, time: 290.47079 +[RESULT]: Val. Epoch: 28, summary_loss: 0.71388, final_score: 0.43257, time: 26.86514 + +2021-06-25T20:19:30.438733 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.66560, final_score: 0.40490, time: 289.89223 +[RESULT]: Val. Epoch: 29, summary_loss: 0.69313, final_score: 0.41259, time: 26.57602 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:53:23.173530 +LR: 0.000125 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 30, summary_loss: 0.67442, final_score: 0.42039, time: 293.81275 +[RESULT]: Val. Epoch: 30, summary_loss: 0.68414, final_score: 0.42358, time: 24.60329 + +2021-06-26T08:58:41.769891 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 31, summary_loss: 0.67158, final_score: 0.41365, time: 289.93254 +[RESULT]: Val. Epoch: 31, summary_loss: 0.68419, final_score: 0.42408, time: 24.59061 + +2021-06-26T09:03:56.464588 +LR: 0.000125 +Emb_rate: 0.9 +[RESULT]: Train. Epoch: 32, summary_loss: 0.67097, final_score: 0.41315, time: 289.50377 +[RESULT]: Val. Epoch: 32, summary_loss: 0.68766, final_score: 0.41708, time: 25.07673 + +2021-06-26T09:09:11.203084 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 33, summary_loss: 0.67053, final_score: 0.40977, time: 289.48119 +[RESULT]: Val. Epoch: 33, summary_loss: 0.68018, final_score: 0.42008, time: 24.77790 + +2021-06-26T09:14:25.621109 +LR: 0.000125 +Emb_rate: 0.81 +[RESULT]: Train. Epoch: 34, summary_loss: 0.66935, final_score: 0.40740, time: 289.50817 +[RESULT]: Val. Epoch: 34, summary_loss: 0.68040, final_score: 0.42008, time: 24.33404 + +2021-06-26T09:19:39.618309 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.66713, final_score: 0.40465, time: 289.71068 +[RESULT]: Val. Epoch: 35, summary_loss: 0.70271, final_score: 0.42557, time: 24.75349 + +2021-06-26T09:24:54.261237 +LR: 0.000125 +Emb_rate: 0.7290000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.66630, final_score: 0.40502, time: 289.57200 +[RESULT]: Val. Epoch: 36, summary_loss: 0.68240, final_score: 0.41858, time: 25.13296 + +2021-06-26T09:30:09.137612 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.66607, final_score: 0.40215, time: 289.71302 +[RESULT]: Val. Epoch: 37, summary_loss: 0.68402, final_score: 0.41858, time: 24.45674 + +2021-06-26T09:35:23.470989 +LR: 0.000125 +Emb_rate: 0.6561000000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.66377, final_score: 0.40052, time: 290.31621 +[RESULT]: Val. Epoch: 38, summary_loss: 0.68677, final_score: 0.40809, time: 24.26277 + +2021-06-26T09:40:38.211835 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 39, summary_loss: 0.66333, final_score: 0.39978, time: 289.47866 +[RESULT]: Val. Epoch: 39, summary_loss: 0.70275, final_score: 0.42408, time: 24.43087 + +2021-06-26T09:45:52.326072 +LR: 0.000125 +Emb_rate: 0.5904900000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.66266, final_score: 0.39578, time: 289.60719 +[RESULT]: Val. Epoch: 40, summary_loss: 0.69212, final_score: 0.42507, time: 25.06366 + +2021-06-26T09:51:07.164384 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.66181, final_score: 0.39690, time: 289.24794 +[RESULT]: Val. Epoch: 41, summary_loss: 0.71239, final_score: 0.42807, time: 25.04314 + +2021-06-26T09:56:21.615468 +LR: 0.000125 +Emb_rate: 0.5314410000000002 +[RESULT]: Train. Epoch: 42, summary_loss: 0.66018, final_score: 0.39340, time: 289.45224 +[RESULT]: Val. Epoch: 42, summary_loss: 0.71245, final_score: 0.41858, time: 23.75519 + +2021-06-26T10:01:34.986330 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 43, summary_loss: 0.65830, final_score: 0.38778, time: 289.93943 +[RESULT]: Val. Epoch: 43, summary_loss: 0.68265, final_score: 0.41508, time: 26.05476 + +2021-06-26T10:06:51.141779 +LR: 0.000125 +Emb_rate: 0.47829690000000014 +[RESULT]: Train. Epoch: 44, summary_loss: 0.65900, final_score: 0.38940, time: 289.24518 +[RESULT]: Val. Epoch: 44, summary_loss: 0.67816, final_score: 0.40859, time: 25.60115 + +2021-06-26T10:12:06.142663 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 45, summary_loss: 0.65768, final_score: 0.38965, time: 290.28377 +[RESULT]: Val. Epoch: 45, summary_loss: 0.68936, final_score: 0.41009, time: 25.16630 + +2021-06-26T10:17:21.760951 +LR: 0.000125 +Emb_rate: 0.43046721000000016 +[RESULT]: Train. Epoch: 46, summary_loss: 0.65690, final_score: 0.39415, time: 290.15734 +[RESULT]: Val. Epoch: 46, summary_loss: 0.67998, final_score: 0.41059, time: 24.10699 + +2021-06-26T10:22:36.192585 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.65318, final_score: 0.38440, time: 289.95613 +[RESULT]: Val. Epoch: 47, summary_loss: 0.69638, final_score: 0.40659, time: 25.70998 + +2021-06-26T10:27:52.027416 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.65378, final_score: 0.38515, time: 289.30379 +[RESULT]: Val. Epoch: 48, summary_loss: 0.68723, final_score: 0.40809, time: 24.73830 + +2021-06-26T10:33:06.225261 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.64887, final_score: 0.38215, time: 290.43244 +[RESULT]: Val. Epoch: 49, summary_loss: 0.68696, final_score: 0.40410, time: 25.01953 + +2021-06-26T10:38:21.844383 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.65028, final_score: 0.37716, time: 289.41333 +[RESULT]: Val. Epoch: 50, summary_loss: 0.69367, final_score: 0.40460, time: 24.81593 + +2021-06-26T10:43:36.247965 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.65053, final_score: 0.38103, time: 289.78670 +[RESULT]: Val. Epoch: 51, summary_loss: 0.68427, final_score: 0.40360, time: 24.85318 + +2021-06-26T10:48:51.083584 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.64827, final_score: 0.37753, time: 289.79249 +[RESULT]: Val. Epoch: 52, summary_loss: 0.68667, final_score: 0.40559, time: 25.03715 + +2021-06-26T10:54:06.081377 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.64861, final_score: 0.38128, time: 289.32338 +[RESULT]: Val. Epoch: 53, summary_loss: 0.68844, final_score: 0.40110, time: 25.47052 + +2021-06-26T10:59:21.033381 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.64826, final_score: 0.36991, time: 289.72214 +[RESULT]: Val. Epoch: 54, summary_loss: 0.68474, final_score: 0.40110, time: 24.33139 + +2021-06-26T11:04:35.258485 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.64769, final_score: 0.37316, time: 289.94974 +[RESULT]: Val. Epoch: 55, summary_loss: 0.68850, final_score: 0.40410, time: 25.19742 + +2021-06-26T11:09:50.620405 +LR: 3.90625e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.64723, final_score: 0.37603, time: 290.44198 +[RESULT]: Val. Epoch: 56, summary_loss: 0.69781, final_score: 0.40609, time: 24.30765 + +2021-06-26T11:15:05.528418 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.64854, final_score: 0.37828, time: 290.03439 +[RESULT]: Val. Epoch: 57, summary_loss: 0.68422, final_score: 0.40110, time: 26.80078 + +2021-06-26T11:20:22.527503 +LR: 1.953125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.64849, final_score: 0.37416, time: 289.84963 +[RESULT]: Val. Epoch: 58, summary_loss: 0.68796, final_score: 0.40559, time: 24.15200 + +2021-06-26T11:25:36.694399 +LR: 9.765625e-07 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.64639, final_score: 0.37341, time: 289.83514 +[RESULT]: Val. Epoch: 59, summary_loss: 0.68406, final_score: 0.40260, time: 25.13345 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-001epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-001epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..42f7356fbea4376375bc4db83692fe1873bc58c8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-001epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8e5571ba7df62b01c34ada03c4624f7f594666dc6507fc2595dc21e2a86e278d +size 69172438 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-005epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-005epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..7a4a85d5839ea56444955fefd2a8bdce61cd27f8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-005epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7f0abbb4883cda8046397e1c41a3ca50307e17f0b38083fb88a4d1868c18dc67 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..8386a118c17943e053040778a8469fd8d572d553 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c16406d93929541ea90636a390384ba7cfcdda60fe300e8594089b5675d41405 +size 69172374 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..c612d029e8ab411258257e71728ef2b8d5344ba1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4437eeb04d924afcfdc32fb373c67b1e5c0780c2292d8dc3dac43465cc325f4e +size 69172438 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f0aed9e661922a0c0427666d127a26b90cc904e3 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/log.txt @@ -0,0 +1,100 @@ +Fitter prepared. Device is cuda:0 + +2021-04-06T13:41:24.938679 +LR: 0.001 +Emb_rate: 0.7 +[RESULT]: Train. Epoch: 0, summary_loss: 0.72282, final_score: 0.49809, time: 517.16676 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69943, final_score: 0.49800, time: 160.16959 + +2021-04-06T13:52:42.719632 +LR: 0.001 +Emb_rate: 0.63 +[RESULT]: Train. Epoch: 1, summary_loss: 0.70199, final_score: 0.49022, time: 581.01155 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69885, final_score: 0.49401, time: 155.75730 + +2021-04-06T14:04:59.902507 +LR: 0.001 +Emb_rate: 0.63 +[RESULT]: Train. Epoch: 2, summary_loss: 0.70219, final_score: 0.49772, time: 518.94051 +[RESULT]: Val. Epoch: 2, summary_loss: 0.71018, final_score: 0.49401, time: 150.45693 + +2021-04-06T14:16:09.504348 +LR: 0.001 +Emb_rate: 0.5670000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69956, final_score: 0.49435, time: 524.41321 +[RESULT]: Val. Epoch: 3, summary_loss: 0.70864, final_score: 0.49800, time: 134.31624 + +2021-04-06T14:27:08.417532 +LR: 0.001 +Emb_rate: 0.5670000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.70110, final_score: 0.48935, time: 534.77653 +[RESULT]: Val. Epoch: 4, summary_loss: 0.70395, final_score: 0.49800, time: 151.50510 + +2021-04-06T14:38:34.878508 +LR: 0.001 +Emb_rate: 0.5103000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69935, final_score: 0.49249, time: 569.52817 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69317, final_score: 0.49700, time: 163.87445 + +2021-04-06T14:50:48.694448 +LR: 0.001 +Emb_rate: 0.5103000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69852, final_score: 0.49800, time: 596.01768 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69381, final_score: 0.49451, time: 164.66586 + +2021-04-06T15:03:29.589571 +LR: 0.001 +Emb_rate: 0.45927000000000007 +[RESULT]: Train. Epoch: 7, summary_loss: 0.69915, final_score: 0.49399, time: 518.97630 +[RESULT]: Val. Epoch: 7, summary_loss: 0.77485, final_score: 0.49650, time: 162.52371 + +2021-04-06T15:14:51.300477 +LR: 0.001 +Emb_rate: 0.45927000000000007 +[RESULT]: Train. Epoch: 8, summary_loss: 0.69952, final_score: 0.49599, time: 499.44378 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69465, final_score: 0.49650, time: 157.05457 + +2021-04-06T15:25:48.119656 +LR: 0.001 +Emb_rate: 0.41334300000000007 +[RESULT]: Train. Epoch: 9, summary_loss: 0.69844, final_score: 0.49848, time: 539.14084 +[RESULT]: Val. Epoch: 9, summary_loss: 0.70249, final_score: 0.49800, time: 161.58685 + +2021-04-06T15:37:29.053104 +LR: 0.001 +Emb_rate: 0.41334300000000007 +[RESULT]: Train. Epoch: 10, summary_loss: 0.69690, final_score: 0.48819, time: 587.14150 +[RESULT]: Val. Epoch: 10, summary_loss: 0.69441, final_score: 0.49500, time: 156.75844 +Fitter prepared. Device is cuda:0 + +2021-04-08T08:06:55.352664 +LR: 0.001 +Emb_rate: 1.0 +Fitter prepared. Device is cuda:0 + +2021-04-08T08:08:08.333123 +LR: 0.001 +Emb_rate: 1.0 +[RESULT]: Train. Epoch: 0, summary_loss: 0.61767, final_score: 0.34491, time: 433.87334 +[RESULT]: Val. Epoch: 0, summary_loss: 1.12149, final_score: 0.32717, time: 127.36631 + +2021-04-08T08:17:30.168372 +LR: 0.001 +Emb_rate: 0.9 +Fitter prepared. Device is cuda:0 + +2021-04-12T13:51:48.541192 +LR: 0.001 +Emb_rate: 1.2 +Fitter prepared. Device is cuda:0 +Fitter prepared. Device is cuda:0 + +2021-04-28T09:36:54.965790 +LR: 0.001 +Emb_rate: 0.24 +[RESULT]: Train. Epoch: 1, summary_loss: 0.67230, final_score: 0.38303, time: 673.06895 +[RESULT]: Val. Epoch: 1, summary_loss: 1.30752, final_score: 0.47902, time: 202.51438 + +2021-04-28T09:51:30.922833 +LR: 0.001 +Emb_rate: 0.216 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..194b7fe8b732c3dc7af9a5a5e8f5bcd1b3aa71bb Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-028epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-028epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..391ca2c5ed568d7673819914e3d9dc056432e8b6 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-028epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4a03bfbc3b4c6a2587320e9fa13a15700a614b458ecaf517b0e2673a515a6cc2 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-031epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-031epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..ac03cb52d436ed5deb3e3d99c509325eabcb43c1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-031epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:76c806d368d29e8f7e22f9c856059dfe74d64711469a02a1e6b955725b985d64 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-036epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-036epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..375cb9ccfb010784666e50be578afbe3a659d6b8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/best-checkpoint-036epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ed4efbc3bfc5f81cff9fc8a37992ed3aa9e014c7eb5183e65bf0881a5da8b9c1 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..030b7886cc31ef4bd3f01d091a6f08baeb9013e2 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8037bc09f6b05b5baeeece1098b61315cb58848ae3ce3c9ee46aa24199ee4cf5 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..5bd3507d8728c9e0902d271c9b5f877072520e17 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/log.txt @@ -0,0 +1,254 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:47:45.181104 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.46653, final_score: 0.20845, time: 647.80818 +[RESULT]: Val. Epoch: 0, summary_loss: 2.61759, final_score: 0.48002, time: 199.41531 + +2021-04-26T10:01:52.834758 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.18362, final_score: 0.01900, time: 637.79749 +[RESULT]: Val. Epoch: 1, summary_loss: 1.48727, final_score: 0.47902, time: 215.57560 + +2021-04-26T10:16:06.553729 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.16076, final_score: 0.01137, time: 647.79765 +[RESULT]: Val. Epoch: 2, summary_loss: 1.22666, final_score: 0.45055, time: 203.14394 + +2021-04-26T10:30:17.971094 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.16445, final_score: 0.01225, time: 647.51563 +[RESULT]: Val. Epoch: 3, summary_loss: 2.11409, final_score: 0.47103, time: 205.91400 + +2021-04-26T10:44:31.602627 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.17419, final_score: 0.01687, time: 655.63127 +[RESULT]: Val. Epoch: 4, summary_loss: 3.01678, final_score: 0.48002, time: 203.66919 + +2021-04-26T10:58:51.093886 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.17580, final_score: 0.01712, time: 653.53254 +[RESULT]: Val. Epoch: 5, summary_loss: 1.38926, final_score: 0.44705, time: 202.57373 + +2021-04-26T11:13:07.393861 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.15821, final_score: 0.01025, time: 679.21056 +[RESULT]: Val. Epoch: 6, summary_loss: 1.43767, final_score: 0.45854, time: 202.87938 + +2021-04-26T11:27:49.657280 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.18987, final_score: 0.02537, time: 686.23749 +[RESULT]: Val. Epoch: 7, summary_loss: 2.50336, final_score: 0.46853, time: 202.90086 + +2021-04-26T11:42:38.978270 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.18251, final_score: 0.02149, time: 673.36028 +[RESULT]: Val. Epoch: 8, summary_loss: 1.99218, final_score: 0.45355, time: 202.70501 + +2021-04-26T11:57:15.203687 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.19793, final_score: 0.03012, time: 676.62080 +[RESULT]: Val. Epoch: 9, summary_loss: 1.78947, final_score: 0.44356, time: 202.46851 + +2021-04-26T12:11:54.464370 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.19506, final_score: 0.02937, time: 669.54129 +[RESULT]: Val. Epoch: 10, summary_loss: 2.69203, final_score: 0.46304, time: 203.21163 + +2021-04-26T12:26:27.408122 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.20559, final_score: 0.03487, time: 685.89687 +[RESULT]: Val. Epoch: 11, summary_loss: 1.96020, final_score: 0.46553, time: 202.38798 + +2021-04-26T12:41:15.890282 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.21981, final_score: 0.04299, time: 680.28723 +[RESULT]: Val. Epoch: 12, summary_loss: 1.85339, final_score: 0.43856, time: 203.07733 + +2021-04-26T12:55:59.416682 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.24046, final_score: 0.05399, time: 686.06290 +[RESULT]: Val. Epoch: 13, summary_loss: 1.28382, final_score: 0.43157, time: 203.11228 + +2021-04-26T13:10:48.777815 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.22656, final_score: 0.04674, time: 672.47998 +[RESULT]: Val. Epoch: 14, summary_loss: 1.77621, final_score: 0.42308, time: 203.64534 + +2021-04-26T13:25:25.114927 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.24707, final_score: 0.06098, time: 679.90146 +[RESULT]: Val. Epoch: 15, summary_loss: 1.93670, final_score: 0.44456, time: 202.74944 + +2021-04-26T13:40:08.031517 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.25391, final_score: 0.06511, time: 681.78799 +[RESULT]: Val. Epoch: 16, summary_loss: 1.99685, final_score: 0.43606, time: 203.62761 + +2021-04-26T13:54:53.641344 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.28172, final_score: 0.07836, time: 680.97461 +[RESULT]: Val. Epoch: 17, summary_loss: 1.05556, final_score: 0.42308, time: 206.22731 + +2021-04-26T14:09:41.304739 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.26787, final_score: 0.07048, time: 681.62578 +[RESULT]: Val. Epoch: 18, summary_loss: 1.66519, final_score: 0.42358, time: 206.34734 + +2021-04-26T14:24:29.483820 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.30682, final_score: 0.09473, time: 680.64729 +[RESULT]: Val. Epoch: 19, summary_loss: 1.18940, final_score: 0.41359, time: 206.65576 + +2021-04-26T14:39:17.017795 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.30944, final_score: 0.09873, time: 682.66315 +[RESULT]: Val. Epoch: 20, summary_loss: 1.04541, final_score: 0.41259, time: 206.19856 + +2021-04-26T14:54:06.227823 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 21, summary_loss: 0.32869, final_score: 0.10922, time: 680.17991 +[RESULT]: Val. Epoch: 21, summary_loss: 1.80547, final_score: 0.43457, time: 205.68367 + +2021-04-26T15:08:52.260713 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 22, summary_loss: 0.32664, final_score: 0.10835, time: 667.00014 +[RESULT]: Val. Epoch: 22, summary_loss: 1.57916, final_score: 0.41558, time: 203.72627 + +2021-04-26T15:23:23.175459 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 23, summary_loss: 0.36265, final_score: 0.13134, time: 673.88407 +[RESULT]: Val. Epoch: 23, summary_loss: 1.24792, final_score: 0.41459, time: 205.94042 + +2021-04-26T15:38:03.172040 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 24, summary_loss: 0.34949, final_score: 0.12209, time: 679.86101 +[RESULT]: Val. Epoch: 24, summary_loss: 1.53584, final_score: 0.41159, time: 202.54676 + +2021-04-26T15:52:45.816931 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 25, summary_loss: 0.38895, final_score: 0.14809, time: 672.69777 +[RESULT]: Val. Epoch: 25, summary_loss: 1.11786, final_score: 0.39710, time: 203.52531 + +2021-04-26T16:07:22.233515 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 26, summary_loss: 0.37853, final_score: 0.14584, time: 671.95245 +[RESULT]: Val. Epoch: 26, summary_loss: 1.27258, final_score: 0.41309, time: 203.50339 + +2021-04-26T16:21:57.978027 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 27, summary_loss: 0.41055, final_score: 0.16033, time: 670.03026 +[RESULT]: Val. Epoch: 27, summary_loss: 0.97403, final_score: 0.39311, time: 206.48937 + +2021-04-26T16:36:34.850832 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 28, summary_loss: 0.40955, final_score: 0.16421, time: 666.72797 +[RESULT]: Val. Epoch: 28, summary_loss: 0.96333, final_score: 0.38462, time: 204.16401 + +2021-04-26T16:51:06.180013 +LR: 0.001 +Emb_rate: 0.24706935851357886 +[RESULT]: Train. Epoch: 29, summary_loss: 0.43107, final_score: 0.18033, time: 672.73569 +[RESULT]: Val. Epoch: 29, summary_loss: 1.61924, final_score: 0.39910, time: 203.56923 +Fitter prepared. Device is cuda:0 + +2021-04-28T10:05:02.001047 +LR: 0.001 +Emb_rate: 0.24 +[RESULT]: Train. Epoch: 30, summary_loss: 0.43901, final_score: 0.18583, time: 670.03966 +[RESULT]: Val. Epoch: 30, summary_loss: 0.98015, final_score: 0.38362, time: 201.49861 + +2021-04-28T10:19:33.723778 +LR: 0.001 +Emb_rate: 0.216 +[RESULT]: Train. Epoch: 31, summary_loss: 0.46583, final_score: 0.20482, time: 662.73002 +[RESULT]: Val. Epoch: 31, summary_loss: 0.84601, final_score: 0.38112, time: 200.20963 + +2021-04-28T10:33:57.297513 +LR: 0.001 +Emb_rate: 0.216 +[RESULT]: Train. Epoch: 32, summary_loss: 0.45929, final_score: 0.19958, time: 664.37477 +[RESULT]: Val. Epoch: 32, summary_loss: 1.19469, final_score: 0.37762, time: 199.11684 + +2021-04-28T10:48:20.965669 +LR: 0.001 +Emb_rate: 0.1944 +[RESULT]: Train. Epoch: 33, summary_loss: 0.48782, final_score: 0.22469, time: 668.25154 +[RESULT]: Val. Epoch: 33, summary_loss: 0.97575, final_score: 0.37862, time: 200.39152 + +2021-04-28T11:02:49.810846 +LR: 0.001 +Emb_rate: 0.1944 +[RESULT]: Train. Epoch: 34, summary_loss: 0.48539, final_score: 0.22682, time: 665.46960 +[RESULT]: Val. Epoch: 34, summary_loss: 0.86914, final_score: 0.38262, time: 199.91907 + +2021-04-28T11:17:15.380361 +LR: 0.001 +Emb_rate: 0.17496 +[RESULT]: Train. Epoch: 35, summary_loss: 0.50773, final_score: 0.24319, time: 665.99118 +[RESULT]: Val. Epoch: 35, summary_loss: 1.88383, final_score: 0.42158, time: 200.60358 + +2021-04-28T11:31:42.297315 +LR: 0.001 +Emb_rate: 0.17496 +[RESULT]: Train. Epoch: 36, summary_loss: 0.50719, final_score: 0.24506, time: 676.49385 +[RESULT]: Val. Epoch: 36, summary_loss: 0.68849, final_score: 0.35564, time: 199.61468 + +2021-04-28T11:46:18.805486 +LR: 0.001 +Emb_rate: 0.15746400000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.53387, final_score: 0.26381, time: 659.37483 +[RESULT]: Val. Epoch: 37, summary_loss: 0.92357, final_score: 0.37213, time: 199.15123 + +2021-04-28T12:00:37.511071 +LR: 0.001 +Emb_rate: 0.15746400000000002 +[RESULT]: Train. Epoch: 38, summary_loss: 0.52559, final_score: 0.25781, time: 662.77672 +[RESULT]: Val. Epoch: 38, summary_loss: 0.87759, final_score: 0.37762, time: 202.62457 + +2021-04-28T12:15:03.104602 +LR: 0.001 +Emb_rate: 0.14171760000000003 +[RESULT]: Train. Epoch: 39, summary_loss: 0.54556, final_score: 0.27543, time: 665.82074 +[RESULT]: Val. Epoch: 39, summary_loss: 0.78534, final_score: 0.38412, time: 202.84920 + +2021-04-28T12:29:31.974626 +LR: 0.001 +Emb_rate: 0.14171760000000003 +[RESULT]: Train. Epoch: 40, summary_loss: 0.53779, final_score: 0.27068, time: 675.80680 +[RESULT]: Val. Epoch: 40, summary_loss: 1.08446, final_score: 0.39011, time: 202.78889 + +2021-04-28T12:44:10.754016 +LR: 0.001 +Emb_rate: 0.12754584000000002 +[RESULT]: Train. Epoch: 41, summary_loss: 0.55730, final_score: 0.28705, time: 682.57216 +[RESULT]: Val. Epoch: 41, summary_loss: 0.69114, final_score: 0.36014, time: 203.69537 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..dd9eff9018d56d1cad22607170667210b5bb3ba5 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-005epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-005epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..8852d7ae636e816c93bc8fb06f4edfd5fcd2418f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-005epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:402a54b4950ef46860238ee5d157c0ee3f9298ab8fadd2ac736852c48d6f8414 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-019epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-019epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..61bdca3534de888eeb1bf2187fdcd267c05f0c3b --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-019epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:22019cf5eb6f27a1501ed19ebb4667f6f708b2864a794b6a4d360248a5ff6bdc +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..759bef315ce8b151e2ddaf97c415ac1eec976e74 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7ec364f2f895dd43b978d94f98f4784b2b5137046e2d14808bdd77d5d2bcd28a +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..68ab102ccd453d5520221548fba869041df1aa63 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:33af0b672f0500821bef125f7baaaf286bcb09de2ed7bbebefa7b7709ff36da5 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec1b206127348c9ed0c2e25f5c55bc79fc2a2f54 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_0_0.2/log.txt @@ -0,0 +1,182 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:41:29.790710 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.49016, final_score: 0.23569, time: 635.97913 +[RESULT]: Val. Epoch: 0, summary_loss: 1.06867, final_score: 0.42258, time: 208.89643 + +2021-04-26T09:55:35.134824 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.21303, final_score: 0.03637, time: 654.17670 +[RESULT]: Val. Epoch: 1, summary_loss: 2.24277, final_score: 0.45255, time: 208.98919 + +2021-04-26T10:09:58.499757 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.20397, final_score: 0.03387, time: 663.72753 +[RESULT]: Val. Epoch: 2, summary_loss: 1.17171, final_score: 0.39411, time: 211.79667 + +2021-04-26T10:24:34.225724 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.18395, final_score: 0.02249, time: 667.18538 +[RESULT]: Val. Epoch: 3, summary_loss: 1.42771, final_score: 0.41009, time: 208.57293 + +2021-04-26T10:39:10.188839 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.19061, final_score: 0.02762, time: 651.98108 +[RESULT]: Val. Epoch: 4, summary_loss: 1.63638, final_score: 0.42058, time: 208.79686 + +2021-04-26T10:53:31.166839 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.20362, final_score: 0.03449, time: 657.47271 +[RESULT]: Val. Epoch: 5, summary_loss: 0.78805, final_score: 0.35914, time: 209.00004 + +2021-04-26T11:07:58.048735 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.19148, final_score: 0.03062, time: 667.15818 +[RESULT]: Val. Epoch: 6, summary_loss: 1.54906, final_score: 0.40210, time: 209.20147 + +2021-04-26T11:22:34.613884 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.19875, final_score: 0.03424, time: 667.58946 +[RESULT]: Val. Epoch: 7, summary_loss: 0.87019, final_score: 0.34915, time: 208.56198 + +2021-04-26T11:37:10.950626 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.18884, final_score: 0.02624, time: 658.72204 +[RESULT]: Val. Epoch: 8, summary_loss: 2.15168, final_score: 0.41658, time: 208.58588 + +2021-04-26T11:51:38.437662 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.21134, final_score: 0.04099, time: 670.18506 +[RESULT]: Val. Epoch: 9, summary_loss: 1.30803, final_score: 0.36763, time: 208.23415 + +2021-04-26T12:06:17.039077 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.20251, final_score: 0.03299, time: 673.37661 +[RESULT]: Val. Epoch: 10, summary_loss: 1.30706, final_score: 0.36863, time: 209.61250 + +2021-04-26T12:21:00.211621 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.21673, final_score: 0.04486, time: 673.14536 +[RESULT]: Val. Epoch: 11, summary_loss: 1.49003, final_score: 0.38462, time: 208.35489 + +2021-04-26T12:35:41.910318 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.22355, final_score: 0.04611, time: 676.56898 +[RESULT]: Val. Epoch: 12, summary_loss: 2.04287, final_score: 0.42308, time: 208.27205 + +2021-04-26T12:50:26.946771 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.25015, final_score: 0.06073, time: 675.18381 +[RESULT]: Val. Epoch: 13, summary_loss: 2.38588, final_score: 0.39411, time: 208.33586 + +2021-04-26T13:05:10.666410 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.22688, final_score: 0.05074, time: 675.49036 +[RESULT]: Val. Epoch: 14, summary_loss: 1.11003, final_score: 0.32567, time: 208.26282 + +2021-04-26T13:19:54.621188 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.25219, final_score: 0.06373, time: 677.78479 +[RESULT]: Val. Epoch: 15, summary_loss: 0.82783, final_score: 0.30170, time: 208.36971 + +2021-04-26T13:34:40.995576 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.25259, final_score: 0.06398, time: 673.35406 +[RESULT]: Val. Epoch: 16, summary_loss: 1.54595, final_score: 0.34016, time: 208.04154 + +2021-04-26T13:49:22.607009 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.28440, final_score: 0.08098, time: 676.17903 +[RESULT]: Val. Epoch: 17, summary_loss: 0.97612, final_score: 0.33666, time: 209.11678 + +2021-04-26T14:04:08.088720 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.27863, final_score: 0.08123, time: 680.64545 +[RESULT]: Val. Epoch: 18, summary_loss: 0.97326, final_score: 0.29920, time: 208.02249 + +2021-04-26T14:18:56.952753 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.31216, final_score: 0.10360, time: 684.32330 +[RESULT]: Val. Epoch: 19, summary_loss: 0.64522, final_score: 0.28122, time: 207.33044 + +2021-04-26T14:33:48.981858 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.29121, final_score: 0.08948, time: 683.49834 +[RESULT]: Val. Epoch: 20, summary_loss: 1.89217, final_score: 0.37163, time: 208.19462 + +2021-04-26T14:48:40.843274 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 21, summary_loss: 0.33566, final_score: 0.11460, time: 677.05413 +[RESULT]: Val. Epoch: 21, summary_loss: 0.70392, final_score: 0.31319, time: 207.55316 + +2021-04-26T15:03:25.654522 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 22, summary_loss: 0.31432, final_score: 0.10272, time: 694.33982 +[RESULT]: Val. Epoch: 22, summary_loss: 0.72450, final_score: 0.27622, time: 208.21273 + +2021-04-26T15:18:28.400063 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 23, summary_loss: 0.35377, final_score: 0.12972, time: 677.04945 +[RESULT]: Val. Epoch: 23, summary_loss: 0.70854, final_score: 0.28472, time: 207.56785 + +2021-04-26T15:33:13.222686 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 24, summary_loss: 0.35176, final_score: 0.13022, time: 671.63821 +[RESULT]: Val. Epoch: 24, summary_loss: 1.42391, final_score: 0.31818, time: 207.47885 + +2021-04-26T15:47:52.534467 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 25, summary_loss: 0.37669, final_score: 0.14696, time: 677.96330 +[RESULT]: Val. Epoch: 25, summary_loss: 1.51473, final_score: 0.34466, time: 207.94727 + +2021-04-26T16:02:38.649474 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 26, summary_loss: 0.37382, final_score: 0.13984, time: 678.22598 +[RESULT]: Val. Epoch: 26, summary_loss: 1.15343, final_score: 0.28621, time: 207.89043 + +2021-04-26T16:17:25.007076 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 27, summary_loss: 0.41130, final_score: 0.16958, time: 678.51397 +[RESULT]: Val. Epoch: 27, summary_loss: 0.78090, final_score: 0.29321, time: 208.07955 + +2021-04-26T16:32:11.806991 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 28, summary_loss: 0.39803, final_score: 0.16196, time: 672.29874 +[RESULT]: Val. Epoch: 28, summary_loss: 1.09821, final_score: 0.30470, time: 207.35893 + +2021-04-26T16:46:51.628359 +LR: 0.001 +Emb_rate: 0.24706935851357886 +[RESULT]: Train. Epoch: 29, summary_loss: 0.43459, final_score: 0.18720, time: 691.76630 +[RESULT]: Val. Epoch: 29, summary_loss: 0.55774, final_score: 0.23477, time: 208.37847 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:41:31.378396 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.38599, final_score: 0.15759, time: 645.79428 +[RESULT]: Val. Epoch: 0, summary_loss: 3.48633, final_score: 0.46054, time: 207.24475 + +2021-04-26T09:55:44.780632 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.19379, final_score: 0.02749, time: 647.36235 +[RESULT]: Val. Epoch: 1, summary_loss: 0.95566, final_score: 0.33866, time: 206.16629 + +2021-04-26T10:09:58.712869 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.17253, final_score: 0.01975, time: 665.58095 +[RESULT]: Val. Epoch: 2, summary_loss: 1.40343, final_score: 0.40959, time: 208.19640 + +2021-04-26T10:24:32.673824 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.18539, final_score: 0.02562, time: 666.22591 +[RESULT]: Val. Epoch: 3, summary_loss: 2.33766, final_score: 0.46054, time: 206.90865 + +2021-04-26T10:39:06.024281 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.16307, final_score: 0.01462, time: 654.57414 +[RESULT]: Val. Epoch: 4, summary_loss: 2.05941, final_score: 0.38412, time: 206.02258 + +2021-04-26T10:53:26.828177 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.22363, final_score: 0.04699, time: 653.03357 +[RESULT]: Val. Epoch: 5, summary_loss: 1.08580, final_score: 0.31469, time: 207.39993 + +2021-04-26T11:07:47.464393 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.18176, final_score: 0.02349, time: 664.45088 +[RESULT]: Val. Epoch: 6, summary_loss: 0.73515, final_score: 0.25824, time: 206.28199 + +2021-04-26T11:22:18.563664 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.19727, final_score: 0.03149, time: 662.58741 +[RESULT]: Val. Epoch: 7, summary_loss: 1.08521, final_score: 0.27073, time: 206.48248 + +2021-04-26T11:36:47.800856 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.18609, final_score: 0.02724, time: 662.30011 +[RESULT]: Val. Epoch: 8, summary_loss: 1.59318, final_score: 0.33916, time: 206.46732 + +2021-04-26T11:51:16.738227 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.20822, final_score: 0.03862, time: 665.88481 +[RESULT]: Val. Epoch: 9, summary_loss: 2.02503, final_score: 0.33167, time: 205.89480 + +2021-04-26T12:05:48.723777 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.19439, final_score: 0.03137, time: 659.93169 +[RESULT]: Val. Epoch: 10, summary_loss: 0.63220, final_score: 0.23177, time: 207.16395 + +2021-04-26T12:20:16.207021 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.22030, final_score: 0.04524, time: 666.04500 +[RESULT]: Val. Epoch: 11, summary_loss: 1.20874, final_score: 0.25275, time: 207.23298 + +2021-04-26T12:34:49.683022 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.20353, final_score: 0.03424, time: 663.01185 +[RESULT]: Val. Epoch: 12, summary_loss: 0.86122, final_score: 0.21379, time: 206.16608 + +2021-04-26T12:49:19.062625 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.22970, final_score: 0.05186, time: 668.37924 +[RESULT]: Val. Epoch: 13, summary_loss: 0.83096, final_score: 0.20679, time: 206.54322 + +2021-04-26T13:03:54.178973 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.22728, final_score: 0.04924, time: 669.62539 +[RESULT]: Val. Epoch: 14, summary_loss: 1.17762, final_score: 0.25425, time: 205.26800 + +2021-04-26T13:18:29.276645 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.24571, final_score: 0.06223, time: 666.63477 +[RESULT]: Val. Epoch: 15, summary_loss: 0.89709, final_score: 0.21129, time: 205.97476 + +2021-04-26T13:33:02.086475 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.23947, final_score: 0.05761, time: 684.47531 +[RESULT]: Val. Epoch: 16, summary_loss: 1.08347, final_score: 0.23277, time: 205.99100 + +2021-04-26T13:47:52.744932 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.27208, final_score: 0.07436, time: 687.41185 +[RESULT]: Val. Epoch: 17, summary_loss: 0.54250, final_score: 0.23227, time: 207.34920 + +2021-04-26T14:02:47.878454 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.26647, final_score: 0.07273, time: 674.94120 +[RESULT]: Val. Epoch: 18, summary_loss: 1.22297, final_score: 0.24975, time: 209.63479 + +2021-04-26T14:17:32.630358 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.29709, final_score: 0.08898, time: 676.97208 +[RESULT]: Val. Epoch: 19, summary_loss: 1.20955, final_score: 0.26873, time: 207.18100 + +2021-04-26T14:32:16.991890 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.29295, final_score: 0.08910, time: 671.08693 +[RESULT]: Val. Epoch: 20, summary_loss: 1.30892, final_score: 0.23277, time: 207.43666 + +2021-04-26T14:46:55.744147 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 21, summary_loss: 0.31993, final_score: 0.10560, time: 681.49227 +[RESULT]: Val. Epoch: 21, summary_loss: 0.53163, final_score: 0.19231, time: 208.51136 + +2021-04-26T15:01:46.110930 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 22, summary_loss: 0.32247, final_score: 0.10310, time: 687.25390 +[RESULT]: Val. Epoch: 22, summary_loss: 0.47227, final_score: 0.17882, time: 206.16453 + +2021-04-26T15:16:39.931051 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 23, summary_loss: 0.35293, final_score: 0.12447, time: 670.10821 +[RESULT]: Val. Epoch: 23, summary_loss: 1.20042, final_score: 0.24925, time: 201.81978 + +2021-04-26T15:31:12.057022 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 24, summary_loss: 0.33927, final_score: 0.11847, time: 668.57467 +[RESULT]: Val. Epoch: 24, summary_loss: 0.44726, final_score: 0.17433, time: 201.66854 + +2021-04-26T15:45:42.646491 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 25, summary_loss: 0.37746, final_score: 0.14721, time: 661.75204 +[RESULT]: Val. Epoch: 25, summary_loss: 0.73953, final_score: 0.21279, time: 201.89830 + +2021-04-26T16:00:06.480786 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 26, summary_loss: 0.37511, final_score: 0.13984, time: 657.88709 +[RESULT]: Val. Epoch: 26, summary_loss: 0.49948, final_score: 0.16733, time: 200.87829 + +2021-04-26T16:14:25.441813 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 27, summary_loss: 0.36757, final_score: 0.13622, time: 658.29337 +[RESULT]: Val. Epoch: 27, summary_loss: 0.41168, final_score: 0.16034, time: 203.21185 + +2021-04-26T16:28:47.466796 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 28, summary_loss: 0.35703, final_score: 0.13497, time: 670.02004 +[RESULT]: Val. Epoch: 28, summary_loss: 0.45268, final_score: 0.16783, time: 201.30139 + +2021-04-26T16:43:18.987870 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 29, summary_loss: 0.35961, final_score: 0.13122, time: 659.53766 +[RESULT]: Val. Epoch: 29, summary_loss: 0.43916, final_score: 0.16933, time: 201.98829 +Fitter prepared. Device is cuda:0 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:41:29.807606 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.45927, final_score: 0.20282, time: 653.78587 +[RESULT]: Val. Epoch: 0, summary_loss: 3.20046, final_score: 0.38511, time: 197.19974 + +2021-04-26T09:55:41.154860 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.20067, final_score: 0.02974, time: 655.16823 +[RESULT]: Val. Epoch: 1, summary_loss: 0.78770, final_score: 0.26024, time: 197.07499 + +2021-04-26T10:09:53.736053 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.15623, final_score: 0.00887, time: 653.42757 +[RESULT]: Val. Epoch: 2, summary_loss: 1.85108, final_score: 0.31668, time: 197.22722 + +2021-04-26T10:24:04.561735 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.16536, final_score: 0.01275, time: 656.26028 +[RESULT]: Val. Epoch: 3, summary_loss: 2.67521, final_score: 0.39560, time: 196.81941 + +2021-04-26T10:38:17.820095 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.16153, final_score: 0.01087, time: 655.09344 +[RESULT]: Val. Epoch: 4, summary_loss: 0.58535, final_score: 0.15035, time: 197.09271 + +2021-04-26T10:52:30.343987 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.17878, final_score: 0.02024, time: 643.96009 +[RESULT]: Val. Epoch: 5, summary_loss: 1.16335, final_score: 0.20230, time: 196.29852 + +2021-04-26T11:06:30.782814 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.16461, final_score: 0.01287, time: 637.14297 +[RESULT]: Val. Epoch: 6, summary_loss: 1.04057, final_score: 0.22378, time: 195.43337 + +2021-04-26T11:20:23.534804 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.18444, final_score: 0.02212, time: 656.67878 +[RESULT]: Val. Epoch: 7, summary_loss: 0.82968, final_score: 0.17233, time: 195.62219 + +2021-04-26T11:34:36.006273 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.17760, final_score: 0.02099, time: 650.11651 +[RESULT]: Val. Epoch: 8, summary_loss: 1.94824, final_score: 0.30969, time: 195.75555 + +2021-04-26T11:48:42.062298 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.19736, final_score: 0.02899, time: 660.41442 +[RESULT]: Val. Epoch: 9, summary_loss: 1.65825, final_score: 0.25125, time: 196.90500 + +2021-04-26T12:02:59.554948 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.17828, final_score: 0.02012, time: 662.07420 +[RESULT]: Val. Epoch: 10, summary_loss: 0.79338, final_score: 0.14785, time: 195.24949 + +2021-04-26T12:17:17.057116 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.20830, final_score: 0.03737, time: 665.60520 +[RESULT]: Val. Epoch: 11, summary_loss: 1.38185, final_score: 0.24925, time: 202.99927 + +2021-04-26T12:31:45.849485 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.20766, final_score: 0.03462, time: 657.19440 +[RESULT]: Val. Epoch: 12, summary_loss: 1.75751, final_score: 0.24875, time: 196.00509 + +2021-04-26T12:45:59.216303 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.22859, final_score: 0.04674, time: 664.53085 +[RESULT]: Val. Epoch: 13, summary_loss: 2.45117, final_score: 0.25724, time: 195.21341 + +2021-04-26T13:00:19.145778 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.22491, final_score: 0.04636, time: 675.78805 +[RESULT]: Val. Epoch: 14, summary_loss: 1.12858, final_score: 0.17083, time: 196.52163 + +2021-04-26T13:14:51.637622 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.25471, final_score: 0.06386, time: 682.03267 +[RESULT]: Val. Epoch: 15, summary_loss: 0.48417, final_score: 0.11788, time: 196.45389 + +2021-04-26T13:29:30.541848 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.24571, final_score: 0.05861, time: 681.76292 +[RESULT]: Val. Epoch: 16, summary_loss: 1.03129, final_score: 0.17483, time: 201.19385 + +2021-04-26T13:44:13.702682 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 17, summary_loss: 0.24909, final_score: 0.05961, time: 679.83901 +[RESULT]: Val. Epoch: 17, summary_loss: 0.87621, final_score: 0.16933, time: 195.64850 + +2021-04-26T13:58:49.354242 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 18, summary_loss: 0.25492, final_score: 0.06223, time: 659.14790 +[RESULT]: Val. Epoch: 18, summary_loss: 0.83993, final_score: 0.19331, time: 197.08850 + +2021-04-26T14:13:05.758707 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 19, summary_loss: 0.24357, final_score: 0.05699, time: 671.24644 +[RESULT]: Val. Epoch: 19, summary_loss: 0.59350, final_score: 0.11638, time: 196.67481 + +2021-04-26T14:27:33.846380 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 20, summary_loss: 0.22768, final_score: 0.04824, time: 657.07229 +[RESULT]: Val. Epoch: 20, summary_loss: 0.59128, final_score: 0.14036, time: 197.09688 + +2021-04-26T14:41:48.192722 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 21, summary_loss: 0.22872, final_score: 0.04774, time: 670.19885 +[RESULT]: Val. Epoch: 21, summary_loss: 0.72829, final_score: 0.08941, time: 195.41106 + +2021-04-26T14:56:14.683862 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 22, summary_loss: 0.22629, final_score: 0.04849, time: 665.45181 +[RESULT]: Val. Epoch: 22, summary_loss: 0.71158, final_score: 0.13586, time: 196.12835 + +2021-04-26T15:10:36.424438 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 23, summary_loss: 0.20375, final_score: 0.03487, time: 664.04294 +[RESULT]: Val. Epoch: 23, summary_loss: 0.35618, final_score: 0.06543, time: 197.96909 + +2021-04-26T15:24:58.831287 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 24, summary_loss: 0.19997, final_score: 0.03099, time: 673.43717 +[RESULT]: Val. Epoch: 24, summary_loss: 0.44139, final_score: 0.07992, time: 195.54916 + +2021-04-26T15:39:27.998354 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 25, summary_loss: 0.19641, final_score: 0.02937, time: 664.57461 +[RESULT]: Val. Epoch: 25, summary_loss: 0.76669, final_score: 0.10889, time: 196.56850 + +2021-04-26T15:53:49.317481 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 26, summary_loss: 0.18907, final_score: 0.02787, time: 668.29295 +[RESULT]: Val. Epoch: 26, summary_loss: 0.23657, final_score: 0.04695, time: 196.52427 + +2021-04-26T16:08:14.483569 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 27, summary_loss: 0.18454, final_score: 0.02487, time: 664.15126 +[RESULT]: Val. Epoch: 27, summary_loss: 0.51024, final_score: 0.09291, time: 196.43586 + +2021-04-26T16:22:35.352431 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 28, summary_loss: 0.18698, final_score: 0.02612, time: 681.02673 +[RESULT]: Val. Epoch: 28, summary_loss: 0.27390, final_score: 0.06793, time: 203.41192 + +2021-04-26T16:37:19.968817 +LR: 0.000125 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 29, summary_loss: 0.17910, final_score: 0.02012, time: 672.68675 +[RESULT]: Val. Epoch: 29, summary_loss: 0.27654, final_score: 0.05345, time: 196.12415 +Fitter prepared. 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Device is cuda:0 + +2021-04-09T14:26:32.381893 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.50880, final_score: 0.25106, time: 402.50623 +[RESULT]: Val. Epoch: 0, summary_loss: 3.21548, final_score: 0.46953, time: 125.26842 + +2021-04-09T14:35:20.520837 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.21665, final_score: 0.03912, time: 406.69880 +[RESULT]: Val. Epoch: 1, summary_loss: 2.00677, final_score: 0.43856, time: 124.43031 + +2021-04-09T14:44:12.019466 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.17964, final_score: 0.02124, time: 405.00425 +[RESULT]: Val. Epoch: 2, summary_loss: 0.98252, final_score: 0.39461, time: 124.73399 + +2021-04-09T14:53:02.149040 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.19752, final_score: 0.02924, time: 411.28023 +[RESULT]: Val. Epoch: 3, summary_loss: 1.73345, final_score: 0.42757, time: 123.87052 + +2021-04-09T15:01:57.494288 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.18191, final_score: 0.02212, time: 408.70378 +[RESULT]: Val. Epoch: 4, summary_loss: 2.96732, final_score: 0.43656, time: 123.71029 + +2021-04-09T15:10:50.111009 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.20142, final_score: 0.03174, time: 411.20297 +[RESULT]: Val. Epoch: 5, summary_loss: 1.65784, final_score: 0.40010, time: 124.77741 + +2021-04-09T15:19:46.297841 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.20188, final_score: 0.03274, time: 409.81489 +[RESULT]: Val. Epoch: 6, summary_loss: 2.20129, final_score: 0.44655, time: 125.60046 + +2021-04-09T15:28:41.912973 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.22638, final_score: 0.04711, time: 413.83959 +[RESULT]: Val. Epoch: 7, summary_loss: 2.11496, final_score: 0.38412, time: 127.13078 + +2021-04-09T15:37:43.087717 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.21975, final_score: 0.04286, time: 414.91235 +[RESULT]: Val. Epoch: 8, summary_loss: 1.96588, final_score: 0.35764, time: 126.35819 + +2021-04-09T15:46:44.566219 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.26150, final_score: 0.06598, time: 421.09882 +[RESULT]: Val. Epoch: 9, summary_loss: 0.97173, final_score: 0.34615, time: 126.15175 + +2021-04-09T15:55:52.251215 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.23795, final_score: 0.05199, time: 424.61797 +[RESULT]: Val. Epoch: 10, summary_loss: 1.91259, final_score: 0.35514, time: 125.33134 + +2021-04-09T16:05:02.412539 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.29764, final_score: 0.09098, time: 424.31906 +[RESULT]: Val. Epoch: 11, summary_loss: 0.84816, final_score: 0.35714, time: 125.80253 + +2021-04-09T16:14:12.923719 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.28483, final_score: 0.08223, time: 422.37200 +[RESULT]: Val. Epoch: 12, summary_loss: 0.95078, final_score: 0.34965, time: 125.35596 + +2021-04-09T16:23:20.849396 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.35148, final_score: 0.12172, time: 429.24279 +[RESULT]: Val. Epoch: 13, summary_loss: 1.30719, final_score: 0.29421, time: 124.72075 + +2021-04-09T16:32:35.033650 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.33115, final_score: 0.10897, time: 426.39000 +[RESULT]: Val. Epoch: 14, summary_loss: 0.68708, final_score: 0.28222, time: 124.41971 + +2021-04-09T16:41:46.311466 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.37656, final_score: 0.13909, time: 427.29041 +[RESULT]: Val. Epoch: 15, summary_loss: 0.82088, final_score: 0.29171, time: 125.01961 + +2021-04-09T16:50:58.823092 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.37787, final_score: 0.14321, time: 422.98008 +[RESULT]: Val. Epoch: 16, summary_loss: 1.60908, final_score: 0.36014, time: 124.66048 + +2021-04-09T17:00:06.702311 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.43966, final_score: 0.18320, time: 428.08081 +[RESULT]: Val. Epoch: 17, summary_loss: 1.18064, final_score: 0.30170, time: 125.00390 + +2021-04-09T17:09:19.986112 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.42972, final_score: 0.17646, time: 428.42628 +[RESULT]: Val. Epoch: 18, summary_loss: 0.64441, final_score: 0.25974, time: 126.40660 + +2021-04-09T17:18:35.171255 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.47222, final_score: 0.20970, time: 427.16171 +[RESULT]: Val. Epoch: 19, summary_loss: 0.59532, final_score: 0.27323, time: 124.22798 + +2021-04-09T17:27:46.944266 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.45237, final_score: 0.19258, time: 429.23317 +[RESULT]: Val. Epoch: 20, summary_loss: 0.58807, final_score: 0.23027, time: 123.39412 + +2021-04-09T17:36:59.954855 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.47702, final_score: 0.20745, time: 431.48436 +[RESULT]: Val. Epoch: 21, summary_loss: 0.80373, final_score: 0.27622, time: 124.21070 + +2021-04-09T17:46:15.849911 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.46153, final_score: 0.20020, time: 428.46089 +[RESULT]: Val. Epoch: 22, summary_loss: 0.73897, final_score: 0.29421, time: 124.84805 + +2021-04-09T17:55:29.369460 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.43283, final_score: 0.18158, time: 435.46057 +[RESULT]: Val. Epoch: 23, summary_loss: 0.54562, final_score: 0.22478, time: 124.38199 + +2021-04-09T18:04:49.601604 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.42660, final_score: 0.17458, time: 429.98881 +[RESULT]: Val. Epoch: 24, summary_loss: 0.64750, final_score: 0.25724, time: 125.92906 + +2021-04-09T18:14:05.754193 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.40870, final_score: 0.16721, time: 428.73946 +[RESULT]: Val. Epoch: 25, summary_loss: 0.91842, final_score: 0.23077, time: 125.41470 + +2021-04-09T18:23:20.111196 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.39375, final_score: 0.15584, time: 430.03138 +[RESULT]: Val. Epoch: 26, summary_loss: 0.57275, final_score: 0.19630, time: 125.40608 + +2021-04-09T18:32:35.756529 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.38258, final_score: 0.14809, time: 428.24292 +[RESULT]: Val. Epoch: 27, summary_loss: 0.56445, final_score: 0.19431, time: 126.01048 + +2021-04-09T18:41:50.226652 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.37078, final_score: 0.13722, time: 427.26766 +[RESULT]: Val. Epoch: 28, summary_loss: 0.51660, final_score: 0.19181, time: 125.77744 + +2021-04-09T18:51:03.665022 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.36786, final_score: 0.13834, time: 429.52909 +[RESULT]: Val. Epoch: 29, summary_loss: 0.48703, final_score: 0.17732, time: 125.33008 +Fitter prepared. Device is cuda:0 + +2021-04-12T18:00:58.477184 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.48428, final_score: 0.22632, time: 438.66438 +[RESULT]: Val. Epoch: 0, summary_loss: 3.34797, final_score: 0.46653, time: 142.18541 + +2021-04-12T18:10:40.031599 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.21569, final_score: 0.03874, time: 443.76478 +[RESULT]: Val. Epoch: 1, summary_loss: 1.30477, final_score: 0.43057, time: 139.25234 + +2021-04-12T18:20:23.513990 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.17624, final_score: 0.01800, time: 445.06598 +[RESULT]: Val. Epoch: 2, summary_loss: 1.22398, final_score: 0.37213, time: 139.06620 + +2021-04-12T18:30:08.121233 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.18908, final_score: 0.02549, time: 432.60417 +[RESULT]: Val. Epoch: 3, summary_loss: 2.23192, final_score: 0.43457, time: 138.56094 + +2021-04-12T18:39:39.496402 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.18107, final_score: 0.02037, time: 436.31047 +[RESULT]: Val. Epoch: 4, summary_loss: 1.47112, final_score: 0.37962, time: 138.09186 + +2021-04-12T18:49:14.174303 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.20598, final_score: 0.03699, time: 454.81060 +[RESULT]: Val. Epoch: 5, summary_loss: 3.43284, final_score: 0.44955, time: 141.57151 + +2021-04-12T18:59:10.800689 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.20087, final_score: 0.03237, time: 439.84112 +[RESULT]: Val. Epoch: 6, summary_loss: 1.47657, final_score: 0.38811, time: 137.59925 + +2021-04-12T19:08:48.485679 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.22896, final_score: 0.04524, time: 449.93577 +[RESULT]: Val. Epoch: 7, summary_loss: 1.47746, final_score: 0.41359, time: 138.10975 + +2021-04-12T19:18:36.747789 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.21754, final_score: 0.04349, time: 445.91988 +[RESULT]: Val. Epoch: 8, summary_loss: 1.67439, final_score: 0.37063, time: 144.85834 + +2021-04-12T19:28:27.729246 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.26677, final_score: 0.07011, time: 455.31442 +[RESULT]: Val. Epoch: 9, summary_loss: 3.96923, final_score: 0.43107, time: 139.11973 + +2021-04-12T19:38:22.367227 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.25230, final_score: 0.06311, time: 444.62797 +[RESULT]: Val. Epoch: 10, summary_loss: 1.20851, final_score: 0.37712, time: 139.38942 + +2021-04-12T19:48:06.973036 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.31534, final_score: 0.10135, time: 459.40691 +[RESULT]: Val. Epoch: 11, summary_loss: 1.71413, final_score: 0.38162, time: 138.93421 + +2021-04-12T19:58:05.554879 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.28639, final_score: 0.08398, time: 453.52716 +[RESULT]: Val. Epoch: 12, summary_loss: 1.82653, final_score: 0.34865, time: 139.71528 + +2021-04-12T20:07:59.005508 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.35358, final_score: 0.12659, time: 450.29876 +[RESULT]: Val. Epoch: 13, summary_loss: 0.83522, final_score: 0.36114, time: 138.76737 + +2021-04-12T20:17:48.467101 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.34055, final_score: 0.11660, time: 453.27352 +[RESULT]: Val. Epoch: 14, summary_loss: 1.28528, final_score: 0.31069, time: 137.28487 + +2021-04-12T20:27:39.322858 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.38922, final_score: 0.14984, time: 448.25744 +[RESULT]: Val. Epoch: 15, summary_loss: 1.40383, final_score: 0.35165, time: 138.01172 + +2021-04-12T20:37:25.779955 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.38232, final_score: 0.14709, time: 459.41706 +[RESULT]: Val. Epoch: 16, summary_loss: 1.30883, final_score: 0.28072, time: 137.59392 + +2021-04-12T20:47:22.984962 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.43797, final_score: 0.18408, time: 455.95951 +[RESULT]: Val. Epoch: 17, summary_loss: 0.56405, final_score: 0.27323, time: 137.22567 + +2021-04-12T20:57:16.553623 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.42152, final_score: 0.17283, time: 455.83525 +[RESULT]: Val. Epoch: 18, summary_loss: 1.32010, final_score: 0.31369, time: 137.72697 + +2021-04-12T21:07:10.308289 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.46860, final_score: 0.20632, time: 449.55976 +[RESULT]: Val. Epoch: 19, summary_loss: 0.60781, final_score: 0.23576, time: 136.89788 + +2021-04-12T21:16:56.952341 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.46742, final_score: 0.20132, time: 455.51998 +[RESULT]: Val. Epoch: 20, summary_loss: 0.78360, final_score: 0.30669, time: 136.99421 + +2021-04-12T21:26:49.661842 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.47724, final_score: 0.21395, time: 462.68792 +[RESULT]: Val. Epoch: 21, summary_loss: 1.32946, final_score: 0.30819, time: 137.98752 + +2021-04-12T21:36:50.530595 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.46816, final_score: 0.20557, time: 456.55752 +[RESULT]: Val. Epoch: 22, summary_loss: 1.19621, final_score: 0.28172, time: 136.98396 + +2021-04-12T21:46:44.348109 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.43918, final_score: 0.18420, time: 461.42478 +[RESULT]: Val. Epoch: 23, summary_loss: 0.79855, final_score: 0.28821, time: 136.81305 + +2021-04-12T21:56:42.813236 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.41829, final_score: 0.17496, time: 453.77212 +[RESULT]: Val. Epoch: 24, summary_loss: 0.57432, final_score: 0.22677, time: 138.96950 + +2021-04-12T22:06:35.750320 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.40649, final_score: 0.16071, time: 457.54659 +[RESULT]: Val. Epoch: 25, summary_loss: 1.65611, final_score: 0.22977, time: 137.09322 + +2021-04-12T22:16:30.580943 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.40723, final_score: 0.16521, time: 465.01436 +[RESULT]: Val. Epoch: 26, summary_loss: 0.51934, final_score: 0.22777, time: 137.14090 + +2021-04-12T22:26:33.150184 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.39618, final_score: 0.15259, time: 466.74769 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..bf9c3aafa44a9bca498a4519d2541477d044d870 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b0643c3675d4f8cd640669ded00c6a7a1e96616a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:45d983098775859616cb0845e592cb8b5b87de7b994866b79cdf1eb3ba3b4174 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b7b4d75c9126ab49cca016da66f1b2ac3fdbe754 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9ce7be8ae5113b12626618f6e53e354c5051f32392448bd681f704c0eddd4ce4 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c6dd99154ea57b633a4da3a0c40262d143729992 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1089ba79d32d41c095cad93a73f8840121f4e8b0de8b0594dbcd6e781ff3a595 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..ff0fa9a671af4a17d38427f8d8b763e2dfd534dd --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5654354d95731ffccb8eb9ed85da448909914d2fdcd644355e7fdf4a6e336610 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..455d604b33dacf7d0bbf0975857e5d4531597d46 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-04-15T07:51:54.863166 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.62708, final_score: 0.31892, time: 402.36934 +[RESULT]: Val. Epoch: 0, summary_loss: 7.58348, final_score: 0.49451, time: 124.36670 + +2021-04-15T08:00:41.960111 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.49450, final_score: 0.22369, time: 409.69803 +[RESULT]: Val. Epoch: 1, summary_loss: 4.18828, final_score: 0.48601, time: 124.70379 + +2021-04-15T08:09:36.719462 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.32524, final_score: 0.10297, time: 413.61195 +[RESULT]: Val. Epoch: 2, summary_loss: 1.18124, final_score: 0.46104, time: 126.02877 + +2021-04-15T08:18:36.710927 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.29928, final_score: 0.08923, time: 409.19170 +[RESULT]: Val. Epoch: 3, summary_loss: 1.53729, final_score: 0.45954, time: 127.26140 + +2021-04-15T08:27:33.345782 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22852, final_score: 0.04624, time: 411.42281 +[RESULT]: Val. Epoch: 4, summary_loss: 1.93370, final_score: 0.44855, time: 129.31487 + +2021-04-15T08:36:34.299763 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.27097, final_score: 0.07186, time: 413.47816 +[RESULT]: Val. Epoch: 5, summary_loss: 1.42547, final_score: 0.44106, time: 129.56446 + +2021-04-15T08:45:37.547431 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22995, final_score: 0.04874, time: 412.53150 +[RESULT]: Val. Epoch: 6, summary_loss: 1.95635, final_score: 0.43656, time: 129.21804 + +2021-04-15T08:54:39.486516 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.27939, final_score: 0.07773, time: 413.30684 +[RESULT]: Val. Epoch: 7, summary_loss: 1.51215, final_score: 0.42258, time: 128.90793 + +2021-04-15T09:03:41.902448 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.26582, final_score: 0.06836, time: 414.73827 +[RESULT]: Val. Epoch: 8, summary_loss: 1.67121, final_score: 0.43257, time: 129.62783 + +2021-04-15T09:12:46.477403 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.31181, final_score: 0.09760, time: 425.54922 +[RESULT]: Val. Epoch: 9, summary_loss: 1.24133, final_score: 0.41159, time: 129.55461 + +2021-04-15T09:22:01.798883 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.31708, final_score: 0.10197, time: 418.59210 +[RESULT]: Val. Epoch: 10, summary_loss: 1.86136, final_score: 0.44156, time: 129.65190 + +2021-04-15T09:31:10.260549 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.36156, final_score: 0.13072, time: 427.26039 +[RESULT]: Val. Epoch: 11, summary_loss: 1.71666, final_score: 0.40160, time: 130.22975 + +2021-04-15T09:40:27.956226 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.35724, final_score: 0.12747, time: 422.38595 +[RESULT]: Val. Epoch: 12, summary_loss: 1.63407, final_score: 0.41608, time: 128.83496 + +2021-04-15T09:49:39.383200 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.43309, final_score: 0.17871, time: 426.28925 +[RESULT]: Val. Epoch: 13, summary_loss: 0.94756, final_score: 0.38811, time: 129.85277 + +2021-04-15T09:58:55.940973 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.42474, final_score: 0.17271, time: 425.00773 +[RESULT]: Val. Epoch: 14, summary_loss: 0.91114, final_score: 0.37562, time: 129.56796 + +2021-04-15T10:08:10.869280 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.48198, final_score: 0.21195, time: 424.21870 +[RESULT]: Val. Epoch: 15, summary_loss: 2.09205, final_score: 0.39061, time: 129.95336 + +2021-04-15T10:17:25.250271 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.46799, final_score: 0.20270, time: 422.06789 +[RESULT]: Val. Epoch: 16, summary_loss: 1.00801, final_score: 0.39211, time: 128.74490 + +2021-04-15T10:26:36.248692 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.52376, final_score: 0.24506, time: 429.16847 +[RESULT]: Val. Epoch: 17, summary_loss: 0.82713, final_score: 0.35714, time: 129.08907 + +2021-04-15T10:35:54.862280 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.51698, final_score: 0.24106, time: 427.12824 +[RESULT]: Val. Epoch: 18, summary_loss: 0.90282, final_score: 0.34865, time: 129.67944 + +2021-04-15T10:45:11.868193 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.56358, final_score: 0.27893, time: 424.17587 +[RESULT]: Val. Epoch: 19, summary_loss: 0.62801, final_score: 0.31069, time: 129.01723 + +2021-04-15T10:54:25.428711 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.55109, final_score: 0.26581, time: 426.91463 +[RESULT]: Val. Epoch: 20, summary_loss: 1.17616, final_score: 0.37912, time: 128.46500 + +2021-04-15T11:03:41.058207 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.56382, final_score: 0.28130, time: 430.00769 +[RESULT]: Val. Epoch: 21, summary_loss: 1.27088, final_score: 0.35764, time: 128.32204 + +2021-04-15T11:12:59.591625 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.54931, final_score: 0.26718, time: 425.32347 +[RESULT]: Val. Epoch: 22, summary_loss: 0.60565, final_score: 0.29920, time: 127.56254 + +2021-04-15T11:22:12.829802 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.55300, final_score: 0.26793, time: 426.59903 +[RESULT]: Val. Epoch: 23, summary_loss: 0.63713, final_score: 0.28871, time: 127.04145 + +2021-04-15T11:31:26.674663 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.54546, final_score: 0.25931, time: 426.37550 +[RESULT]: Val. Epoch: 24, summary_loss: 0.57717, final_score: 0.27722, time: 127.36562 + +2021-04-15T11:40:40.775515 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.53900, final_score: 0.25381, time: 426.62515 +[RESULT]: Val. Epoch: 25, summary_loss: 2.03884, final_score: 0.37612, time: 125.91541 + +2021-04-15T11:49:53.527810 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.53918, final_score: 0.25606, time: 427.38334 +[RESULT]: Val. Epoch: 26, summary_loss: 0.60773, final_score: 0.28521, time: 126.82035 + +2021-04-15T11:59:07.946758 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.50606, final_score: 0.23394, time: 426.89213 +[RESULT]: Val. Epoch: 27, summary_loss: 0.83973, final_score: 0.27722, time: 126.98801 + +2021-04-15T12:08:22.031063 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.50448, final_score: 0.22794, time: 432.45939 +[RESULT]: Val. Epoch: 28, summary_loss: 0.79911, final_score: 0.28571, time: 129.82443 + +2021-04-15T12:17:44.538091 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.48222, final_score: 0.21707, time: 430.80292 +[RESULT]: Val. Epoch: 29, summary_loss: 0.57013, final_score: 0.24975, time: 128.22108 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..c39552bfdf9db9a0146533dae7320b10c6ff17c2 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_2/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-021epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-021epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..e1b06ee257d1b2a353b9c092d5388742ec1f8ca9 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-021epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d31fb07f2f0ad25787fe2d12ca7ea4a917d45bf535afd47031a4f7bd87e2b16c +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a6c8a1c96aeebef2757dfdc36c6d25f5ba50be32 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:76f156116e2fc5356453b6bf935c1b82e272926630405fa928f702001a597897 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..9e1a90027c368df6b238000d3f44fa7106453ec1 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:09fa4a90761784c9d4285575e48b7c03ced676ec3d48d6dad1668cbf369b375a +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..d47d410e021f240a0138f2de3e5d8d9fc070ef8c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d0d39163fd79445481d0c031aeeeab1cd5b70711c82393d9cc44a5bc466a8360 +size 69172566 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..288713ade722b8a3eaa43176b22132b3acf5a98c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/log.txt @@ -0,0 +1,240 @@ +Fitter prepared. Device is cuda:0 + +2021-04-19T06:46:36.328914 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.48788, final_score: 0.22144, time: 662.71609 +[RESULT]: Val. Epoch: 0, summary_loss: 1.23488, final_score: 0.48102, time: 206.50357 + +2021-04-19T07:01:05.988956 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.23714, final_score: 0.05699, time: 663.71629 +[RESULT]: Val. Epoch: 1, summary_loss: 1.63338, final_score: 0.47203, time: 211.43606 + +2021-04-19T07:15:41.358522 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.19656, final_score: 0.02949, time: 669.32617 +[RESULT]: Val. Epoch: 2, summary_loss: 2.82807, final_score: 0.47702, time: 202.41411 + +2021-04-19T07:30:13.299604 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.23040, final_score: 0.05361, time: 655.17119 +[RESULT]: Val. Epoch: 3, summary_loss: 1.25491, final_score: 0.48152, time: 201.74034 + +2021-04-19T07:44:30.426678 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.20337, final_score: 0.03562, time: 668.82833 +[RESULT]: Val. Epoch: 4, summary_loss: 1.99418, final_score: 0.47652, time: 201.79144 + +2021-04-19T07:59:01.226092 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24395, final_score: 0.05736, time: 667.29155 +[RESULT]: Val. Epoch: 5, summary_loss: 1.68170, final_score: 0.46603, time: 202.88219 + +2021-04-19T08:13:31.590332 +LR: 0.001 +Emb_rate: 0.8748000000000001 +Fitter prepared. Device is cuda:0 + +2021-04-19T18:41:08.558186 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.58729, final_score: 0.31967, time: 677.12094 +[RESULT]: Val. Epoch: 0, summary_loss: 2.78126, final_score: 0.49251, time: 213.94392 + +2021-04-19T18:56:00.124051 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.24176, final_score: 0.05361, time: 686.59191 +[RESULT]: Val. Epoch: 1, summary_loss: 2.20877, final_score: 0.48651, time: 211.77799 + +2021-04-19T19:10:58.912812 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.18828, final_score: 0.02387, time: 695.39382 +[RESULT]: Val. Epoch: 2, summary_loss: 2.10062, final_score: 0.49201, time: 212.91195 + +2021-04-19T19:26:07.640035 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.22345, final_score: 0.04399, time: 694.49552 +[RESULT]: Val. Epoch: 3, summary_loss: 2.37738, final_score: 0.48801, time: 213.05900 + +2021-04-19T19:41:15.388180 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.20109, final_score: 0.02974, time: 698.33332 +[RESULT]: Val. Epoch: 4, summary_loss: 1.35152, final_score: 0.48352, time: 214.57835 + +2021-04-19T19:56:28.701276 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24859, final_score: 0.05724, time: 702.26998 +[RESULT]: Val. Epoch: 5, summary_loss: 2.38236, final_score: 0.48052, time: 214.09926 + +2021-04-19T20:11:45.300183 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22671, final_score: 0.04674, time: 692.21349 +[RESULT]: Val. Epoch: 6, summary_loss: 1.35193, final_score: 0.47552, time: 213.17342 + +2021-04-19T20:26:50.919264 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28623, final_score: 0.07998, time: 693.06104 +[RESULT]: Val. Epoch: 7, summary_loss: 1.67610, final_score: 0.47802, time: 212.14060 + +2021-04-19T20:41:56.317137 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.25750, final_score: 0.06311, time: 696.30483 +[RESULT]: Val. Epoch: 8, summary_loss: 2.19302, final_score: 0.47752, time: 212.66086 + +2021-04-19T20:57:05.507021 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.33241, final_score: 0.10710, time: 700.99891 +[RESULT]: Val. Epoch: 9, summary_loss: 2.32706, final_score: 0.46553, time: 212.12924 + +2021-04-19T21:12:18.841839 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.32876, final_score: 0.10847, time: 697.32577 +[RESULT]: Val. Epoch: 10, summary_loss: 1.29618, final_score: 0.45654, time: 211.67012 + +2021-04-19T21:27:28.254973 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39061, final_score: 0.14621, time: 692.04497 +[RESULT]: Val. Epoch: 11, summary_loss: 2.38576, final_score: 0.46254, time: 209.28829 + +2021-04-19T21:42:29.761434 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.37796, final_score: 0.14196, time: 696.35216 +[RESULT]: Val. Epoch: 12, summary_loss: 2.11282, final_score: 0.45904, time: 209.12145 + +2021-04-19T21:57:35.446530 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.45565, final_score: 0.19620, time: 695.87802 +[RESULT]: Val. Epoch: 13, summary_loss: 0.88575, final_score: 0.39560, time: 208.20087 + +2021-04-19T22:12:39.977543 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.44313, final_score: 0.17971, time: 695.75353 +[RESULT]: Val. Epoch: 14, summary_loss: 1.08665, final_score: 0.41209, time: 207.31392 + +2021-04-19T22:27:43.251408 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.49978, final_score: 0.22657, time: 704.13129 +[RESULT]: Val. Epoch: 15, summary_loss: 0.72385, final_score: 0.36513, time: 208.69480 + +2021-04-19T22:42:56.489894 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.49318, final_score: 0.21882, time: 702.69145 +[RESULT]: Val. Epoch: 16, summary_loss: 1.78968, final_score: 0.37762, time: 212.56849 + +2021-04-19T22:58:11.923498 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.51712, final_score: 0.23319, time: 698.07584 +[RESULT]: Val. Epoch: 17, summary_loss: 0.66799, final_score: 0.31019, time: 209.43483 + +2021-04-19T23:13:19.801397 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.50614, final_score: 0.22807, time: 693.51467 +[RESULT]: Val. Epoch: 18, summary_loss: 0.58116, final_score: 0.27972, time: 211.10319 + +2021-04-19T23:28:24.805634 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.51971, final_score: 0.23869, time: 695.11652 +[RESULT]: Val. Epoch: 19, summary_loss: 1.08790, final_score: 0.36214, time: 209.79795 + +2021-04-19T23:43:29.896259 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.51607, final_score: 0.23144, time: 698.39378 +[RESULT]: Val. Epoch: 20, summary_loss: 0.80032, final_score: 0.25524, time: 208.49191 + +2021-04-19T23:58:36.967025 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.50804, final_score: 0.23032, time: 694.72337 +[RESULT]: Val. Epoch: 21, summary_loss: 0.54563, final_score: 0.22527, time: 209.07687 + +2021-04-20T00:13:41.136389 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.49771, final_score: 0.22257, time: 703.28226 +[RESULT]: Val. Epoch: 22, summary_loss: 1.07376, final_score: 0.32368, time: 207.37316 + +2021-04-20T00:28:51.972278 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.49092, final_score: 0.21657, time: 692.98693 +[RESULT]: Val. Epoch: 23, summary_loss: 1.03617, final_score: 0.27672, time: 207.34973 + +2021-04-20T00:43:52.494296 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.46836, final_score: 0.20095, time: 693.86656 +[RESULT]: Val. Epoch: 24, summary_loss: 0.54144, final_score: 0.23127, time: 207.23518 + +2021-04-20T00:58:53.931394 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.46231, final_score: 0.19945, time: 698.76766 +[RESULT]: Val. Epoch: 25, summary_loss: 0.75841, final_score: 0.23477, time: 207.19381 + +2021-04-20T01:14:00.066715 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.45864, final_score: 0.19545, time: 700.11422 +[RESULT]: Val. Epoch: 26, summary_loss: 0.58177, final_score: 0.23177, time: 207.39133 + +2021-04-20T01:29:07.814466 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.44121, final_score: 0.17783, time: 698.70620 +[RESULT]: Val. Epoch: 27, summary_loss: 0.48290, final_score: 0.19930, time: 207.31190 + +2021-04-20T01:44:14.234701 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.43324, final_score: 0.17771, time: 703.74715 +[RESULT]: Val. Epoch: 28, summary_loss: 0.51630, final_score: 0.21029, time: 207.00380 + +2021-04-20T01:59:25.179479 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.43648, final_score: 0.18245, time: 700.24421 +[RESULT]: Val. Epoch: 29, summary_loss: 0.50993, final_score: 0.20729, time: 206.94086 +Fitter prepared. Device is cuda:0 + +2021-04-28T09:21:15.045053 +LR: 0.00025 +Emb_rate: 0.24 +[RESULT]: Train. Epoch: 30, summary_loss: 0.44258, final_score: 0.18520, time: 696.90540 +[RESULT]: Val. Epoch: 30, summary_loss: 0.74181, final_score: 0.24575, time: 203.73491 + +2021-04-28T09:36:15.907347 +LR: 0.00025 +Emb_rate: 0.216 +[RESULT]: Train. Epoch: 31, summary_loss: 0.43119, final_score: 0.17721, time: 690.80668 +[RESULT]: Val. Epoch: 31, summary_loss: 0.54522, final_score: 0.23027, time: 201.02705 + +2021-04-28T09:51:07.924218 +LR: 0.00025 +Emb_rate: 0.216 +[RESULT]: Train. Epoch: 32, summary_loss: 0.42469, final_score: 0.16658, time: 683.29846 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..f13f00e0fb3b879c9cc29e91dc72b5298d1821be Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..76d57df8fe9e6593fae5a1ddf8f092c17c6910f2 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:81f583167f31dbf98a31718e946e7cdaf55cf044e48b6b83c5177b33c1e243bd +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..01c3f11fd4ea7cccd3a19191dcb4d596121f6b1c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e8ab36421afede525763f99275d832b0dae197dc62371e840f1af8386d031b7c +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-032epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-032epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..fbe4caf30b3891414a1738282d40378bb1e87324 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/best-checkpoint-032epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5015e309af252842d5746d96b97fe4832b2dbd29501d1a47cfc0372c6142b7ed +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..5c7d8f3b908d876624d6eae2ec50fc66a9d40209 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:35b9f32b229d14ca6f985929fa5efa71ff2ca0ec25645673269d673a6c833b00 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..ecd90d3a3b23f3808978d26312a04059c264827c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/log.txt @@ -0,0 +1,252 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T09:50:39.809890 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.63156, final_score: 0.33779, time: 917.64000 +[RESULT]: Val. Epoch: 0, summary_loss: 3.08189, final_score: 0.50000, time: 236.69175 + +2021-04-26T10:09:54.774859 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.26212, final_score: 0.06448, time: 963.79370 +[RESULT]: Val. Epoch: 1, summary_loss: 2.42425, final_score: 0.49950, time: 231.77085 + +2021-04-26T10:29:50.874157 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.20454, final_score: 0.03374, time: 986.73583 +[RESULT]: Val. Epoch: 2, summary_loss: 1.85543, final_score: 0.50000, time: 276.83907 + +2021-04-26T10:50:54.952175 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.22267, final_score: 0.04261, time: 973.16202 +[RESULT]: Val. Epoch: 3, summary_loss: 1.49686, final_score: 0.50000, time: 288.95537 + +2021-04-26T11:11:57.496567 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.20684, final_score: 0.03399, time: 983.37107 +[RESULT]: Val. Epoch: 4, summary_loss: 1.96537, final_score: 0.50000, time: 248.20471 + +2021-04-26T11:32:29.282264 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24972, final_score: 0.06323, time: 941.80197 +[RESULT]: Val. Epoch: 5, summary_loss: 1.87845, final_score: 0.50000, time: 262.79973 + +2021-04-26T11:52:34.093851 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22807, final_score: 0.04799, time: 1002.12939 +[RESULT]: Val. Epoch: 6, summary_loss: 1.44981, final_score: 0.50000, time: 238.66233 + +2021-04-26T12:13:15.370010 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.29174, final_score: 0.08610, time: 948.32260 +[RESULT]: Val. Epoch: 7, summary_loss: 1.46717, final_score: 0.49950, time: 253.43940 + +2021-04-26T12:33:17.335276 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.27893, final_score: 0.07786, time: 964.17895 +[RESULT]: Val. Epoch: 8, summary_loss: 2.67220, final_score: 0.50000, time: 253.35764 + +2021-04-26T12:53:35.200503 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.33474, final_score: 0.11372, time: 980.03950 +[RESULT]: Val. Epoch: 9, summary_loss: 1.58595, final_score: 0.50000, time: 245.29764 + +2021-04-26T13:14:00.754424 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.33258, final_score: 0.10847, time: 954.66127 +[RESULT]: Val. Epoch: 10, summary_loss: 2.21578, final_score: 0.50000, time: 265.28557 + +2021-04-26T13:34:20.917047 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.40379, final_score: 0.15259, time: 980.66151 +[RESULT]: Val. Epoch: 11, summary_loss: 1.54649, final_score: 0.50000, time: 255.77876 + +2021-04-26T13:54:57.603416 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.38290, final_score: 0.14134, time: 1007.29861 +[RESULT]: Val. Epoch: 12, summary_loss: 1.60408, final_score: 0.50000, time: 236.77989 + +2021-04-26T14:15:42.025394 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44349, final_score: 0.18708, time: 991.34302 +[RESULT]: Val. Epoch: 13, summary_loss: 1.37694, final_score: 0.49850, time: 281.09896 + +2021-04-26T14:36:54.929568 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.43094, final_score: 0.17308, time: 970.88238 +[RESULT]: Val. Epoch: 14, summary_loss: 1.30532, final_score: 0.49900, time: 263.06930 + +2021-04-26T14:57:29.363205 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.49627, final_score: 0.22444, time: 995.33084 +[RESULT]: Val. Epoch: 15, summary_loss: 1.15096, final_score: 0.49351, time: 255.77235 + +2021-04-26T15:18:20.924202 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.47056, final_score: 0.20582, time: 987.62623 +[RESULT]: Val. Epoch: 16, summary_loss: 1.56664, final_score: 0.49201, time: 291.80306 + +2021-04-26T15:39:40.535668 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.51071, final_score: 0.23194, time: 973.69281 +[RESULT]: Val. Epoch: 17, summary_loss: 0.99025, final_score: 0.44705, time: 261.53903 + +2021-04-26T16:00:16.244432 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.50031, final_score: 0.22182, time: 1003.35406 +[RESULT]: Val. Epoch: 18, summary_loss: 0.95442, final_score: 0.44505, time: 268.83476 + +2021-04-26T16:21:28.890333 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.51159, final_score: 0.23232, time: 996.33581 +[RESULT]: Val. Epoch: 19, summary_loss: 1.23905, final_score: 0.40310, time: 242.74764 + +2021-04-26T16:42:08.215995 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.50218, final_score: 0.22607, time: 1026.32870 +[RESULT]: Val. Epoch: 20, summary_loss: 0.84523, final_score: 0.37812, time: 273.11002 + +2021-04-26T17:03:48.227264 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 21, summary_loss: 0.50434, final_score: 0.22819, time: 1037.64541 +[RESULT]: Val. Epoch: 21, summary_loss: 1.62630, final_score: 0.38861, time: 286.60542 + +2021-04-26T17:25:52.715200 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 22, summary_loss: 0.49016, final_score: 0.21182, time: 1013.60512 +[RESULT]: Val. Epoch: 22, summary_loss: 1.61645, final_score: 0.34416, time: 275.52631 + +2021-04-26T17:47:22.067236 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 23, summary_loss: 0.49360, final_score: 0.21595, time: 884.74358 +[RESULT]: Val. Epoch: 23, summary_loss: 0.80027, final_score: 0.30070, time: 257.97957 + +2021-04-26T18:06:25.211082 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 24, summary_loss: 0.47704, final_score: 0.20057, time: 875.01294 +[RESULT]: Val. Epoch: 24, summary_loss: 0.67859, final_score: 0.25824, time: 246.49223 + +2021-04-26T18:25:07.094672 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 25, summary_loss: 0.46499, final_score: 0.19570, time: 868.02859 +[RESULT]: Val. Epoch: 25, summary_loss: 0.91502, final_score: 0.31369, time: 220.95803 + +2021-04-26T18:43:16.296261 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 26, summary_loss: 0.45449, final_score: 0.18820, time: 874.96565 +[RESULT]: Val. Epoch: 26, summary_loss: 0.67249, final_score: 0.24675, time: 230.98878 + +2021-04-26T19:01:42.613710 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 27, summary_loss: 0.44385, final_score: 0.18420, time: 919.83307 +[RESULT]: Val. Epoch: 27, summary_loss: 0.64816, final_score: 0.26973, time: 261.88999 + +2021-04-26T19:21:24.718123 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 28, summary_loss: 0.43320, final_score: 0.17658, time: 884.21125 +[RESULT]: Val. Epoch: 28, summary_loss: 1.88805, final_score: 0.33866, time: 235.14951 + +2021-04-26T19:40:04.300015 +LR: 0.001 +Emb_rate: 0.24706935851357886 +Fitter prepared. Device is cuda:0 + +2021-04-28T10:06:50.846348 +LR: 0.001 +Emb_rate: 0.24 +[RESULT]: Train. Epoch: 29, summary_loss: 0.42476, final_score: 0.16883, time: 682.30213 +[RESULT]: Val. Epoch: 29, summary_loss: 0.80835, final_score: 0.22178, time: 204.63336 + +2021-04-28T10:21:38.127866 +LR: 0.001 +Emb_rate: 0.216 +[RESULT]: Train. Epoch: 30, summary_loss: 0.41559, final_score: 0.16408, time: 686.97646 +[RESULT]: Val. Epoch: 30, summary_loss: 0.74304, final_score: 0.25475, time: 204.77019 + +2021-04-28T10:36:30.205384 +LR: 0.001 +Emb_rate: 0.216 +[RESULT]: Train. Epoch: 31, summary_loss: 0.40924, final_score: 0.16071, time: 677.54650 +[RESULT]: Val. Epoch: 31, summary_loss: 1.50815, final_score: 0.26673, time: 207.72422 + +2021-04-28T10:51:15.687714 +LR: 0.001 +Emb_rate: 0.1944 +[RESULT]: Train. Epoch: 32, summary_loss: 0.39250, final_score: 0.14759, time: 685.29124 +[RESULT]: Val. Epoch: 32, summary_loss: 0.47818, final_score: 0.20529, time: 206.90191 + +2021-04-28T11:06:08.323936 +LR: 0.001 +Emb_rate: 0.1944 +[RESULT]: Train. Epoch: 33, summary_loss: 0.39161, final_score: 0.14759, time: 682.65054 +[RESULT]: Val. Epoch: 33, summary_loss: 0.60547, final_score: 0.20330, time: 208.08353 + +2021-04-28T11:20:59.294768 +LR: 0.001 +Emb_rate: 0.17496 +[RESULT]: Train. Epoch: 34, summary_loss: 0.38770, final_score: 0.14334, time: 691.67403 +[RESULT]: Val. Epoch: 34, summary_loss: 0.61422, final_score: 0.21878, time: 207.81111 + +2021-04-28T11:35:59.001290 +LR: 0.001 +Emb_rate: 0.17496 +[RESULT]: Train. Epoch: 35, summary_loss: 0.37174, final_score: 0.13197, time: 684.67847 +[RESULT]: Val. Epoch: 35, summary_loss: 0.61547, final_score: 0.20979, time: 206.81741 + +2021-04-28T11:50:50.694734 +LR: 0.001 +Emb_rate: 0.15746400000000002 +[RESULT]: Train. Epoch: 36, summary_loss: 0.37443, final_score: 0.13909, time: 678.81593 +[RESULT]: Val. Epoch: 36, summary_loss: 1.14144, final_score: 0.25375, time: 206.96695 + +2021-04-28T12:05:36.687522 +LR: 0.001 +Emb_rate: 0.15746400000000002 +[RESULT]: Train. Epoch: 37, summary_loss: 0.36538, final_score: 0.13272, time: 687.62750 +[RESULT]: Val. Epoch: 37, summary_loss: 1.10525, final_score: 0.26274, time: 208.62765 + +2021-04-28T12:20:33.107210 +LR: 0.001 +Emb_rate: 0.14171760000000003 +[RESULT]: Train. Epoch: 38, summary_loss: 0.36577, final_score: 0.13109, time: 703.35752 +[RESULT]: Val. Epoch: 38, summary_loss: 1.84810, final_score: 0.30020, time: 208.28293 + +2021-04-28T12:35:45.001299 +LR: 0.001 +Emb_rate: 0.14171760000000003 +[RESULT]: Train. Epoch: 39, summary_loss: 0.36320, final_score: 0.12859, time: 682.42444 +[RESULT]: Val. Epoch: 39, summary_loss: 3.20809, final_score: 0.30619, time: 206.52718 + +2021-04-28T12:50:34.270593 +LR: 0.001 +Emb_rate: 0.12754584000000002 +[RESULT]: Train. Epoch: 40, summary_loss: 0.37123, final_score: 0.13672, time: 686.84760 +[RESULT]: Val. Epoch: 40, summary_loss: 2.09923, final_score: 0.28921, time: 207.84924 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..b761732c62e5e02f8219557829a26a3c9bec30fe Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.1/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-019epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-019epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..0193c2c343605e33ca2fc50f48b47d4176d8465c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-019epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e6848c3972cacf864657207b02a4daf328358f6e4db1a63124a0b3f82dcf78c2 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-022epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-022epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f495b9e64b206c01c9c66e4536c53665981f31f7 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-022epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:de171dd071c8f99bf314a71b15ce0939d79f1ab3f9995855eae8c1a65341e332 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-023epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-023epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..5f1e336dc94ee9dd155cfb2c49e224b8fb29ad77 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/best-checkpoint-023epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8e6ef35865802d8995f0250816dcc9d9339fb1c845c1c9a6bb8082342643f761 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..9115aa697e9c17bbe6175a513af2567717458623 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:235bd2b741d85d5a6c1db01880e906dec8d672325c4e365bd78b77833ed3a155 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..fab456b586e32e3cbf9a4fc2f1eaabfb6607054e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_3_0.2/log.txt @@ -0,0 +1,200 @@ +Fitter prepared. Device is cuda:0 + +2021-04-26T08:50:31.331371 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.52695, final_score: 0.26531, time: 667.68201 +[RESULT]: Val. Epoch: 0, summary_loss: 1.64035, final_score: 0.49950, time: 206.97561 + +2021-04-26T09:05:06.487863 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.27181, final_score: 0.07398, time: 677.81942 +[RESULT]: Val. Epoch: 1, summary_loss: 2.33448, final_score: 0.50000, time: 207.03914 + +2021-04-26T09:19:51.527345 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.21958, final_score: 0.04324, time: 676.11247 +Fitter prepared. Device is cuda:0 + +2021-04-26T09:37:40.105987 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.51689, final_score: 0.24631, time: 658.93309 +[RESULT]: Val. Epoch: 0, summary_loss: 1.66347, final_score: 0.50000, time: 205.03070 + +2021-04-26T09:52:04.499356 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.23921, final_score: 0.05299, time: 684.10522 +[RESULT]: Val. Epoch: 1, summary_loss: 1.64712, final_score: 0.49900, time: 203.04202 + +2021-04-26T10:06:52.072355 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.20776, final_score: 0.03537, time: 658.28485 +[RESULT]: Val. Epoch: 2, summary_loss: 2.55084, final_score: 0.50000, time: 206.71596 + +2021-04-26T10:21:17.257603 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.21672, final_score: 0.04036, time: 665.44691 +[RESULT]: Val. Epoch: 3, summary_loss: 2.77565, final_score: 0.50000, time: 204.29789 + +2021-04-26T10:35:47.174164 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.19242, final_score: 0.02812, time: 665.77943 +[RESULT]: Val. Epoch: 4, summary_loss: 1.78202, final_score: 0.50000, time: 203.61472 + +2021-04-26T10:50:16.735081 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.25075, final_score: 0.06311, time: 658.56977 +[RESULT]: Val. Epoch: 5, summary_loss: 2.35209, final_score: 0.49950, time: 202.89468 + +2021-04-26T11:04:38.373293 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.23509, final_score: 0.05186, time: 664.20813 +[RESULT]: Val. Epoch: 6, summary_loss: 1.93404, final_score: 0.50000, time: 203.65672 + +2021-04-26T11:19:06.408360 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28555, final_score: 0.08010, time: 679.33425 +[RESULT]: Val. Epoch: 7, summary_loss: 2.45511, final_score: 0.49900, time: 203.94349 + +2021-04-26T11:33:49.868434 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.25204, final_score: 0.06348, time: 674.16033 +[RESULT]: Val. Epoch: 8, summary_loss: 2.73924, final_score: 0.49950, time: 203.68229 + +2021-04-26T11:48:27.894652 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.32024, final_score: 0.10397, time: 670.29461 +[RESULT]: Val. Epoch: 9, summary_loss: 5.95728, final_score: 0.49950, time: 202.89049 + +2021-04-26T12:03:01.246385 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.32922, final_score: 0.10947, time: 665.92099 +[RESULT]: Val. Epoch: 10, summary_loss: 3.49516, final_score: 0.50000, time: 203.92171 + +2021-04-26T12:17:31.269933 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.38777, final_score: 0.14471, time: 675.08509 +[RESULT]: Val. Epoch: 11, summary_loss: 1.49856, final_score: 0.49950, time: 202.95561 + +2021-04-26T12:32:09.665454 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.37489, final_score: 0.13672, time: 680.21116 +[RESULT]: Val. Epoch: 12, summary_loss: 1.58749, final_score: 0.49950, time: 203.70530 + +2021-04-26T12:46:53.749724 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44023, final_score: 0.17946, time: 669.43802 +[RESULT]: Val. Epoch: 13, summary_loss: 1.64554, final_score: 0.49800, time: 203.93827 + +2021-04-26T13:01:27.299002 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.42191, final_score: 0.17096, time: 676.64621 +[RESULT]: Val. Epoch: 14, summary_loss: 2.24370, final_score: 0.49151, time: 203.72827 + +2021-04-26T13:16:07.832932 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.47162, final_score: 0.20582, time: 685.08782 +[RESULT]: Val. Epoch: 15, summary_loss: 1.38231, final_score: 0.49451, time: 203.29741 + +2021-04-26T13:30:56.678055 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.46126, final_score: 0.19583, time: 670.03288 +[RESULT]: Val. Epoch: 16, summary_loss: 1.59151, final_score: 0.45804, time: 204.22642 + +2021-04-26T13:45:31.105349 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.49557, final_score: 0.22494, time: 688.80952 +[RESULT]: Val. Epoch: 17, summary_loss: 1.17195, final_score: 0.43856, time: 205.59447 + +2021-04-26T14:00:25.896853 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.48440, final_score: 0.20945, time: 684.51551 +[RESULT]: Val. Epoch: 18, summary_loss: 1.04760, final_score: 0.36813, time: 210.35243 + +2021-04-26T14:15:21.117052 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.50578, final_score: 0.22557, time: 694.74043 +[RESULT]: Val. Epoch: 19, summary_loss: 0.58701, final_score: 0.28671, time: 210.20594 + +2021-04-26T14:30:26.390917 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.49511, final_score: 0.21970, time: 691.52068 +[RESULT]: Val. Epoch: 20, summary_loss: 0.65544, final_score: 0.30769, time: 204.46743 + +2021-04-26T14:45:22.554878 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 21, summary_loss: 0.49293, final_score: 0.22007, time: 680.67821 +[RESULT]: Val. Epoch: 21, summary_loss: 1.16800, final_score: 0.32418, time: 203.67064 + +2021-04-26T15:00:07.095406 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 22, summary_loss: 0.48268, final_score: 0.20957, time: 712.32906 +[RESULT]: Val. Epoch: 22, summary_loss: 0.52160, final_score: 0.22428, time: 203.45800 + +2021-04-26T15:15:23.204233 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 23, summary_loss: 0.47919, final_score: 0.21357, time: 690.43168 +[RESULT]: Val. Epoch: 23, summary_loss: 0.50964, final_score: 0.22028, time: 208.41465 + +2021-04-26T15:30:22.386683 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 24, summary_loss: 0.46417, final_score: 0.19858, time: 696.33556 +[RESULT]: Val. Epoch: 24, summary_loss: 0.82923, final_score: 0.22777, time: 209.60743 + +2021-04-26T15:45:28.499047 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 25, summary_loss: 0.45298, final_score: 0.19195, time: 674.43471 +[RESULT]: Val. Epoch: 25, summary_loss: 1.12080, final_score: 0.24775, time: 204.99402 + +2021-04-26T16:00:08.104570 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 26, summary_loss: 0.43923, final_score: 0.17833, time: 685.52714 +[RESULT]: Val. Epoch: 26, summary_loss: 0.60589, final_score: 0.20779, time: 209.55517 + +2021-04-26T16:15:03.372350 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 27, summary_loss: 0.42671, final_score: 0.17208, time: 675.03748 +[RESULT]: Val. Epoch: 27, summary_loss: 0.55724, final_score: 0.22428, time: 203.73440 + +2021-04-26T16:29:42.420345 +LR: 0.001 +Emb_rate: 0.2745215094595321 +[RESULT]: Train. Epoch: 28, summary_loss: 0.42151, final_score: 0.16596, time: 681.38593 +[RESULT]: Val. Epoch: 28, summary_loss: 0.79479, final_score: 0.24575, time: 203.49926 + +2021-04-26T16:44:27.463874 +LR: 0.001 +Emb_rate: 0.24706935851357886 +[RESULT]: Train. Epoch: 29, summary_loss: 0.40995, final_score: 0.16146, time: 690.79693 +[RESULT]: Val. Epoch: 29, summary_loss: 2.73762, final_score: 0.36064, time: 203.95476 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:27:19.176668 +LR: 0.001 +Emb_rate: 1.2 +Fitter prepared. Device is cuda:0 + +2021-04-26T09:43:41.327503 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.63889, final_score: 0.36553, time: 751.46293 +[RESULT]: Val. Epoch: 0, summary_loss: 3.30784, final_score: 0.49850, time: 227.34682 + +2021-04-26T10:00:00.595547 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.25373, final_score: 0.06361, time: 783.07678 +[RESULT]: Val. Epoch: 1, summary_loss: 2.15665, final_score: 0.50000, time: 213.97724 + +2021-04-26T10:16:38.038530 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.19446, final_score: 0.02887, time: 805.66843 +[RESULT]: Val. Epoch: 2, summary_loss: 2.42055, final_score: 0.49950, time: 241.92908 + +2021-04-26T10:34:05.839246 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.22463, final_score: 0.04349, time: 756.89836 +[RESULT]: Val. Epoch: 3, summary_loss: 1.45529, final_score: 0.49900, time: 240.49926 + +2021-04-26T10:50:43.670453 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.21257, final_score: 0.03812, time: 742.67095 +[RESULT]: Val. Epoch: 4, summary_loss: 2.03169, final_score: 0.49900, time: 211.83724 + +2021-04-26T11:06:38.389051 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.23857, final_score: 0.05274, time: 786.61378 +[RESULT]: Val. Epoch: 5, summary_loss: 1.82372, final_score: 0.49950, time: 231.02863 + +2021-04-26T11:23:36.211853 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.24250, final_score: 0.05686, time: 787.27572 +[RESULT]: Val. Epoch: 6, summary_loss: 3.43616, final_score: 0.49850, time: 220.43129 + +2021-04-26T11:40:24.108723 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28924, final_score: 0.08373, time: 760.50872 +[RESULT]: Val. Epoch: 7, summary_loss: 2.79181, final_score: 0.49850, time: 259.18722 + +2021-04-26T11:57:23.993719 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.26760, final_score: 0.07036, time: 768.46976 +[RESULT]: Val. Epoch: 8, summary_loss: 1.55941, final_score: 0.49850, time: 224.52110 + +2021-04-26T12:13:57.183979 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.32093, final_score: 0.10535, time: 794.61614 +[RESULT]: Val. Epoch: 9, summary_loss: 4.66164, final_score: 0.50000, time: 212.53483 + +2021-04-26T12:30:44.510510 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.30720, final_score: 0.09348, time: 785.22759 +[RESULT]: Val. Epoch: 10, summary_loss: 2.99897, final_score: 0.49850, time: 223.73114 + +2021-04-26T12:47:33.675422 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.38270, final_score: 0.14234, time: 781.37816 +[RESULT]: Val. Epoch: 11, summary_loss: 2.97536, final_score: 0.49700, time: 214.31955 + +2021-04-26T13:04:09.551789 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.36896, final_score: 0.13497, time: 791.21776 +[RESULT]: Val. Epoch: 12, summary_loss: 2.18942, final_score: 0.49550, time: 259.32322 + +2021-04-26T13:21:40.283427 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.45033, final_score: 0.18908, time: 764.47211 +[RESULT]: Val. Epoch: 13, summary_loss: 2.38255, final_score: 0.48252, time: 259.72644 + +2021-04-26T13:38:44.705248 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.42947, final_score: 0.17333, time: 761.45846 +[RESULT]: Val. Epoch: 14, summary_loss: 2.89281, final_score: 0.46903, time: 237.20923 + +2021-04-26T13:55:23.576782 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.48386, final_score: 0.21170, time: 785.23619 +[RESULT]: Val. Epoch: 15, summary_loss: 0.98968, final_score: 0.42258, time: 223.59714 + +2021-04-26T14:12:12.991454 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.46797, final_score: 0.20182, time: 741.02182 +[RESULT]: Val. Epoch: 16, summary_loss: 1.00460, final_score: 0.41908, time: 243.56891 + +2021-04-26T14:28:37.765580 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.50314, final_score: 0.22957, time: 854.04312 +[RESULT]: Val. Epoch: 17, summary_loss: 0.86024, final_score: 0.38362, time: 215.21613 + +2021-04-26T14:46:27.440050 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.48717, final_score: 0.21557, time: 779.32309 +[RESULT]: Val. Epoch: 18, summary_loss: 1.26110, final_score: 0.36314, time: 234.49381 + +2021-04-26T15:03:22.249163 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.50924, final_score: 0.22632, time: 747.28143 +[RESULT]: Val. Epoch: 19, summary_loss: 1.19103, final_score: 0.28821, time: 206.64633 + +2021-04-26T15:19:16.361804 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.49242, final_score: 0.21582, time: 821.96047 +[RESULT]: Val. Epoch: 20, summary_loss: 0.66516, final_score: 0.31518, time: 214.50450 + +2021-04-26T15:36:33.243003 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 21, summary_loss: 0.49792, final_score: 0.22207, time: 813.37064 +[RESULT]: Val. Epoch: 21, summary_loss: 0.57878, final_score: 0.26823, time: 225.82752 + +2021-04-26T15:53:52.847656 +LR: 0.001 +Emb_rate: 0.3765727153080001 +[RESULT]: Train. Epoch: 22, summary_loss: 0.48277, final_score: 0.21045, time: 724.47636 +[RESULT]: Val. Epoch: 22, summary_loss: 0.54557, final_score: 0.24176, time: 224.54699 + +2021-04-26T16:09:42.280307 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 23, summary_loss: 0.47176, final_score: 0.20282, time: 762.45200 +[RESULT]: Val. Epoch: 23, summary_loss: 0.62227, final_score: 0.25175, time: 216.08188 + +2021-04-26T16:26:01.037721 +LR: 0.001 +Emb_rate: 0.3389154437772001 +[RESULT]: Train. Epoch: 24, summary_loss: 0.45931, final_score: 0.19345, time: 720.03909 +[RESULT]: Val. Epoch: 24, summary_loss: 0.87039, final_score: 0.24326, time: 231.75784 + +2021-04-26T16:41:53.023850 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 25, summary_loss: 0.44798, final_score: 0.18220, time: 784.49626 +[RESULT]: Val. Epoch: 25, summary_loss: 1.91181, final_score: 0.23676, time: 247.58658 + +2021-04-26T16:59:05.360971 +LR: 0.001 +Emb_rate: 0.3050238993994801 +[RESULT]: Train. Epoch: 26, summary_loss: 0.44431, final_score: 0.18483, time: 795.64845 +[RESULT]: Val. Epoch: 26, summary_loss: 0.64143, final_score: 0.25225, time: 238.50467 + +2021-04-26T17:16:19.713685 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 27, summary_loss: 0.43190, final_score: 0.17571, time: 830.31281 +[RESULT]: Val. Epoch: 27, summary_loss: 0.60047, final_score: 0.21429, time: 254.44267 + +2021-04-26T17:34:24.663183 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 28, summary_loss: 0.42739, final_score: 0.16983, time: 802.35233 +[RESULT]: Val. Epoch: 28, summary_loss: 0.52063, final_score: 0.21578, time: 260.02768 + +2021-04-26T17:52:07.465295 +LR: 0.001 +Emb_rate: 0.3 +[RESULT]: Train. Epoch: 29, summary_loss: 0.42212, final_score: 0.16908, time: 762.42699 +[RESULT]: Val. Epoch: 29, summary_loss: 0.49199, final_score: 0.18581, time: 231.08803 +Fitter prepared. 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Device is cuda:0 + +2021-04-26T09:26:56.512772 +LR: 0.001 +Emb_rate: 1.2 +Fitter prepared. Device is cuda:0 + +2021-04-26T09:37:40.354199 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.45831, final_score: 0.20482, time: 675.03005 +[RESULT]: Val. Epoch: 0, summary_loss: 1.33632, final_score: 0.43856, time: 199.72044 + +2021-04-26T09:52:15.578120 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.25561, final_score: 0.06236, time: 672.17219 +[RESULT]: Val. Epoch: 1, summary_loss: 0.81795, final_score: 0.40659, time: 212.89124 + +2021-04-26T10:07:01.139645 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.22822, final_score: 0.04899, time: 687.32931 +[RESULT]: Val. Epoch: 2, summary_loss: 0.92381, final_score: 0.41359, time: 213.30312 + +2021-04-26T10:22:01.982416 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.24118, final_score: 0.05574, time: 703.89663 +[RESULT]: Val. Epoch: 3, summary_loss: 1.52796, final_score: 0.39510, time: 216.97245 + +2021-04-26T10:37:23.046906 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.22841, final_score: 0.04886, time: 696.72759 +[RESULT]: Val. Epoch: 4, summary_loss: 1.50082, final_score: 0.40310, time: 214.77195 + +2021-04-26T10:52:34.777906 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.26949, final_score: 0.07211, time: 697.82921 +[RESULT]: Val. Epoch: 5, summary_loss: 0.86536, final_score: 0.37413, time: 215.55218 + +2021-04-26T11:07:48.349089 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.25324, final_score: 0.06448, time: 704.51238 +[RESULT]: Val. Epoch: 6, summary_loss: 1.27039, final_score: 0.39061, time: 215.20175 + +2021-04-26T11:23:08.265514 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.30243, final_score: 0.08985, time: 698.12147 +[RESULT]: Val. Epoch: 7, summary_loss: 1.63375, final_score: 0.39510, time: 215.72380 + +2021-04-26T11:38:22.291426 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.28125, final_score: 0.08198, time: 696.77479 +[RESULT]: Val. Epoch: 8, summary_loss: 1.84140, final_score: 0.36913, time: 216.35911 + +2021-04-26T11:53:35.605031 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.36361, final_score: 0.12959, time: 711.91891 +[RESULT]: Val. Epoch: 9, summary_loss: 2.98215, final_score: 0.39610, time: 216.30519 + +2021-04-26T12:09:04.017159 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.33748, final_score: 0.11497, time: 703.59252 +[RESULT]: Val. Epoch: 10, summary_loss: 2.10540, final_score: 0.40859, time: 216.50637 + +2021-04-26T12:24:24.301477 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.41364, final_score: 0.16558, time: 713.53902 +[RESULT]: Val. Epoch: 11, summary_loss: 0.74160, final_score: 0.32867, time: 215.02397 + +2021-04-26T12:39:53.347998 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.40050, final_score: 0.15496, time: 713.25096 +[RESULT]: Val. Epoch: 12, summary_loss: 0.66695, final_score: 0.30969, time: 216.63458 + +2021-04-26T12:55:23.680862 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.45687, final_score: 0.19358, time: 719.67258 +[RESULT]: Val. Epoch: 13, summary_loss: 0.63055, final_score: 0.31968, time: 215.05857 + +2021-04-26T13:10:58.841812 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.45304, final_score: 0.19533, time: 717.02093 +[RESULT]: Val. Epoch: 14, summary_loss: 0.56606, final_score: 0.27522, time: 216.08497 + +2021-04-26T13:26:32.406733 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.50644, final_score: 0.23394, time: 720.31339 +[RESULT]: Val. Epoch: 15, summary_loss: 0.65421, final_score: 0.31419, time: 216.16046 + +2021-04-26T13:42:09.058072 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.49544, final_score: 0.22494, time: 718.26714 +[RESULT]: Val. Epoch: 16, summary_loss: 1.02487, final_score: 0.29421, time: 216.20373 + +2021-04-26T13:57:43.746757 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 17, summary_loss: 0.50185, final_score: 0.23069, time: 717.41987 +[RESULT]: Val. Epoch: 17, summary_loss: 0.54195, final_score: 0.23876, time: 211.12163 + +2021-04-26T14:13:12.770352 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 18, summary_loss: 0.48434, final_score: 0.21495, time: 716.04747 +[RESULT]: Val. Epoch: 18, summary_loss: 0.77416, final_score: 0.27373, time: 216.18467 + +2021-04-26T14:28:45.311736 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 19, summary_loss: 0.47928, final_score: 0.21632, time: 721.95117 +[RESULT]: Val. Epoch: 19, summary_loss: 0.49855, final_score: 0.23477, time: 218.15612 + +2021-04-26T14:44:25.894845 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 20, summary_loss: 0.46231, final_score: 0.19258, time: 714.02724 +[RESULT]: Val. Epoch: 20, summary_loss: 1.05797, final_score: 0.29570, time: 214.29239 + +2021-04-26T14:59:54.458239 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 21, summary_loss: 0.45630, final_score: 0.19008, time: 713.94870 +[RESULT]: Val. Epoch: 21, summary_loss: 0.47714, final_score: 0.21479, time: 216.71757 + +2021-04-26T15:15:25.604126 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 22, summary_loss: 0.44326, final_score: 0.18570, time: 721.52252 +[RESULT]: Val. Epoch: 22, summary_loss: 0.47063, final_score: 0.19780, time: 216.86653 + +2021-04-26T15:31:04.448378 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 23, summary_loss: 0.43975, final_score: 0.18420, time: 713.52268 +[RESULT]: Val. Epoch: 23, summary_loss: 0.80331, final_score: 0.23327, time: 212.28179 + +2021-04-26T15:46:30.474892 +LR: 0.001 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 24, summary_loss: 0.42810, final_score: 0.17408, time: 714.66213 +[RESULT]: Val. Epoch: 24, summary_loss: 1.66185, final_score: 0.26374, time: 216.08413 + +2021-04-26T16:02:01.450445 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 25, summary_loss: 0.39489, final_score: 0.15396, time: 721.67571 +[RESULT]: Val. Epoch: 25, summary_loss: 0.46313, final_score: 0.17732, time: 213.25198 + +2021-04-26T16:17:36.959104 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 26, summary_loss: 0.38847, final_score: 0.14396, time: 713.82764 +[RESULT]: Val. Epoch: 26, summary_loss: 0.59978, final_score: 0.19031, time: 216.37953 + +2021-04-26T16:33:07.382786 +LR: 0.0005 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 27, summary_loss: 0.38544, final_score: 0.14946, time: 719.72215 +[RESULT]: Val. Epoch: 27, summary_loss: 0.51674, final_score: 0.17932, time: 218.45084 + +2021-04-26T16:48:45.767749 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 28, summary_loss: 0.36143, final_score: 0.13234, time: 722.80904 +[RESULT]: Val. Epoch: 28, summary_loss: 0.47029, final_score: 0.16733, time: 214.77856 + +2021-04-26T17:04:23.575289 +LR: 0.00025 +Emb_rate: 0.5 +[RESULT]: Train. Epoch: 29, summary_loss: 0.35808, final_score: 0.12822, time: 727.64872 +[RESULT]: Val. Epoch: 29, summary_loss: 0.44502, final_score: 0.16883, time: 213.44717 +Fitter prepared. 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Device is cuda:0 + +2021-04-25T01:44:38.127534 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.57519, final_score: 0.29268, time: 657.35253 +[RESULT]: Val. Epoch: 0, summary_loss: 1.58751, final_score: 0.47403, time: 207.62215 + +2021-04-25T01:59:03.476942 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.25540, final_score: 0.06223, time: 645.82340 +[RESULT]: Val. Epoch: 1, summary_loss: 1.98783, final_score: 0.48302, time: 205.41457 + +2021-04-25T02:13:14.893595 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.20187, final_score: 0.03324, time: 662.68838 +[RESULT]: Val. Epoch: 2, summary_loss: 1.92979, final_score: 0.47602, time: 204.12998 + +2021-04-25T02:27:41.907763 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.21896, final_score: 0.04324, time: 656.25616 +[RESULT]: Val. Epoch: 3, summary_loss: 1.13568, final_score: 0.47103, time: 203.85315 + +2021-04-25T02:42:02.365469 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.19997, final_score: 0.03137, time: 659.21033 +[RESULT]: Val. Epoch: 4, summary_loss: 2.29100, final_score: 0.47453, time: 203.40709 + +2021-04-25T02:56:25.145813 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24925, final_score: 0.05849, time: 671.47125 +[RESULT]: Val. Epoch: 5, summary_loss: 1.53753, final_score: 0.47153, time: 204.30961 + +2021-04-25T03:11:01.109629 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22987, final_score: 0.04599, time: 653.66722 +[RESULT]: Val. Epoch: 6, summary_loss: 1.95367, final_score: 0.47053, time: 203.71008 + +2021-04-25T03:25:18.662854 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28185, final_score: 0.07848, time: 671.07701 +[RESULT]: Val. Epoch: 7, summary_loss: 2.52477, final_score: 0.46703, time: 204.65722 + +2021-04-25T03:39:54.602758 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.26846, final_score: 0.07223, time: 662.55891 +[RESULT]: Val. Epoch: 8, summary_loss: 1.67781, final_score: 0.46503, time: 204.09381 + +2021-04-25T03:54:21.419820 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.34194, final_score: 0.11585, time: 665.67141 +[RESULT]: Val. Epoch: 9, summary_loss: 2.00164, final_score: 0.47053, time: 204.05712 + +2021-04-25T04:08:51.374557 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.32622, final_score: 0.10772, time: 671.16381 +[RESULT]: Val. Epoch: 10, summary_loss: 1.80299, final_score: 0.46503, time: 203.83420 + +2021-04-25T04:23:26.563502 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.40644, final_score: 0.15921, time: 669.85727 +[RESULT]: Val. Epoch: 11, summary_loss: 1.20507, final_score: 0.44855, time: 204.04871 + +2021-04-25T04:38:00.662832 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.38978, final_score: 0.14271, time: 672.67203 +[RESULT]: Val. Epoch: 12, summary_loss: 2.45753, final_score: 0.45155, time: 203.95450 + +2021-04-25T04:52:37.463681 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47666, final_score: 0.20820, time: 671.98049 +[RESULT]: Val. Epoch: 13, summary_loss: 1.99105, final_score: 0.47253, time: 204.79491 + +2021-04-25T05:07:14.420138 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.47132, final_score: 0.20570, time: 676.85669 +[RESULT]: Val. Epoch: 14, summary_loss: 0.99391, final_score: 0.43357, time: 204.16529 + +2021-04-25T05:21:55.787571 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54772, final_score: 0.26756, time: 674.95191 +[RESULT]: Val. Epoch: 15, summary_loss: 1.06537, final_score: 0.42707, time: 203.38223 + +2021-04-25T05:36:34.405711 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.53604, final_score: 0.25906, time: 674.86458 +[RESULT]: Val. Epoch: 16, summary_loss: 1.34175, final_score: 0.44955, time: 203.40287 + +2021-04-25T05:51:12.870550 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.59546, final_score: 0.31530, time: 679.37136 +[RESULT]: Val. Epoch: 17, summary_loss: 0.93011, final_score: 0.41459, time: 203.61021 + +2021-04-25T06:05:56.288843 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.58624, final_score: 0.30680, time: 675.06850 +[RESULT]: Val. Epoch: 18, summary_loss: 2.16578, final_score: 0.43257, time: 203.84593 + +2021-04-25T06:20:35.378917 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.62702, final_score: 0.34941, time: 676.39633 +[RESULT]: Val. Epoch: 19, summary_loss: 1.00437, final_score: 0.40410, time: 203.62092 + +2021-04-25T06:35:15.592340 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.62355, final_score: 0.34316, time: 676.56427 +[RESULT]: Val. Epoch: 20, summary_loss: 0.67825, final_score: 0.38412, time: 204.05454 + +2021-04-25T06:49:56.550953 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.63171, final_score: 0.35354, time: 672.68895 +[RESULT]: Val. Epoch: 21, summary_loss: 0.64911, final_score: 0.36414, time: 206.56607 + +2021-04-25T07:04:36.218772 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.62587, final_score: 0.34929, time: 687.85116 +[RESULT]: Val. Epoch: 22, summary_loss: 0.66475, final_score: 0.38711, time: 208.06392 + +2021-04-25T07:19:32.475210 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.61857, final_score: 0.34254, time: 682.04283 +[RESULT]: Val. Epoch: 23, summary_loss: 0.63577, final_score: 0.36414, time: 207.43192 + +2021-04-25T07:34:22.373820 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.61854, final_score: 0.34766, time: 694.96475 +[RESULT]: Val. Epoch: 24, summary_loss: 0.72694, final_score: 0.37512, time: 206.05129 + +2021-04-25T07:49:23.593524 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.61232, final_score: 0.33817, time: 677.09249 +[RESULT]: Val. Epoch: 25, summary_loss: 0.67692, final_score: 0.35714, time: 206.97400 + +2021-04-25T08:04:07.873299 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.59609, final_score: 0.32329, time: 689.93556 +[RESULT]: Val. Epoch: 26, summary_loss: 0.76962, final_score: 0.37413, time: 204.75671 + +2021-04-25T08:19:02.740650 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.58674, final_score: 0.30867, time: 681.58222 +[RESULT]: Val. Epoch: 27, summary_loss: 0.80671, final_score: 0.36314, time: 203.75225 + +2021-04-25T08:33:48.249778 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.57023, final_score: 0.29868, time: 684.65369 +[RESULT]: Val. Epoch: 28, summary_loss: 0.70936, final_score: 0.35564, time: 203.38599 + +2021-04-25T08:48:36.464563 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.56430, final_score: 0.29143, time: 680.28235 +[RESULT]: Val. Epoch: 29, summary_loss: 0.71090, final_score: 0.35215, time: 205.14647 +Fitter prepared. Device is cuda:0 + +2021-04-26T00:51:15.574295 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.54588, final_score: 0.27256, time: 731.71172 +[RESULT]: Val. Epoch: 0, summary_loss: 1.43949, final_score: 0.48951, time: 212.00594 + +2021-04-26T01:06:59.657254 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.24640, final_score: 0.05661, time: 736.43947 +[RESULT]: Val. Epoch: 1, summary_loss: 1.71014, final_score: 0.48551, time: 244.33584 + +2021-04-26T01:23:20.609972 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.19512, final_score: 0.02762, time: 685.83979 +[RESULT]: Val. Epoch: 2, summary_loss: 2.93172, final_score: 0.49201, time: 226.72925 + +2021-04-26T01:38:33.373609 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.21503, final_score: 0.03662, time: 707.31482 +[RESULT]: Val. Epoch: 3, summary_loss: 1.69078, final_score: 0.48701, time: 227.72630 + +2021-04-26T01:54:08.653986 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.20043, final_score: 0.03112, time: 710.02928 +[RESULT]: Val. Epoch: 4, summary_loss: 1.89298, final_score: 0.48352, time: 214.43589 + +2021-04-26T02:09:33.623108 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24968, final_score: 0.05911, time: 723.90607 +[RESULT]: Val. Epoch: 5, summary_loss: 1.18794, final_score: 0.48551, time: 229.08717 + +2021-04-26T02:25:27.015016 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22361, final_score: 0.04486, time: 744.96087 +[RESULT]: Val. Epoch: 6, summary_loss: 2.58819, final_score: 0.48452, time: 241.94943 + +2021-04-26T02:41:54.101179 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28812, final_score: 0.07948, time: 787.01440 +[RESULT]: Val. Epoch: 7, summary_loss: 3.40034, final_score: 0.48302, time: 220.13551 + +2021-04-26T02:58:41.425592 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.25940, final_score: 0.06661, time: 763.83590 +[RESULT]: Val. Epoch: 8, summary_loss: 1.86380, final_score: 0.47203, time: 223.35602 + +2021-04-26T03:15:08.825264 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.33368, final_score: 0.11035, time: 746.52029 +[RESULT]: Val. Epoch: 9, summary_loss: 1.51183, final_score: 0.47602, time: 214.24487 + +2021-04-26T03:31:09.798990 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.32644, final_score: 0.10510, time: 764.78510 +[RESULT]: Val. Epoch: 10, summary_loss: 0.98799, final_score: 0.46853, time: 219.99596 + +2021-04-26T03:47:34.938109 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39878, final_score: 0.15121, time: 753.82704 +[RESULT]: Val. Epoch: 11, summary_loss: 1.57407, final_score: 0.46603, time: 224.07263 + +2021-04-26T04:03:53.012096 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.38202, final_score: 0.13897, time: 742.90887 +[RESULT]: Val. Epoch: 12, summary_loss: 2.13003, final_score: 0.46054, time: 219.40731 + +2021-04-26T04:19:55.503419 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.46553, final_score: 0.20070, time: 731.71911 +[RESULT]: Val. Epoch: 13, summary_loss: 1.33620, final_score: 0.45305, time: 216.00371 + +2021-04-26T04:35:43.401693 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.45551, final_score: 0.19358, time: 762.51292 +[RESULT]: Val. Epoch: 14, summary_loss: 1.77481, final_score: 0.44106, time: 212.00395 + +2021-04-26T04:51:58.082752 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.52131, final_score: 0.24069, time: 765.05748 +[RESULT]: Val. Epoch: 15, summary_loss: 0.89556, final_score: 0.40509, time: 213.82335 + +2021-04-26T05:08:17.316166 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.51450, final_score: 0.23257, time: 753.78333 +[RESULT]: Val. Epoch: 16, summary_loss: 0.73900, final_score: 0.40360, time: 212.31389 + +2021-04-26T05:24:23.769478 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.56344, final_score: 0.27706, time: 788.76350 +[RESULT]: Val. Epoch: 17, summary_loss: 0.70601, final_score: 0.38012, time: 229.83603 + +2021-04-26T05:41:22.729274 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.55814, final_score: 0.27306, time: 807.12736 +[RESULT]: Val. Epoch: 18, summary_loss: 2.38023, final_score: 0.43856, time: 209.51845 + +2021-04-26T05:58:19.736173 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.58722, final_score: 0.30055, time: 765.83919 +[RESULT]: Val. Epoch: 19, summary_loss: 1.05829, final_score: 0.37463, time: 214.33652 + +2021-04-26T06:14:40.247551 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.57781, final_score: 0.29118, time: 747.82587 +[RESULT]: Val. Epoch: 20, summary_loss: 0.74401, final_score: 0.34965, time: 213.81925 + +2021-04-26T06:30:42.070932 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.58219, final_score: 0.29568, time: 780.24385 +[RESULT]: Val. Epoch: 21, summary_loss: 0.62706, final_score: 0.31019, time: 212.77311 + +2021-04-26T06:47:15.478584 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.57585, final_score: 0.28693, time: 746.43904 +[RESULT]: Val. Epoch: 22, summary_loss: 0.63927, final_score: 0.32318, time: 213.34169 + +2021-04-26T07:03:15.435007 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.56906, final_score: 0.28518, time: 763.37815 +[RESULT]: Val. Epoch: 23, summary_loss: 0.74384, final_score: 0.36613, time: 212.70461 + +2021-04-26T07:19:31.724621 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.54953, final_score: 0.26706, time: 748.11610 +[RESULT]: Val. Epoch: 24, summary_loss: 0.59152, final_score: 0.29471, time: 220.70644 + +2021-04-26T07:35:40.983672 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.53721, final_score: 0.25844, time: 754.11865 +[RESULT]: Val. Epoch: 25, summary_loss: 0.65589, final_score: 0.29471, time: 211.49802 + +2021-04-26T07:51:46.824784 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.53528, final_score: 0.25331, time: 757.76284 +[RESULT]: Val. Epoch: 26, summary_loss: 0.71581, final_score: 0.32767, time: 249.81220 + +2021-04-26T08:08:34.574648 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.52330, final_score: 0.24269, time: 720.64223 +[RESULT]: Val. Epoch: 27, summary_loss: 0.57054, final_score: 0.27572, time: 215.27999 + +2021-04-26T08:24:10.920179 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.51215, final_score: 0.23919, time: 778.28602 +[RESULT]: Val. Epoch: 28, summary_loss: 0.58603, final_score: 0.27572, time: 212.88804 + +2021-04-26T08:40:42.282607 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.51258, final_score: 0.23857, time: 773.52610 +[RESULT]: Val. Epoch: 29, summary_loss: 0.67722, final_score: 0.28372, time: 218.21543 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_4/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_4/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..4d2955e07a2c300fdfc48d050d7ab76feffdbd65 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_4/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-023epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-023epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..5693ccffbdae5d29d4d94643922dd2ec6544f1bc --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-023epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7dc31bd782b6b79cafacc88dd4c057f36e82c78c7bc63512ac77d69e99e211e1 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..b2c7fd5de689ea76589c21ef227ceacb5530eede --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4fd30d8d24caf02adb7bc0b40631b8aa8dfbfd05d3317450d9549f048bd2df22 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-025epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-025epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..c58be96b68bbea3a76e035b4071e14fd9ba1ea64 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/best-checkpoint-025epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bf8934e4d13a9e0e001cdfaf5a8074315349486e40618675f6c87e5c9e0c2df5 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..623db332e6d442810cb40ea550d64bca56c4b46e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b313dfa8af27b6411360c81161118bbe78dc145e38c005f24ad48d7b88848c68 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..480a1a3c683460fcf01c1f3f1fd77802fc88fe2f --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-04-28T09:17:03.079102 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.72076, final_score: 0.44626, time: 687.36632 +[RESULT]: Val. Epoch: 0, summary_loss: 2.16182, final_score: 0.49051, time: 201.68500 + +2021-04-28T09:31:52.495089 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.32373, final_score: 0.10372, time: 673.54068 +[RESULT]: Val. Epoch: 1, summary_loss: 2.81898, final_score: 0.47552, time: 203.87077 + +2021-04-28T09:46:30.099379 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.20551, final_score: 0.03449, time: 661.95903 +[RESULT]: Val. Epoch: 2, summary_loss: 1.52131, final_score: 0.46503, time: 204.89573 + +2021-04-28T10:00:57.347064 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.23097, final_score: 0.04561, time: 655.25764 +[RESULT]: Val. Epoch: 3, summary_loss: 1.79543, final_score: 0.46204, time: 203.75988 + +2021-04-28T10:15:16.543245 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.20160, final_score: 0.03287, time: 667.33771 +[RESULT]: Val. Epoch: 4, summary_loss: 2.86872, final_score: 0.48202, time: 202.49279 + +2021-04-28T10:29:46.544153 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.24780, final_score: 0.05886, time: 667.58622 +[RESULT]: Val. Epoch: 5, summary_loss: 2.03048, final_score: 0.46154, time: 206.12107 + +2021-04-28T10:44:20.461330 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.23551, final_score: 0.05036, time: 663.41558 +[RESULT]: Val. Epoch: 6, summary_loss: 1.05778, final_score: 0.45904, time: 202.52133 + +2021-04-28T10:58:46.837538 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.28506, final_score: 0.08135, time: 665.48190 +[RESULT]: Val. Epoch: 7, summary_loss: 1.23643, final_score: 0.45355, time: 203.46848 + +2021-04-28T11:13:16.031098 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.26719, final_score: 0.07186, time: 666.07373 +[RESULT]: Val. Epoch: 8, summary_loss: 2.47907, final_score: 0.45854, time: 204.21058 + +2021-04-28T11:27:46.497198 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.32535, final_score: 0.10660, time: 672.58189 +[RESULT]: Val. Epoch: 9, summary_loss: 1.33497, final_score: 0.45455, time: 203.59528 + +2021-04-28T11:42:22.847042 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.31112, final_score: 0.09623, time: 671.43524 +[RESULT]: Val. Epoch: 10, summary_loss: 1.45318, final_score: 0.44755, time: 203.36583 + +2021-04-28T11:56:57.903834 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.40567, final_score: 0.15496, time: 674.91461 +[RESULT]: Val. Epoch: 11, summary_loss: 0.88991, final_score: 0.42957, time: 206.72844 + +2021-04-28T12:11:39.967310 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.38717, final_score: 0.14546, time: 680.48974 +[RESULT]: Val. Epoch: 12, summary_loss: 0.93955, final_score: 0.44406, time: 202.22652 + +2021-04-28T12:26:22.917096 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47471, final_score: 0.20945, time: 676.44493 +[RESULT]: Val. Epoch: 13, summary_loss: 1.40557, final_score: 0.44406, time: 205.14617 + +2021-04-28T12:41:04.717260 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.46488, final_score: 0.20057, time: 681.58189 +[RESULT]: Val. Epoch: 14, summary_loss: 1.04488, final_score: 0.43956, time: 206.76650 + +2021-04-28T12:55:53.299406 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54068, final_score: 0.26756, time: 679.11722 +[RESULT]: Val. Epoch: 15, summary_loss: 0.98963, final_score: 0.42058, time: 205.22576 + +2021-04-28T13:10:37.822521 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.53357, final_score: 0.25219, time: 683.37380 +[RESULT]: Val. Epoch: 16, summary_loss: 1.26544, final_score: 0.43906, time: 204.31003 + +2021-04-28T13:25:25.709211 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.59812, final_score: 0.31480, time: 679.87638 +[RESULT]: Val. Epoch: 17, summary_loss: 0.98206, final_score: 0.42507, time: 204.38314 + +2021-04-28T13:40:10.160747 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.58749, final_score: 0.31030, time: 683.06263 +[RESULT]: Val. Epoch: 18, summary_loss: 0.77237, final_score: 0.42657, time: 204.38597 + +2021-04-28T13:54:58.022313 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.64038, final_score: 0.36741, time: 684.10613 +[RESULT]: Val. Epoch: 19, summary_loss: 0.78988, final_score: 0.40859, time: 202.48048 + +2021-04-28T14:09:44.777201 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.63145, final_score: 0.35929, time: 682.64827 +[RESULT]: Val. Epoch: 20, summary_loss: 0.68601, final_score: 0.39411, time: 204.80238 + +2021-04-28T14:24:32.598521 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.64914, final_score: 0.37891, time: 697.59643 +[RESULT]: Val. Epoch: 21, summary_loss: 0.68819, final_score: 0.39461, time: 202.29644 + +2021-04-28T14:39:32.671943 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.64107, final_score: 0.36878, time: 686.54189 +[RESULT]: Val. Epoch: 22, summary_loss: 0.92549, final_score: 0.43457, time: 201.70626 + +2021-04-28T14:54:21.095761 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.63552, final_score: 0.36453, time: 692.55005 +[RESULT]: Val. Epoch: 23, summary_loss: 0.66898, final_score: 0.37612, time: 201.72017 + +2021-04-28T15:09:15.748077 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.62976, final_score: 0.36303, time: 693.77677 +[RESULT]: Val. Epoch: 24, summary_loss: 0.66221, final_score: 0.37862, time: 203.20384 + +2021-04-28T15:24:13.051926 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.62749, final_score: 0.35191, time: 691.40835 +[RESULT]: Val. Epoch: 25, summary_loss: 0.64237, final_score: 0.36813, time: 206.94574 + +2021-04-28T15:39:11.820640 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.62336, final_score: 0.34841, time: 693.43598 +[RESULT]: Val. Epoch: 26, summary_loss: 0.87615, final_score: 0.38711, time: 208.34547 + +2021-04-28T15:54:13.764787 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.62107, final_score: 0.35204, time: 695.49289 +[RESULT]: Val. Epoch: 27, summary_loss: 0.78731, final_score: 0.39261, time: 209.58349 + +2021-04-28T16:09:19.006500 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.60938, final_score: 0.33654, time: 694.86755 +[RESULT]: Val. Epoch: 28, summary_loss: 0.70300, final_score: 0.36264, time: 206.94745 + +2021-04-28T16:24:20.992134 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.60396, final_score: 0.33317, time: 696.80940 +[RESULT]: Val. Epoch: 29, summary_loss: 0.65423, final_score: 0.35714, time: 207.03813 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..a819f2d198c2e939ad30e0f7a622f46f1ae8445c Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_5/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-021epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-021epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a5686b455969262055c3df2f36ca74534137d57e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-021epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:93b434f71abc6c4e3a6d1ba959e874139704bc2641a11d982a141bd582eecdfa +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-026epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-026epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..9c306c977ccbfe77ee674d467c06d2ad7129bd86 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-026epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:380d9d6f4d63c3eb1447a7dfb1559ad85879b0df9b1dd5ccb932c1be3cc7a1bb +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..3ecaea095254115fbba4141dd9c8afe0862211c7 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:71334206f8bfe0f9df4ccd73068475e7878c18773b3c10db3760c5a0dee48ba0 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..8144669c15067df73cb28a3863e8fcbc1d0d0a22 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:200623a43d4e61882ecacf2b82979e32aa63f30c7e09fa1e722f6ab7f3f4e27f +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..75f659fade530e2cf855933d859db4e1cfdacf12 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-10T19:19:47.201076 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.46984, final_score: 0.20970, time: 669.39783 +[RESULT]: Val. Epoch: 0, summary_loss: 1.49312, final_score: 0.46603, time: 207.34879 + +2021-06-10T19:34:24.337460 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.21728, final_score: 0.03799, time: 664.47242 +[RESULT]: Val. Epoch: 1, summary_loss: 1.13414, final_score: 0.45804, time: 206.48844 + +2021-06-10T19:48:55.755460 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.20556, final_score: 0.03262, time: 661.07343 +[RESULT]: Val. Epoch: 2, summary_loss: 2.81443, final_score: 0.47902, time: 205.22899 + +2021-06-10T20:03:22.321790 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.21793, final_score: 0.03999, time: 665.31948 +[RESULT]: Val. Epoch: 3, summary_loss: 1.24304, final_score: 0.45604, time: 205.20164 + +2021-06-10T20:17:53.026295 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.19009, final_score: 0.02449, time: 671.33521 +[RESULT]: Val. Epoch: 4, summary_loss: 1.74208, final_score: 0.45604, time: 205.83335 + +2021-06-10T20:32:30.555153 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.23487, final_score: 0.05024, time: 671.23533 +[RESULT]: Val. Epoch: 5, summary_loss: 1.64425, final_score: 0.45904, time: 203.74089 + +2021-06-10T20:47:05.731656 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.22788, final_score: 0.04549, time: 683.48632 +[RESULT]: Val. Epoch: 6, summary_loss: 5.09686, final_score: 0.47802, time: 203.25732 + +2021-06-10T21:01:52.661225 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.27065, final_score: 0.07036, time: 683.79004 +[RESULT]: Val. Epoch: 7, summary_loss: 1.77465, final_score: 0.46553, time: 203.27433 + +2021-06-10T21:16:39.904523 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.26725, final_score: 0.06748, time: 681.93149 +[RESULT]: Val. Epoch: 8, summary_loss: 2.01071, final_score: 0.46204, time: 203.99995 + +2021-06-10T21:31:26.106224 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.32331, final_score: 0.10160, time: 682.58605 +[RESULT]: Val. Epoch: 9, summary_loss: 1.05715, final_score: 0.44805, time: 204.66720 + +2021-06-10T21:46:13.786302 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.32530, final_score: 0.10510, time: 688.10499 +[RESULT]: Val. Epoch: 10, summary_loss: 2.98367, final_score: 0.46354, time: 206.67440 + +2021-06-10T22:01:08.757426 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.39588, final_score: 0.15246, time: 688.29119 +[RESULT]: Val. Epoch: 11, summary_loss: 2.20241, final_score: 0.45055, time: 203.71555 + +2021-06-10T22:16:00.960842 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.39175, final_score: 0.15159, time: 684.28280 +[RESULT]: Val. Epoch: 12, summary_loss: 1.47414, final_score: 0.44705, time: 202.46403 + +2021-06-10T22:30:47.958377 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.48051, final_score: 0.21545, time: 676.22770 +[RESULT]: Val. Epoch: 13, summary_loss: 1.31230, final_score: 0.45954, time: 202.76624 + +2021-06-10T22:45:27.147472 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.46413, final_score: 0.20007, time: 692.55273 +[RESULT]: Val. Epoch: 14, summary_loss: 0.94769, final_score: 0.43157, time: 202.31893 + +2021-06-10T23:00:22.693618 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.53892, final_score: 0.25919, time: 681.47723 +[RESULT]: Val. Epoch: 15, summary_loss: 0.76455, final_score: 0.42757, time: 202.28529 + +2021-06-10T23:15:06.809363 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.52999, final_score: 0.25181, time: 687.64653 +[RESULT]: Val. Epoch: 16, summary_loss: 1.37281, final_score: 0.44605, time: 205.69005 + +2021-06-10T23:30:00.341947 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.60028, final_score: 0.31905, time: 688.46086 +[RESULT]: Val. Epoch: 17, summary_loss: 0.85325, final_score: 0.41608, time: 203.67487 + +2021-06-10T23:44:52.718610 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.59229, final_score: 0.31317, time: 685.23175 +[RESULT]: Val. Epoch: 18, summary_loss: 0.81835, final_score: 0.42657, time: 202.24881 + +2021-06-10T23:59:40.510488 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.63657, final_score: 0.36866, time: 688.13578 +[RESULT]: Val. Epoch: 19, summary_loss: 0.71016, final_score: 0.40909, time: 202.18198 + +2021-06-11T00:14:31.238227 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.63241, final_score: 0.36016, time: 686.34146 +[RESULT]: Val. Epoch: 20, summary_loss: 1.03550, final_score: 0.42507, time: 202.75284 + +2021-06-11T00:29:20.596792 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.64795, final_score: 0.38253, time: 684.35915 +[RESULT]: Val. Epoch: 21, summary_loss: 0.67622, final_score: 0.40310, time: 202.57003 + +2021-06-11T00:44:07.961491 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.64210, final_score: 0.37478, time: 684.88590 +[RESULT]: Val. Epoch: 22, summary_loss: 0.75024, final_score: 0.41409, time: 202.78727 + +2021-06-11T00:58:55.973788 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.63896, final_score: 0.36966, time: 682.32556 +[RESULT]: Val. Epoch: 23, summary_loss: 0.71570, final_score: 0.38911, time: 203.56125 + +2021-06-11T01:13:42.066199 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.62614, final_score: 0.35579, time: 683.13363 +[RESULT]: Val. Epoch: 24, summary_loss: 0.71589, final_score: 0.39710, time: 203.28610 + +2021-06-11T01:28:28.647066 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.62175, final_score: 0.34904, time: 681.10799 +[RESULT]: Val. Epoch: 25, summary_loss: 0.78766, final_score: 0.38561, time: 202.29533 + +2021-06-11T01:43:12.218961 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.61337, final_score: 0.33904, time: 685.77027 +[RESULT]: Val. Epoch: 26, summary_loss: 0.67402, final_score: 0.36663, time: 205.54237 + +2021-06-11T01:58:03.981524 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.60675, final_score: 0.33304, time: 683.42066 +[RESULT]: Val. Epoch: 27, summary_loss: 0.66303, final_score: 0.36763, time: 204.23750 + +2021-06-11T02:12:52.041063 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.60493, final_score: 0.32867, time: 685.40360 +[RESULT]: Val. Epoch: 28, summary_loss: 0.68369, final_score: 0.37413, time: 202.41460 + +2021-06-11T02:27:40.162456 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.60413, final_score: 0.33717, time: 685.64939 +[RESULT]: Val. Epoch: 29, summary_loss: 0.67185, final_score: 0.36264, time: 202.86535 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/p_error/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/p_error/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..828605cfa4a13922368053ddd9e8dab85ee7c5eb Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_6/p_error/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-023epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-023epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..9116cea52cdfc2c87fd51a8183329c34ac6d9477 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-023epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:31bd54f273197174be448b336e5fd8058855e945ef16d66e1c4348bbb012d5d4 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-024epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-024epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..3c091269fa513daf871a81c1b625065269ba0b1e --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-024epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4107a5bf195e6343bba4a038f5c118e03b04593e19bb51c35a67e27f5724507e +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-027epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-027epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..30ba01956d4dd9edfc3112432d8f51f05e8f5af8 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/best-checkpoint-027epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a2aa28309bdd55758d3b6861effc0d4876938c6a8c7302f967d447177ea96abe +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..d6e2ef57449b948b7b7caf775a25bf7cf3cbde00 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7765e911e529311d681625abd75fda612f13b8bfba417f04ec2478b85644f959 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..740a36c8798addfce07c1ef321a59269e3e9b939 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_7/log.txt @@ -0,0 +1,181 @@ +Fitter prepared. Device is cuda:0 + +2021-06-11T15:46:08.730149 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.42571, final_score: 0.18608, time: 663.62564 +[RESULT]: Val. Epoch: 0, summary_loss: 1.40447, final_score: 0.47802, time: 210.28822 + +2021-06-11T16:00:42.996310 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.21537, final_score: 0.03949, time: 669.51251 +[RESULT]: Val. Epoch: 1, summary_loss: 1.83501, final_score: 0.47552, time: 208.21981 + +2021-06-11T16:15:20.898271 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.17074, final_score: 0.01475, time: 666.82929 +[RESULT]: Val. Epoch: 2, summary_loss: 1.22591, final_score: 0.46054, time: 207.68415 + +2021-06-11T16:29:55.797221 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.21060, final_score: 0.03699, time: 683.04671 +[RESULT]: Val. Epoch: 3, summary_loss: 1.62604, final_score: 0.46503, time: 204.48885 + +2021-06-11T16:44:43.507288 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.19492, final_score: 0.02974, time: 666.03741 +[RESULT]: Val. Epoch: 4, summary_loss: 1.99898, final_score: 0.46953, time: 207.14507 + +2021-06-11T16:59:16.852560 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.23269, final_score: 0.05161, time: 673.99393 +[RESULT]: Val. Epoch: 5, summary_loss: 2.47895, final_score: 0.47652, time: 207.43454 + +2021-06-11T17:13:58.455054 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.21369, final_score: 0.04049, time: 676.39750 +[RESULT]: Val. Epoch: 6, summary_loss: 1.54958, final_score: 0.44156, time: 205.75080 + +2021-06-11T17:28:40.762191 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.25722, final_score: 0.06536, time: 679.10952 +[RESULT]: Val. Epoch: 7, summary_loss: 1.20403, final_score: 0.43556, time: 206.05103 + +2021-06-11T17:43:26.268815 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.24896, final_score: 0.06036, time: 676.38517 +[RESULT]: Val. Epoch: 8, summary_loss: 2.56761, final_score: 0.45355, time: 205.07628 + +2021-06-11T17:58:07.895457 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.32062, final_score: 0.10335, time: 680.45377 +[RESULT]: Val. Epoch: 9, summary_loss: 1.49816, final_score: 0.45255, time: 205.68594 + +2021-06-11T18:12:54.248573 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.30306, final_score: 0.09348, time: 690.28350 +[RESULT]: Val. Epoch: 10, summary_loss: 1.91997, final_score: 0.45654, time: 205.70484 + +2021-06-11T18:27:50.414176 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.38390, final_score: 0.14671, time: 685.62405 +[RESULT]: Val. Epoch: 11, summary_loss: 1.17636, final_score: 0.44206, time: 206.31174 + +2021-06-11T18:42:42.671756 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.36328, final_score: 0.13297, time: 684.58247 +[RESULT]: Val. Epoch: 12, summary_loss: 0.93691, final_score: 0.44156, time: 206.09913 + +2021-06-11T18:57:33.699607 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44125, final_score: 0.19070, time: 684.46879 +[RESULT]: Val. Epoch: 13, summary_loss: 0.88344, final_score: 0.43556, time: 206.19237 + +2021-06-11T19:12:24.704829 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.43800, final_score: 0.18458, time: 692.59859 +[RESULT]: Val. Epoch: 14, summary_loss: 1.16624, final_score: 0.41508, time: 203.74919 + +2021-06-11T19:27:21.225642 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.51206, final_score: 0.23757, time: 697.28507 +[RESULT]: Val. Epoch: 15, summary_loss: 1.20056, final_score: 0.42458, time: 207.88482 + +2021-06-11T19:42:26.593670 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.51489, final_score: 0.24956, time: 685.03554 +[RESULT]: Val. Epoch: 16, summary_loss: 0.99689, final_score: 0.42757, time: 208.07804 + +2021-06-11T19:57:19.891568 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.57189, final_score: 0.29605, time: 694.94306 +[RESULT]: Val. Epoch: 17, summary_loss: 0.76127, final_score: 0.39960, time: 205.14963 + +2021-06-11T20:12:20.391083 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.56852, final_score: 0.29205, time: 689.19444 +[RESULT]: Val. Epoch: 18, summary_loss: 0.92938, final_score: 0.42657, time: 205.88470 + +2021-06-11T20:27:15.715004 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.62115, final_score: 0.34716, time: 689.42575 +[RESULT]: Val. Epoch: 19, summary_loss: 0.76167, final_score: 0.41508, time: 207.96423 + +2021-06-11T20:42:13.300319 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.61647, final_score: 0.34266, time: 688.34402 +[RESULT]: Val. Epoch: 20, summary_loss: 1.22405, final_score: 0.43157, time: 205.97105 + +2021-06-11T20:57:07.819266 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.63225, final_score: 0.36516, time: 692.87682 +[RESULT]: Val. Epoch: 21, summary_loss: 0.71704, final_score: 0.39960, time: 205.68641 + +2021-06-11T21:12:06.754212 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.63042, final_score: 0.36103, time: 693.14638 +[RESULT]: Val. Epoch: 22, summary_loss: 0.83860, final_score: 0.40959, time: 206.82210 + +2021-06-11T21:27:06.901331 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.62843, final_score: 0.36153, time: 700.07687 +[RESULT]: Val. Epoch: 23, summary_loss: 0.68313, final_score: 0.38262, time: 205.83387 + +2021-06-11T21:42:13.160223 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.62909, final_score: 0.36091, time: 691.58331 +[RESULT]: Val. Epoch: 24, summary_loss: 0.66488, final_score: 0.38212, time: 207.06302 + +2021-06-11T21:57:12.141055 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.62836, final_score: 0.35791, time: 690.03032 +[RESULT]: Val. Epoch: 25, summary_loss: 0.70249, final_score: 0.40559, time: 207.66177 + +2021-06-11T22:12:10.042755 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.62363, final_score: 0.35254, time: 697.49768 +[RESULT]: Val. Epoch: 26, summary_loss: 0.74445, final_score: 0.40060, time: 208.30950 + +2021-06-11T22:27:16.058799 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.60688, final_score: 0.34141, time: 690.85699 +[RESULT]: Val. Epoch: 27, summary_loss: 0.66130, final_score: 0.36214, time: 206.89672 + +2021-06-11T22:42:14.201327 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.60372, final_score: 0.33317, time: 695.68848 +[RESULT]: Val. Epoch: 28, summary_loss: 0.68243, final_score: 0.37263, time: 205.73838 + +2021-06-11T22:57:15.792166 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.60136, final_score: 0.33054, time: 690.81108 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T12:55:22.630832 +LR: 0.001 +Emb_rate: 1.2 +Fitter prepared. Device is cuda:0 + +2021-06-25T12:58:18.790351 +LR: 0.001 +Emb_rate: 1.2 +Fitter prepared. Device is cuda:0 + +2021-06-25T13:07:01.368832 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.73446, final_score: 0.49838, time: 111.13417 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69378, final_score: 0.49550, time: 32.83594 + +2021-06-25T13:09:25.744286 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69342, final_score: 0.49638, time: 91.62950 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69320, final_score: 0.48951, time: 26.75422 + +2021-06-25T13:11:24.468287 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69085, final_score: 0.47051, time: 92.41708 +[RESULT]: Val. Epoch: 2, summary_loss: 1.08113, final_score: 0.48102, time: 26.27322 + +2021-06-25T13:13:23.320956 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.68161, final_score: 0.43564, time: 91.43521 +[RESULT]: Val. Epoch: 3, summary_loss: 0.97471, final_score: 0.47303, time: 26.43233 + +2021-06-25T13:15:21.382652 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.66102, final_score: 0.39303, time: 90.25668 +[RESULT]: Val. Epoch: 4, summary_loss: 1.12363, final_score: 0.43706, time: 26.39587 + +2021-06-25T13:17:18.200622 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.62603, final_score: 0.33892, time: 90.91511 +[RESULT]: Val. Epoch: 5, summary_loss: 1.49882, final_score: 0.41359, time: 26.31770 + +2021-06-25T13:19:15.598248 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.59905, final_score: 0.30717, time: 93.01556 +[RESULT]: Val. Epoch: 6, summary_loss: 0.81680, final_score: 0.35614, time: 26.30480 + +2021-06-25T13:21:15.102413 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.56744, final_score: 0.27706, time: 93.30545 +[RESULT]: Val. Epoch: 7, summary_loss: 1.51717, final_score: 0.32567, time: 26.70336 + +2021-06-25T13:23:15.288391 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.55521, final_score: 0.26643, time: 91.35354 +[RESULT]: Val. Epoch: 8, summary_loss: 1.82578, final_score: 0.38611, time: 26.36872 + +2021-06-25T13:25:13.196253 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.53459, final_score: 0.25169, time: 92.21858 +[RESULT]: Val. Epoch: 9, summary_loss: 0.63135, final_score: 0.28771, time: 26.26996 + +2021-06-25T13:27:12.036842 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.52508, final_score: 0.24531, time: 92.47006 +[RESULT]: Val. Epoch: 10, summary_loss: 0.65355, final_score: 0.28771, time: 25.92795 + +2021-06-25T13:29:10.604974 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.50830, final_score: 0.23182, time: 92.84406 +[RESULT]: Val. Epoch: 11, summary_loss: 0.59817, final_score: 0.22877, time: 27.11560 + +2021-06-25T13:31:10.944915 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.49954, final_score: 0.22632, time: 93.63755 +[RESULT]: Val. Epoch: 12, summary_loss: 0.80060, final_score: 0.29570, time: 26.84618 + +2021-06-25T13:33:11.600459 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.47327, final_score: 0.20582, time: 95.09385 +[RESULT]: Val. Epoch: 13, summary_loss: 0.55482, final_score: 0.21229, time: 26.12797 + +2021-06-25T13:35:13.171330 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.47017, final_score: 0.20282, time: 93.79077 +[RESULT]: Val. Epoch: 14, summary_loss: 0.61621, final_score: 0.27722, time: 26.84154 + +2021-06-25T13:37:14.055072 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.46013, final_score: 0.19745, time: 93.04424 +[RESULT]: Val. Epoch: 15, summary_loss: 0.78093, final_score: 0.30869, time: 26.10475 + +2021-06-25T13:39:13.395814 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.45890, final_score: 0.19545, time: 93.48888 +[RESULT]: Val. Epoch: 16, summary_loss: 0.58030, final_score: 0.22827, time: 26.02379 + +2021-06-25T13:41:13.074235 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.45201, final_score: 0.19108, time: 90.53256 +[RESULT]: Val. Epoch: 17, summary_loss: 0.73241, final_score: 0.23427, time: 26.39008 + +2021-06-25T13:43:10.156956 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.44202, final_score: 0.18495, time: 93.57011 +[RESULT]: Val. Epoch: 18, summary_loss: 1.22128, final_score: 0.29720, time: 26.87367 + +2021-06-25T13:45:10.777572 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.43349, final_score: 0.18158, time: 93.73033 +[RESULT]: Val. Epoch: 19, summary_loss: 0.58537, final_score: 0.21628, time: 26.46318 + +2021-06-25T13:47:11.150406 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.42575, final_score: 0.17658, time: 94.66544 +[RESULT]: Val. Epoch: 20, summary_loss: 1.28832, final_score: 0.24126, time: 27.71574 + +2021-06-25T13:49:13.702373 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.41649, final_score: 0.16433, time: 94.33719 +[RESULT]: Val. Epoch: 21, summary_loss: 0.70959, final_score: 0.25624, time: 27.43609 + +2021-06-25T13:51:15.656601 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.40665, final_score: 0.15696, time: 94.98939 +[RESULT]: Val. Epoch: 22, summary_loss: 0.56413, final_score: 0.21878, time: 26.70102 + +2021-06-25T13:53:17.513313 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.39976, final_score: 0.15671, time: 94.81677 +[RESULT]: Val. Epoch: 23, summary_loss: 0.59093, final_score: 0.20330, time: 27.49440 + +2021-06-25T13:55:19.983729 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.40271, final_score: 0.15959, time: 93.71080 +[RESULT]: Val. Epoch: 24, summary_loss: 0.81983, final_score: 0.24975, time: 26.67982 + +2021-06-25T13:57:20.567527 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.36716, final_score: 0.13184, time: 96.86995 +[RESULT]: Val. Epoch: 25, summary_loss: 0.64819, final_score: 0.19630, time: 26.81084 + +2021-06-25T13:59:24.433661 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.35999, final_score: 0.12559, time: 93.62694 +[RESULT]: Val. Epoch: 26, summary_loss: 0.66466, final_score: 0.22228, time: 26.81236 + +2021-06-25T14:01:25.050518 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.32818, final_score: 0.11072, time: 93.64050 +[RESULT]: Val. Epoch: 27, summary_loss: 0.60287, final_score: 0.20330, time: 26.51553 + +2021-06-25T14:03:25.370919 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.32672, final_score: 0.10772, time: 90.89624 +[RESULT]: Val. Epoch: 28, summary_loss: 0.53478, final_score: 0.17782, time: 26.44898 + +2021-06-25T14:05:23.070132 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.31713, final_score: 0.10085, time: 93.66560 +[RESULT]: Val. Epoch: 29, summary_loss: 0.52616, final_score: 0.18332, time: 26.49338 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:45.598848 +LR: 0.000125 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.37217, final_score: 0.13984, time: 97.65524 +[RESULT]: Val. Epoch: 30, summary_loss: 0.48564, final_score: 0.18931, time: 30.53014 + +2021-06-26T08:56:54.195073 +LR: 0.000125 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 31, summary_loss: 0.37016, final_score: 0.13634, time: 92.90333 +[RESULT]: Val. Epoch: 31, summary_loss: 0.47642, final_score: 0.18581, time: 26.62365 + +2021-06-26T08:58:54.095059 +LR: 0.000125 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 32, summary_loss: 0.36466, final_score: 0.13472, time: 93.69856 +[RESULT]: Val. Epoch: 32, summary_loss: 0.46373, final_score: 0.18332, time: 26.70628 + +2021-06-26T09:00:54.849586 +LR: 0.000125 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.36137, final_score: 0.13309, time: 94.43152 +[RESULT]: Val. Epoch: 33, summary_loss: 0.47023, final_score: 0.19381, time: 26.78824 + +2021-06-26T09:02:56.240702 +LR: 0.000125 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.35910, final_score: 0.13234, time: 94.18977 +[RESULT]: Val. Epoch: 34, summary_loss: 0.51978, final_score: 0.18581, time: 27.15020 + +2021-06-26T09:04:57.774932 +LR: 0.000125 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.35895, final_score: 0.13272, time: 93.77634 +[RESULT]: Val. Epoch: 35, summary_loss: 0.54709, final_score: 0.20929, time: 26.41698 + +2021-06-26T09:06:58.137808 +LR: 0.000125 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.35630, final_score: 0.13072, time: 93.70343 +[RESULT]: Val. Epoch: 36, summary_loss: 0.52367, final_score: 0.17882, time: 26.24896 + +2021-06-26T09:08:58.270644 +LR: 0.000125 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.34924, final_score: 0.12584, time: 94.04265 +[RESULT]: Val. Epoch: 37, summary_loss: 0.49694, final_score: 0.18382, time: 26.55239 + +2021-06-26T09:10:59.036067 +LR: 0.000125 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.35134, final_score: 0.12647, time: 93.65509 +[RESULT]: Val. Epoch: 38, summary_loss: 0.50441, final_score: 0.18781, time: 27.00727 + +2021-06-26T09:12:59.884220 +LR: 0.000125 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.34407, final_score: 0.12359, time: 93.45072 +[RESULT]: Val. Epoch: 39, summary_loss: 0.48896, final_score: 0.17932, time: 26.24423 + +2021-06-26T09:14:59.753095 +LR: 0.000125 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.34587, final_score: 0.12559, time: 92.97832 +[RESULT]: Val. Epoch: 40, summary_loss: 0.67072, final_score: 0.22677, time: 26.46089 + +2021-06-26T09:16:59.374065 +LR: 0.000125 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.33807, final_score: 0.11560, time: 94.66201 +[RESULT]: Val. Epoch: 41, summary_loss: 0.49552, final_score: 0.18082, time: 26.82114 + +2021-06-26T09:19:01.030157 +LR: 0.000125 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.33965, final_score: 0.11822, time: 94.31378 +[RESULT]: Val. Epoch: 42, summary_loss: 0.51181, final_score: 0.19331, time: 27.08081 + +2021-06-26T09:21:02.591299 +LR: 0.000125 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 43, summary_loss: 0.33733, final_score: 0.11635, time: 93.30225 +[RESULT]: Val. Epoch: 43, summary_loss: 0.82327, final_score: 0.20330, time: 26.72871 + +2021-06-26T09:23:02.788337 +LR: 0.000125 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 44, summary_loss: 0.33416, final_score: 0.11535, time: 93.97211 +[RESULT]: Val. Epoch: 44, summary_loss: 0.50709, final_score: 0.18482, time: 28.19489 + +2021-06-26T09:25:05.132031 +LR: 0.000125 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 45, summary_loss: 0.33264, final_score: 0.11385, time: 96.39408 +[RESULT]: Val. Epoch: 45, summary_loss: 0.51801, final_score: 0.17732, time: 26.77805 + +2021-06-26T09:27:08.545446 +LR: 0.000125 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 46, summary_loss: 0.32645, final_score: 0.11022, time: 95.46185 +[RESULT]: Val. Epoch: 46, summary_loss: 0.46844, final_score: 0.17582, time: 28.76571 + +2021-06-26T09:29:12.959539 +LR: 0.000125 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 47, summary_loss: 0.32121, final_score: 0.10797, time: 94.90948 +[RESULT]: Val. Epoch: 47, summary_loss: 0.48355, final_score: 0.18182, time: 27.08986 + +2021-06-26T09:31:15.141456 +LR: 0.000125 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 48, summary_loss: 0.32086, final_score: 0.10147, time: 97.38224 +[RESULT]: Val. Epoch: 48, summary_loss: 0.63337, final_score: 0.17333, time: 26.97280 + +2021-06-26T09:33:19.686720 +LR: 0.000125 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 49, summary_loss: 0.32008, final_score: 0.10422, time: 93.71527 +[RESULT]: Val. Epoch: 49, summary_loss: 0.55483, final_score: 0.19780, time: 26.77048 + +2021-06-26T09:35:20.347258 +LR: 0.000125 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 50, summary_loss: 0.31663, final_score: 0.10485, time: 96.29278 +[RESULT]: Val. Epoch: 50, summary_loss: 0.52606, final_score: 0.18681, time: 26.98395 + +2021-06-26T09:37:23.811552 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.31386, final_score: 0.09735, time: 95.99069 +[RESULT]: Val. Epoch: 51, summary_loss: 0.75812, final_score: 0.19830, time: 27.13539 + +2021-06-26T09:39:27.112067 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.30657, final_score: 0.09560, time: 96.74377 +[RESULT]: Val. Epoch: 52, summary_loss: 0.46112, final_score: 0.17283, time: 27.25492 + +2021-06-26T09:41:31.503649 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.29958, final_score: 0.09173, time: 96.58630 +[RESULT]: Val. Epoch: 53, summary_loss: 0.48113, final_score: 0.17283, time: 26.76529 + +2021-06-26T09:43:35.053783 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.29665, final_score: 0.08935, time: 96.72644 +[RESULT]: Val. Epoch: 54, summary_loss: 0.59282, final_score: 0.17832, time: 27.33035 + +2021-06-26T09:45:39.301578 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.29593, final_score: 0.08773, time: 93.17107 +[RESULT]: Val. Epoch: 55, summary_loss: 0.46631, final_score: 0.17133, time: 26.52681 + +2021-06-26T09:47:39.183202 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.28850, final_score: 0.08623, time: 97.48012 +[RESULT]: Val. Epoch: 56, summary_loss: 0.46882, final_score: 0.17333, time: 26.95663 + +2021-06-26T09:49:43.803659 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.28930, final_score: 0.08335, time: 95.93409 +[RESULT]: Val. Epoch: 57, summary_loss: 0.46886, final_score: 0.16933, time: 27.33763 + +2021-06-26T09:51:47.250412 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.28975, final_score: 0.08460, time: 97.35658 +[RESULT]: Val. Epoch: 58, summary_loss: 0.47102, final_score: 0.17083, time: 27.17674 + +2021-06-26T09:53:51.950035 +LR: 7.8125e-06 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.28465, final_score: 0.07861, time: 96.19712 +[RESULT]: Val. Epoch: 59, summary_loss: 0.46858, final_score: 0.17033, time: 26.87433 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..bdd5131e8b8d99c3e685bff331981736aaa34ad1 Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-029epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-029epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..11ccafbdf89781cb328291452c2c69b9eeaf1507 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-029epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:01c4bb7cb552f1c6e30b127786041bbd0f4b98a73807a99991552d11b0eb286c +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-034epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-034epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..4a69292ba467dc2d9a65098fa243808f4c812d91 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-034epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:64f954fefe8a73c5f72119e8c450e79fd13968fb7c53e9aa463df754087acf1f +size 69172566 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-036epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-036epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..0fbbac7e90989a0a17d7eb87e85724ab73f72a3c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/best-checkpoint-036epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d24192adfa3a101cc362de65325d8b7d9372432b034a7fe55aebe3436830b1e6 +size 69172566 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..e70c426f009ba614bed0631773f8ac7d9e0643f9 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:92b67befb33d988d9e6ef54314eed8a21da52bf5f118580813ca334037c458d0 +size 69172566 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..2755480f94e51c6f90ec494d012253f01582034c --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_2/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T16:56:37.651360 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.72709, final_score: 0.49813, time: 105.30422 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69382, final_score: 0.49700, time: 31.48556 + +2021-06-25T16:58:54.826176 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69366, final_score: 0.49788, time: 90.80809 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69339, final_score: 0.49650, time: 25.85338 + +2021-06-25T17:00:51.825504 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69333, final_score: 0.49713, time: 87.98778 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69322, final_score: 0.49401, time: 26.01081 + +2021-06-25T17:02:46.159829 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69317, final_score: 0.49488, time: 93.28953 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69325, final_score: 0.48701, time: 25.94451 + +2021-06-25T17:04:45.573941 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69237, final_score: 0.48050, time: 89.92168 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69498, final_score: 0.48202, time: 26.55545 + +2021-06-25T17:06:42.262478 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.68831, final_score: 0.45814, time: 93.65534 +[RESULT]: Val. Epoch: 5, summary_loss: 0.71851, final_score: 0.45604, time: 25.89995 + +2021-06-25T17:08:42.001623 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.67117, final_score: 0.40927, time: 91.00221 +[RESULT]: Val. Epoch: 6, summary_loss: 0.68870, final_score: 0.38511, time: 26.51468 + +2021-06-25T17:10:39.888473 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.63792, final_score: 0.35191, time: 90.90818 +[RESULT]: Val. Epoch: 7, summary_loss: 0.80654, final_score: 0.34815, time: 26.05016 + +2021-06-25T17:12:37.030995 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.60451, final_score: 0.31105, time: 92.48518 +[RESULT]: Val. Epoch: 8, summary_loss: 0.83999, final_score: 0.33117, time: 26.23746 + +2021-06-25T17:14:35.926546 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.58483, final_score: 0.29143, time: 90.98567 +[RESULT]: Val. Epoch: 9, summary_loss: 0.92284, final_score: 0.36963, time: 26.11458 + +2021-06-25T17:16:33.224781 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.56831, final_score: 0.27068, time: 91.15269 +[RESULT]: Val. Epoch: 10, summary_loss: 1.05931, final_score: 0.31369, time: 26.35870 + +2021-06-25T17:18:30.908579 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.55379, final_score: 0.26693, time: 92.04271 +[RESULT]: Val. Epoch: 11, summary_loss: 0.72228, final_score: 0.29021, time: 26.47329 + +2021-06-25T17:20:29.585723 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.53888, final_score: 0.24844, time: 92.95194 +[RESULT]: Val. Epoch: 12, summary_loss: 0.57578, final_score: 0.27223, time: 26.14220 + +2021-06-25T17:22:29.036068 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.53362, final_score: 0.24794, time: 90.93793 +[RESULT]: Val. Epoch: 13, summary_loss: 1.11856, final_score: 0.40210, time: 26.67845 + +2021-06-25T17:24:26.814640 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.51869, final_score: 0.24044, time: 92.43479 +[RESULT]: Val. Epoch: 14, summary_loss: 1.25271, final_score: 0.27772, time: 26.60923 + +2021-06-25T17:26:26.105333 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.51096, final_score: 0.22894, time: 93.37928 +[RESULT]: Val. Epoch: 15, summary_loss: 0.82688, final_score: 0.29271, time: 25.95164 + +2021-06-25T17:28:25.597599 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.49975, final_score: 0.22419, time: 93.60636 +[RESULT]: Val. Epoch: 16, summary_loss: 0.72696, final_score: 0.30270, time: 26.59464 + +2021-06-25T17:30:25.971731 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.50373, final_score: 0.22419, time: 90.78837 +[RESULT]: Val. Epoch: 17, summary_loss: 0.63920, final_score: 0.25624, time: 26.13885 + +2021-06-25T17:32:23.081674 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.48579, final_score: 0.21395, time: 89.89214 +[RESULT]: Val. Epoch: 18, summary_loss: 0.64052, final_score: 0.25874, time: 25.86201 + +2021-06-25T17:34:19.047831 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.47903, final_score: 0.21132, time: 91.72062 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69698, final_score: 0.26174, time: 26.18711 + +2021-06-25T17:36:17.137574 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.47514, final_score: 0.20282, time: 93.67912 +[RESULT]: Val. Epoch: 20, summary_loss: 1.51772, final_score: 0.24825, time: 26.37578 + +2021-06-25T17:38:17.363669 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.46617, final_score: 0.19870, time: 91.62013 +[RESULT]: Val. Epoch: 21, summary_loss: 0.83199, final_score: 0.25075, time: 26.53045 + +2021-06-25T17:40:15.706674 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.45679, final_score: 0.19108, time: 92.95174 +[RESULT]: Val. Epoch: 22, summary_loss: 0.83976, final_score: 0.24376, time: 26.21160 + +2021-06-25T17:42:15.068595 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.45638, final_score: 0.19520, time: 89.67031 +[RESULT]: Val. Epoch: 23, summary_loss: 0.56424, final_score: 0.23676, time: 26.31174 + +2021-06-25T17:44:11.428357 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.44577, final_score: 0.18408, time: 92.91717 +[RESULT]: Val. Epoch: 24, summary_loss: 0.55948, final_score: 0.24026, time: 26.53326 + +2021-06-25T17:46:11.200224 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.44406, final_score: 0.18658, time: 90.68171 +[RESULT]: Val. Epoch: 25, summary_loss: 0.65519, final_score: 0.26074, time: 26.64271 + +2021-06-25T17:48:08.709159 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.42933, final_score: 0.17283, time: 90.73768 +[RESULT]: Val. Epoch: 26, summary_loss: 1.17679, final_score: 0.29171, time: 26.02287 + +2021-06-25T17:50:05.652047 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.40491, final_score: 0.15884, time: 90.36451 +[RESULT]: Val. Epoch: 27, summary_loss: 0.56654, final_score: 0.21828, time: 26.33545 + +2021-06-25T17:52:02.527662 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.38531, final_score: 0.14509, time: 93.31516 +[RESULT]: Val. Epoch: 28, summary_loss: 0.56346, final_score: 0.21778, time: 27.20268 + +2021-06-25T17:54:03.227582 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.36782, final_score: 0.13347, time: 93.64331 +[RESULT]: Val. Epoch: 29, summary_loss: 0.55278, final_score: 0.20180, time: 26.28194 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:45.825351 +LR: 0.00025 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 30, summary_loss: 0.49592, final_score: 0.21795, time: 92.25341 +[RESULT]: Val. Epoch: 30, summary_loss: 0.57017, final_score: 0.25724, time: 29.66334 + +2021-06-26T08:56:47.908155 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 31, summary_loss: 0.49014, final_score: 0.21595, time: 91.74696 +[RESULT]: Val. Epoch: 31, summary_loss: 0.59724, final_score: 0.25175, time: 25.73664 + +2021-06-26T08:58:45.569399 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 32, summary_loss: 0.48070, final_score: 0.21095, time: 89.09000 +[RESULT]: Val. Epoch: 32, summary_loss: 0.68420, final_score: 0.27722, time: 26.34026 + +2021-06-26T09:00:41.171289 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.47239, final_score: 0.20307, time: 89.29770 +[RESULT]: Val. Epoch: 33, summary_loss: 0.57392, final_score: 0.25325, time: 26.28376 + +2021-06-26T09:02:36.929847 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.46629, final_score: 0.20245, time: 90.77793 +[RESULT]: Val. Epoch: 34, summary_loss: 0.55840, final_score: 0.25075, time: 26.38085 + +2021-06-26T09:04:34.472983 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.46487, final_score: 0.20132, time: 92.17909 +[RESULT]: Val. Epoch: 35, summary_loss: 0.61222, final_score: 0.25375, time: 25.95869 + +2021-06-26T09:06:32.806840 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.45972, final_score: 0.19420, time: 91.02904 +[RESULT]: Val. Epoch: 36, summary_loss: 0.54439, final_score: 0.23377, time: 26.04622 + +2021-06-26T09:08:30.299031 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.44960, final_score: 0.19120, time: 91.88862 +[RESULT]: Val. Epoch: 37, summary_loss: 0.60691, final_score: 0.24426, time: 25.91317 + +2021-06-26T09:10:28.275313 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.44531, final_score: 0.18420, time: 90.07762 +[RESULT]: Val. Epoch: 38, summary_loss: 0.58448, final_score: 0.24126, time: 26.40617 + +2021-06-26T09:12:24.962146 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.44708, final_score: 0.18808, time: 92.49291 +[RESULT]: Val. Epoch: 39, summary_loss: 0.57727, final_score: 0.25724, time: 26.02673 + +2021-06-26T09:14:23.660061 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.43791, final_score: 0.17908, time: 92.29894 +[RESULT]: Val. Epoch: 40, summary_loss: 0.94893, final_score: 0.26573, time: 26.26456 + +2021-06-26T09:16:22.387317 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.43130, final_score: 0.17758, time: 91.57360 +[RESULT]: Val. Epoch: 41, summary_loss: 0.73495, final_score: 0.27123, time: 26.25756 + +2021-06-26T09:18:20.398473 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.42127, final_score: 0.16671, time: 92.09630 +[RESULT]: Val. Epoch: 42, summary_loss: 0.75360, final_score: 0.23826, time: 27.10974 + +2021-06-26T09:20:19.783107 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 43, summary_loss: 0.42170, final_score: 0.16933, time: 90.26316 +[RESULT]: Val. Epoch: 43, summary_loss: 0.64727, final_score: 0.24875, time: 26.55820 + +2021-06-26T09:22:16.780677 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 44, summary_loss: 0.41630, final_score: 0.16733, time: 91.68749 +[RESULT]: Val. Epoch: 44, summary_loss: 0.55470, final_score: 0.22727, time: 25.69683 + +2021-06-26T09:24:14.335151 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 45, summary_loss: 0.41235, final_score: 0.16258, time: 91.65277 +[RESULT]: Val. Epoch: 45, summary_loss: 0.57259, final_score: 0.23127, time: 26.06412 + +2021-06-26T09:26:12.244542 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 46, summary_loss: 0.41238, final_score: 0.16483, time: 91.80882 +[RESULT]: Val. Epoch: 46, summary_loss: 0.62448, final_score: 0.22478, time: 25.93871 + +2021-06-26T09:28:10.180031 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 47, summary_loss: 0.40044, final_score: 0.15334, time: 93.49811 +[RESULT]: Val. Epoch: 47, summary_loss: 0.56972, final_score: 0.22877, time: 26.13568 + +2021-06-26T09:30:09.995909 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 48, summary_loss: 0.39987, final_score: 0.15534, time: 91.47905 +[RESULT]: Val. Epoch: 48, summary_loss: 0.76101, final_score: 0.24426, time: 26.20075 + +2021-06-26T09:32:07.850882 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 49, summary_loss: 0.39195, final_score: 0.15034, time: 91.79958 +[RESULT]: Val. Epoch: 49, summary_loss: 0.68190, final_score: 0.24575, time: 26.00349 + +2021-06-26T09:34:05.859084 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 50, summary_loss: 0.38096, final_score: 0.14309, time: 89.20878 +[RESULT]: Val. Epoch: 50, summary_loss: 0.62277, final_score: 0.22328, time: 26.40451 + +2021-06-26T09:36:01.641088 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.38409, final_score: 0.14734, time: 92.03928 +[RESULT]: Val. Epoch: 51, summary_loss: 0.64830, final_score: 0.23576, time: 26.28069 + +2021-06-26T09:38:00.139229 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.36541, final_score: 0.13209, time: 90.25057 +[RESULT]: Val. Epoch: 52, summary_loss: 0.63881, final_score: 0.24126, time: 26.09083 + +2021-06-26T09:39:56.651050 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.35348, final_score: 0.12584, time: 91.42486 +[RESULT]: Val. Epoch: 53, summary_loss: 0.62094, final_score: 0.21928, time: 25.89097 + +2021-06-26T09:41:54.129938 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.34477, final_score: 0.11997, time: 92.72122 +[RESULT]: Val. Epoch: 54, summary_loss: 0.56652, final_score: 0.21878, time: 25.98456 + +2021-06-26T09:43:53.000106 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.33773, final_score: 0.11185, time: 91.89350 +[RESULT]: Val. Epoch: 55, summary_loss: 0.60505, final_score: 0.21628, time: 26.41704 + +2021-06-26T09:45:51.473581 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.33794, final_score: 0.11222, time: 92.22696 +[RESULT]: Val. Epoch: 56, summary_loss: 0.61859, final_score: 0.21878, time: 26.35815 + +2021-06-26T09:47:50.221097 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.32704, final_score: 0.10785, time: 91.92069 +[RESULT]: Val. Epoch: 57, summary_loss: 0.58576, final_score: 0.21179, time: 26.02524 + +2021-06-26T09:49:48.333599 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 58, summary_loss: 0.32696, final_score: 0.10897, time: 92.93401 +[RESULT]: Val. Epoch: 58, summary_loss: 0.58853, final_score: 0.21578, time: 25.51717 + +2021-06-26T09:51:46.950851 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 59, summary_loss: 0.32553, final_score: 0.10622, time: 92.97231 +[RESULT]: Val. Epoch: 59, summary_loss: 0.59006, final_score: 0.21129, time: 26.91379 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..49af53116a8b3a18649c93e7ba8dbabe5ba12e1b Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-009epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-009epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..f443f94c089cdd9fee0073745f1c104cf42d079a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-009epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3d1118076fcc0eda74057ed72993365b9d6f774be65def1729502b30fb4328cb +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-012epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-012epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..89723152f2bb22b6675a047c19c2b1f29003c565 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-012epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0e63e0e4f118f8ff1e0aba24c231b84370ec20bb177dc74242568381071b3e57 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-015epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-015epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..22f01ec94bd36c8f8d3ef9121137e39c1344ce46 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/best-checkpoint-015epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9d45db08905c714112f6528257c90836dbfb39308cd2772aabd517013a88bd75 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..1769676ed36a6333df77cdc90990dcf61b5ea321 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f023f0444620e35cbd5735aa0572b79b2b3b18c36183d5ece459f83df78c91fe +size 69172566 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..f1b4899e2869a8d9baf5dc394a7b95b19db6d069 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_3/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T16:56:42.029780 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.73304, final_score: 0.49775, time: 106.65634 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69507, final_score: 0.49500, time: 29.96007 + +2021-06-25T16:58:59.000773 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69476, final_score: 0.49638, time: 92.02085 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69349, final_score: 0.48951, time: 26.85649 + +2021-06-25T17:00:58.213162 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69153, final_score: 0.47663, time: 94.61112 +[RESULT]: Val. Epoch: 2, summary_loss: 0.77623, final_score: 0.47902, time: 26.66523 + +2021-06-25T17:02:59.668325 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.62445, final_score: 0.33642, time: 94.11812 +[RESULT]: Val. Epoch: 3, summary_loss: 1.28223, final_score: 0.43806, time: 26.46771 + +2021-06-25T17:05:00.417366 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.57626, final_score: 0.28693, time: 94.01227 +[RESULT]: Val. Epoch: 4, summary_loss: 0.82811, final_score: 0.30569, time: 26.71361 + +2021-06-25T17:07:01.324773 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.54089, final_score: 0.24906, time: 93.71722 +[RESULT]: Val. Epoch: 5, summary_loss: 0.65087, final_score: 0.27572, time: 27.70618 + +2021-06-25T17:09:03.091663 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.51383, final_score: 0.23244, time: 91.94190 +[RESULT]: Val. Epoch: 6, summary_loss: 1.24356, final_score: 0.23876, time: 26.60600 + +2021-06-25T17:11:01.812373 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.49852, final_score: 0.22157, time: 94.72511 +[RESULT]: Val. Epoch: 7, summary_loss: 0.70833, final_score: 0.24825, time: 26.83797 + +2021-06-25T17:13:03.570902 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.48372, final_score: 0.20732, time: 94.09734 +[RESULT]: Val. Epoch: 8, summary_loss: 0.69218, final_score: 0.22727, time: 27.03061 + +2021-06-25T17:15:04.875077 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.47201, final_score: 0.20307, time: 93.18508 +[RESULT]: Val. Epoch: 9, summary_loss: 0.51477, final_score: 0.22577, time: 26.88778 + +2021-06-25T17:17:05.320685 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.45836, final_score: 0.19120, time: 95.54773 +[RESULT]: Val. Epoch: 10, summary_loss: 0.52630, final_score: 0.24725, time: 26.85685 + +2021-06-25T17:19:07.899403 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.45072, final_score: 0.18983, time: 94.63775 +[RESULT]: Val. Epoch: 11, summary_loss: 0.60439, final_score: 0.24176, time: 27.08013 + +2021-06-25T17:21:09.806017 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.45086, final_score: 0.18645, time: 94.88283 +[RESULT]: Val. Epoch: 12, summary_loss: 0.48273, final_score: 0.20130, time: 26.68133 + +2021-06-25T17:23:11.728532 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.44423, final_score: 0.18120, time: 94.60943 +[RESULT]: Val. Epoch: 13, summary_loss: 1.47879, final_score: 0.33916, time: 27.40990 + +2021-06-25T17:25:13.911739 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.42715, final_score: 0.16683, time: 91.79803 +[RESULT]: Val. Epoch: 14, summary_loss: 0.49505, final_score: 0.20679, time: 26.60366 + +2021-06-25T17:27:12.556462 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.41943, final_score: 0.16671, time: 92.93488 +[RESULT]: Val. Epoch: 15, summary_loss: 0.46122, final_score: 0.19481, time: 26.97990 + +2021-06-25T17:29:12.835443 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.41717, final_score: 0.16521, time: 93.52364 +[RESULT]: Val. Epoch: 16, summary_loss: 1.30617, final_score: 0.20130, time: 26.52654 + +2021-06-25T17:31:13.057343 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.40068, final_score: 0.15134, time: 94.25449 +[RESULT]: Val. Epoch: 17, summary_loss: 0.88678, final_score: 0.29371, time: 26.83796 + +2021-06-25T17:33:14.322053 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.40293, final_score: 0.15271, time: 93.71139 +[RESULT]: Val. Epoch: 18, summary_loss: 0.55746, final_score: 0.19880, time: 26.99989 + +2021-06-25T17:35:15.238913 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.38811, final_score: 0.14609, time: 93.24405 +[RESULT]: Val. Epoch: 19, summary_loss: 0.82215, final_score: 0.22328, time: 26.60939 + +2021-06-25T17:37:15.261608 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.39053, final_score: 0.14709, time: 91.92685 +[RESULT]: Val. Epoch: 20, summary_loss: 0.49047, final_score: 0.17483, time: 27.16060 + +2021-06-25T17:39:14.546023 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.37986, final_score: 0.13934, time: 92.62770 +[RESULT]: Val. Epoch: 21, summary_loss: 0.92712, final_score: 0.29221, time: 26.68029 + +2021-06-25T17:41:14.026073 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.37773, final_score: 0.13472, time: 92.58721 +[RESULT]: Val. Epoch: 22, summary_loss: 0.83970, final_score: 0.24326, time: 26.59716 + +2021-06-25T17:43:13.447536 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.35173, final_score: 0.11985, time: 93.12854 +[RESULT]: Val. Epoch: 23, summary_loss: 0.51880, final_score: 0.18132, time: 26.68557 + +2021-06-25T17:45:13.452425 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.34464, final_score: 0.11485, time: 94.08140 +[RESULT]: Val. Epoch: 24, summary_loss: 0.62326, final_score: 0.18831, time: 26.59448 + +2021-06-25T17:47:14.316332 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.32434, final_score: 0.10447, time: 92.88538 +[RESULT]: Val. Epoch: 25, summary_loss: 0.47633, final_score: 0.16034, time: 26.69450 + +2021-06-25T17:49:14.117055 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.31642, final_score: 0.09698, time: 94.18202 +[RESULT]: Val. Epoch: 26, summary_loss: 0.57038, final_score: 0.18482, time: 26.62313 + +2021-06-25T17:51:15.093007 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.31191, final_score: 0.09385, time: 91.94276 +[RESULT]: Val. Epoch: 27, summary_loss: 0.47115, final_score: 0.16583, time: 26.97862 + +2021-06-25T17:53:14.208895 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.30956, final_score: 0.09260, time: 94.56201 +[RESULT]: Val. Epoch: 28, summary_loss: 0.60412, final_score: 0.18432, time: 26.92607 + +2021-06-25T17:55:15.897680 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.30538, final_score: 0.08985, time: 94.06492 +[RESULT]: Val. Epoch: 29, summary_loss: 0.51845, final_score: 0.17532, time: 26.54854 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:45.500601 +LR: 0.00025 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 28, summary_loss: 0.42440, final_score: 0.17408, time: 94.27172 +[RESULT]: Val. Epoch: 28, summary_loss: 0.63739, final_score: 0.24276, time: 28.41873 + +2021-06-26T08:56:48.378347 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 29, summary_loss: 0.41817, final_score: 0.16171, time: 92.34003 +[RESULT]: Val. Epoch: 29, summary_loss: 0.51926, final_score: 0.19980, time: 26.03594 + +2021-06-26T08:58:46.930550 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 30, summary_loss: 0.41238, final_score: 0.15996, time: 89.71259 +[RESULT]: Val. Epoch: 30, summary_loss: 0.53516, final_score: 0.18232, time: 25.85842 + +2021-06-26T09:00:42.666272 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.41048, final_score: 0.15971, time: 92.11312 +[RESULT]: Val. Epoch: 31, summary_loss: 0.69178, final_score: 0.19481, time: 26.33831 + +2021-06-26T09:02:41.289538 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.40356, final_score: 0.15359, time: 91.66145 +[RESULT]: Val. Epoch: 32, summary_loss: 0.56930, final_score: 0.20879, time: 26.38823 + +2021-06-26T09:04:39.533030 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.40431, final_score: 0.15796, time: 92.65079 +[RESULT]: Val. Epoch: 33, summary_loss: 0.70701, final_score: 0.20180, time: 26.25279 + +2021-06-26T09:06:38.613021 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.39698, final_score: 0.15196, time: 92.06260 +[RESULT]: Val. Epoch: 34, summary_loss: 0.54496, final_score: 0.19181, time: 25.73027 + +2021-06-26T09:08:36.568109 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.39517, final_score: 0.15159, time: 91.22365 +[RESULT]: Val. Epoch: 35, summary_loss: 0.87329, final_score: 0.26374, time: 25.89412 + +2021-06-26T09:10:33.869135 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.39175, final_score: 0.14846, time: 91.79996 +[RESULT]: Val. Epoch: 36, summary_loss: 0.48912, final_score: 0.19181, time: 25.95037 + +2021-06-26T09:12:31.813375 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.38559, final_score: 0.14234, time: 92.95642 +[RESULT]: Val. Epoch: 37, summary_loss: 0.55527, final_score: 0.17932, time: 26.19053 + +2021-06-26T09:14:31.131378 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.38359, final_score: 0.14484, time: 92.82383 +[RESULT]: Val. Epoch: 38, summary_loss: 0.65271, final_score: 0.19730, time: 25.78120 + +2021-06-26T09:16:29.910409 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.37588, final_score: 0.13922, time: 90.49892 +[RESULT]: Val. Epoch: 39, summary_loss: 1.14099, final_score: 0.26124, time: 26.45680 + +2021-06-26T09:18:27.040171 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.37551, final_score: 0.13522, time: 91.73666 +[RESULT]: Val. Epoch: 40, summary_loss: 0.87688, final_score: 0.26324, time: 26.28088 + +2021-06-26T09:20:25.243362 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.36995, final_score: 0.13659, time: 91.41387 +[RESULT]: Val. Epoch: 41, summary_loss: 0.60433, final_score: 0.19231, time: 26.11146 + +2021-06-26T09:22:22.942601 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.36699, final_score: 0.13097, time: 91.06804 +[RESULT]: Val. Epoch: 42, summary_loss: 0.58570, final_score: 0.19680, time: 26.09148 + +2021-06-26T09:24:20.270585 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 43, summary_loss: 0.35812, final_score: 0.12659, time: 90.98558 +[RESULT]: Val. Epoch: 43, summary_loss: 0.76444, final_score: 0.21479, time: 26.62282 + +2021-06-26T09:26:18.044777 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 44, summary_loss: 0.36119, final_score: 0.12797, time: 90.11517 +[RESULT]: Val. Epoch: 44, summary_loss: 0.55587, final_score: 0.20430, time: 26.27924 + +2021-06-26T09:28:14.619606 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 45, summary_loss: 0.35365, final_score: 0.12147, time: 92.34683 +[RESULT]: Val. Epoch: 45, summary_loss: 0.56740, final_score: 0.18731, time: 26.20411 + +2021-06-26T09:30:13.337762 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 46, summary_loss: 0.35130, final_score: 0.12084, time: 89.34291 +[RESULT]: Val. Epoch: 46, summary_loss: 0.88595, final_score: 0.23077, time: 26.34657 + +2021-06-26T09:32:09.212393 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 47, summary_loss: 0.34459, final_score: 0.11385, time: 92.52091 +[RESULT]: Val. Epoch: 47, summary_loss: 0.66677, final_score: 0.21279, time: 26.14063 + +2021-06-26T09:34:08.055011 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 48, summary_loss: 0.33957, final_score: 0.11272, time: 92.24934 +[RESULT]: Val. Epoch: 48, summary_loss: 0.56747, final_score: 0.19131, time: 25.95035 + +2021-06-26T09:36:06.420670 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.33757, final_score: 0.11747, time: 91.55127 +[RESULT]: Val. Epoch: 49, summary_loss: 0.49780, final_score: 0.18182, time: 25.94743 + +2021-06-26T09:38:04.122659 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.33491, final_score: 0.11197, time: 91.97387 +[RESULT]: Val. Epoch: 50, summary_loss: 0.56627, final_score: 0.20280, time: 26.48030 + +2021-06-26T09:40:02.752177 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.32890, final_score: 0.10772, time: 91.41768 +[RESULT]: Val. Epoch: 51, summary_loss: 0.54510, final_score: 0.17782, time: 26.47016 + +2021-06-26T09:42:00.836939 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.31153, final_score: 0.09248, time: 91.77401 +[RESULT]: Val. Epoch: 52, summary_loss: 0.50145, final_score: 0.17483, time: 25.98816 + +2021-06-26T09:43:58.775473 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.30779, final_score: 0.09123, time: 92.45866 +[RESULT]: Val. Epoch: 53, summary_loss: 0.57305, final_score: 0.16983, time: 25.91148 + +2021-06-26T09:45:57.320618 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.29748, final_score: 0.08460, time: 92.84216 +[RESULT]: Val. Epoch: 54, summary_loss: 0.50509, final_score: 0.16883, time: 26.48620 + +2021-06-26T09:47:56.817100 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.29585, final_score: 0.08448, time: 91.41818 +[RESULT]: Val. Epoch: 55, summary_loss: 0.50305, final_score: 0.16783, time: 26.25990 + +2021-06-26T09:49:54.684168 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.29323, final_score: 0.08485, time: 91.79226 +[RESULT]: Val. Epoch: 56, summary_loss: 0.49923, final_score: 0.16633, time: 26.29227 + +2021-06-26T09:51:52.938002 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.28753, final_score: 0.07986, time: 90.89130 +[RESULT]: Val. Epoch: 57, summary_loss: 0.50305, final_score: 0.16334, time: 25.92543 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/accuracy.npy b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/accuracy.npy new file mode 100644 index 0000000000000000000000000000000000000000..228a1b9e5ccc5df3e5aa23efafdcfd06d296d10b Binary files /dev/null and b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/accuracy.npy differ diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-009epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-009epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a1d4a3f1b129742b4e38c03cf42498663f5fba86 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-009epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:39599647ae54a83bac87795e09a9a2518c87553429c645e5dee7970e4efc75b3 +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-013epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-013epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..9ee4b3c79f1f01bdffe1863ef6d5ce81ca0cbf62 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-013epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8235086deaf83e3fc95c0a1a2259407e5421d91d91427724c6ec9592b273d8ee +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-015epoch.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-015epoch.bin new file mode 100644 index 0000000000000000000000000000000000000000..a876c328ec6fa04bac848111e7ceeb24278adebe --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/best-checkpoint-015epoch.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d1f94470bb4ef4e8ef8835b2ec1fd98edd3ea1a0d4e07f2e240becb539c5ccdf +size 69172502 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/last-checkpoint.bin b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/last-checkpoint.bin new file mode 100644 index 0000000000000000000000000000000000000000..ad73012ee14bdd8d6b0338e0fae730235258db9a --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/last-checkpoint.bin @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b2960709283a10e0962bfc5b164bb41812935a5a19585d2f03e7eedb6da48c2 +size 69172566 diff --git a/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/log.txt b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/log.txt new file mode 100644 index 0000000000000000000000000000000000000000..7c0909ee533d0d3f09191255249c01a1942c7178 --- /dev/null +++ b/experience_512_75_0_4_SGE_efnetB0s1_xunet_srnet/train_xunet_stego_4/log.txt @@ -0,0 +1,362 @@ +Fitter prepared. Device is cuda:0 + +2021-06-25T16:57:26.657507 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.74174, final_score: 0.49800, time: 102.43047 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69463, final_score: 0.49451, time: 29.81104 + +2021-06-25T16:59:39.250664 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69437, final_score: 0.49700, time: 95.98288 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69355, final_score: 0.49451, time: 27.51356 + +2021-06-25T17:01:43.088782 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69364, final_score: 0.49700, time: 94.01043 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69357, final_score: 0.49550, time: 26.55236 + +2021-06-25T17:03:43.819074 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69334, final_score: 0.49463, time: 92.49537 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69311, final_score: 0.49001, time: 26.56223 + +2021-06-25T17:05:43.256626 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69314, final_score: 0.49163, time: 92.68616 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69343, final_score: 0.48402, time: 26.43858 + +2021-06-25T17:07:42.557850 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69261, final_score: 0.48350, time: 92.40720 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69814, final_score: 0.48002, time: 27.11787 + +2021-06-25T17:09:42.256782 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.68737, final_score: 0.45089, time: 91.75384 +[RESULT]: Val. Epoch: 6, summary_loss: 0.70867, final_score: 0.46204, time: 26.94696 + +2021-06-25T17:11:41.134847 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.66053, final_score: 0.37941, time: 93.49209 +[RESULT]: Val. Epoch: 7, summary_loss: 0.72198, final_score: 0.39960, time: 26.67507 + +2021-06-25T17:13:41.489361 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.63722, final_score: 0.35391, time: 92.69990 +[RESULT]: Val. Epoch: 8, summary_loss: 1.00996, final_score: 0.39610, time: 26.46764 + +2021-06-25T17:15:40.846488 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.61282, final_score: 0.32292, time: 92.84972 +[RESULT]: Val. Epoch: 9, summary_loss: 0.67315, final_score: 0.32318, time: 26.61792 + +2021-06-25T17:17:40.684214 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.60307, final_score: 0.30842, time: 93.08971 +[RESULT]: Val. Epoch: 10, summary_loss: 1.27275, final_score: 0.32717, time: 27.05190 + +2021-06-25T17:19:41.012377 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.58728, final_score: 0.29630, time: 92.44429 +[RESULT]: Val. Epoch: 11, summary_loss: 1.21055, final_score: 0.36364, time: 26.36820 + +2021-06-25T17:21:39.994616 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.57689, final_score: 0.28330, time: 92.60010 +[RESULT]: Val. Epoch: 12, summary_loss: 1.54242, final_score: 0.35514, time: 26.38250 + +2021-06-25T17:23:39.157526 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.57048, final_score: 0.27331, time: 94.08558 +[RESULT]: Val. Epoch: 13, summary_loss: 0.59448, final_score: 0.28521, time: 26.81331 + +2021-06-25T17:25:40.392997 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.56361, final_score: 0.27493, time: 95.57172 +[RESULT]: Val. Epoch: 14, summary_loss: 0.60840, final_score: 0.31119, time: 26.31651 + +2021-06-25T17:27:42.531849 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.54852, final_score: 0.26268, time: 93.59013 +[RESULT]: Val. Epoch: 15, summary_loss: 0.55693, final_score: 0.25774, time: 26.66852 + +2021-06-25T17:29:43.149521 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.54449, final_score: 0.25744, time: 92.68493 +[RESULT]: Val. Epoch: 16, summary_loss: 0.68551, final_score: 0.31668, time: 26.14415 + +2021-06-25T17:31:42.162411 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.53895, final_score: 0.25106, time: 92.61305 +[RESULT]: Val. Epoch: 17, summary_loss: 0.61033, final_score: 0.25874, time: 26.98066 + +2021-06-25T17:33:41.931558 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.52807, final_score: 0.24444, time: 93.42996 +[RESULT]: Val. Epoch: 18, summary_loss: 0.60456, final_score: 0.26673, time: 26.42700 + +2021-06-25T17:35:41.965525 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.51820, final_score: 0.23144, time: 92.09882 +[RESULT]: Val. Epoch: 19, summary_loss: 0.58281, final_score: 0.25924, time: 26.45646 + +2021-06-25T17:37:40.697747 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.51685, final_score: 0.23819, time: 92.93836 +[RESULT]: Val. Epoch: 20, summary_loss: 1.78168, final_score: 0.30769, time: 26.50790 + +2021-06-25T17:39:40.314375 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.50868, final_score: 0.23019, time: 94.31644 +[RESULT]: Val. Epoch: 21, summary_loss: 1.49027, final_score: 0.30819, time: 26.90958 + +2021-06-25T17:41:41.721551 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.50231, final_score: 0.22307, time: 94.76149 +[RESULT]: Val. Epoch: 22, summary_loss: 1.21876, final_score: 0.26723, time: 26.77277 + +2021-06-25T17:43:43.435000 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.49552, final_score: 0.21970, time: 95.56784 +[RESULT]: Val. Epoch: 23, summary_loss: 0.86628, final_score: 0.28022, time: 26.86015 + +2021-06-25T17:45:46.051290 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.48986, final_score: 0.21470, time: 94.36961 +[RESULT]: Val. Epoch: 24, summary_loss: 1.00984, final_score: 0.25524, time: 26.57589 + +2021-06-25T17:47:47.175814 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.47960, final_score: 0.21120, time: 93.89550 +[RESULT]: Val. Epoch: 25, summary_loss: 0.71979, final_score: 0.26274, time: 26.67676 + +2021-06-25T17:49:47.931650 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.47756, final_score: 0.20695, time: 92.93487 +[RESULT]: Val. Epoch: 26, summary_loss: 0.94392, final_score: 0.31119, time: 27.00828 + +2021-06-25T17:51:48.068332 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.47243, final_score: 0.20432, time: 91.55854 +[RESULT]: Val. Epoch: 27, summary_loss: 0.95343, final_score: 0.25724, time: 26.51440 + +2021-06-25T17:53:46.322582 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.45049, final_score: 0.18608, time: 92.30296 +[RESULT]: Val. Epoch: 28, summary_loss: 0.63897, final_score: 0.25475, time: 26.58242 + +2021-06-25T17:55:45.391963 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.44173, final_score: 0.18520, time: 92.06834 +[RESULT]: Val. Epoch: 29, summary_loss: 0.58680, final_score: 0.23676, time: 26.64959 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:44.788357 +LR: 0.00025 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 28, summary_loss: 0.51739, final_score: 0.24419, time: 94.05285 +[RESULT]: Val. Epoch: 28, summary_loss: 0.57996, final_score: 0.28122, time: 28.88783 + +2021-06-26T08:56:47.904945 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 29, summary_loss: 0.50864, final_score: 0.23494, time: 92.83237 +[RESULT]: Val. Epoch: 29, summary_loss: 0.66921, final_score: 0.28971, time: 25.95722 + +2021-06-26T08:58:46.898660 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 30, summary_loss: 0.50156, final_score: 0.23044, time: 92.17058 +[RESULT]: Val. Epoch: 30, summary_loss: 0.85950, final_score: 0.30669, time: 25.84512 + +2021-06-26T09:00:45.086802 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.49610, final_score: 0.22569, time: 92.87919 +[RESULT]: Val. Epoch: 31, summary_loss: 0.61180, final_score: 0.26823, time: 26.31977 + +2021-06-26T09:02:44.476759 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.49125, final_score: 0.22444, time: 93.03477 +[RESULT]: Val. Epoch: 32, summary_loss: 0.67084, final_score: 0.27522, time: 25.93192 + +2021-06-26T09:04:43.608341 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.48445, final_score: 0.21595, time: 92.60989 +[RESULT]: Val. Epoch: 33, summary_loss: 0.62344, final_score: 0.28222, time: 26.25944 + +2021-06-26T09:06:42.661193 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.48347, final_score: 0.21670, time: 92.77624 +[RESULT]: Val. Epoch: 34, summary_loss: 0.69273, final_score: 0.27922, time: 26.52432 + +2021-06-26T09:08:42.165202 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.47536, final_score: 0.20882, time: 90.86503 +[RESULT]: Val. Epoch: 35, summary_loss: 0.65541, final_score: 0.26174, time: 26.41273 + +2021-06-26T09:10:39.600031 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.47422, final_score: 0.20870, time: 88.86762 +[RESULT]: Val. Epoch: 36, summary_loss: 0.68928, final_score: 0.29171, time: 26.57329 + +2021-06-26T09:12:35.212831 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.46882, final_score: 0.20695, time: 91.23069 +[RESULT]: Val. Epoch: 37, summary_loss: 0.65425, final_score: 0.28122, time: 25.87691 + +2021-06-26T09:14:32.479237 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.46168, final_score: 0.20020, time: 92.58077 +[RESULT]: Val. Epoch: 38, summary_loss: 0.63178, final_score: 0.26523, time: 26.01216 + +2021-06-26T09:16:31.231402 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.45375, final_score: 0.19720, time: 91.68467 +[RESULT]: Val. Epoch: 39, summary_loss: 0.73137, final_score: 0.26224, time: 25.58422 + +2021-06-26T09:18:28.660656 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.45604, final_score: 0.19633, time: 92.80578 +[RESULT]: Val. Epoch: 40, summary_loss: 0.57553, final_score: 0.25524, time: 26.88922 + +2021-06-26T09:20:28.531221 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.45061, final_score: 0.19620, time: 90.16969 +[RESULT]: Val. Epoch: 41, summary_loss: 0.83804, final_score: 0.29820, time: 26.36954 + +2021-06-26T09:22:25.236234 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.43833, final_score: 0.18020, time: 92.40809 +[RESULT]: Val. Epoch: 42, summary_loss: 0.62881, final_score: 0.27722, time: 26.21496 + +2021-06-26T09:24:24.018720 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 43, summary_loss: 0.44226, final_score: 0.18583, time: 93.62541 +[RESULT]: Val. Epoch: 43, summary_loss: 0.59211, final_score: 0.26474, time: 26.23719 + +2021-06-26T09:26:24.068344 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 44, summary_loss: 0.43384, final_score: 0.17883, time: 93.65341 +[RESULT]: Val. Epoch: 44, summary_loss: 0.61947, final_score: 0.26324, time: 25.92919 + +2021-06-26T09:28:23.900655 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 45, summary_loss: 0.42978, final_score: 0.17708, time: 92.48735 +[RESULT]: Val. Epoch: 45, summary_loss: 0.58857, final_score: 0.25924, time: 25.73346 + +2021-06-26T09:30:22.278795 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 46, summary_loss: 0.43256, final_score: 0.17933, time: 92.94883 +[RESULT]: Val. Epoch: 46, summary_loss: 0.63783, final_score: 0.26324, time: 26.17231 + +2021-06-26T09:32:21.558441 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 47, summary_loss: 0.41570, final_score: 0.16846, time: 93.21906 +[RESULT]: Val. Epoch: 47, summary_loss: 0.79863, final_score: 0.30170, time: 26.28500 + +2021-06-26T09:34:21.231848 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 48, summary_loss: 0.41568, final_score: 0.17083, time: 92.76083 +[RESULT]: Val. Epoch: 48, summary_loss: 1.09785, final_score: 0.30170, time: 26.52770 + +2021-06-26T09:36:20.677615 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.41415, final_score: 0.16646, time: 92.57003 +[RESULT]: Val. Epoch: 49, summary_loss: 0.72126, final_score: 0.27173, time: 26.04052 + +2021-06-26T09:38:19.466913 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.38755, final_score: 0.14296, time: 92.07279 +[RESULT]: Val. Epoch: 50, summary_loss: 0.63823, final_score: 0.25824, time: 26.09400 + +2021-06-26T09:40:17.792322 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.39055, final_score: 0.14996, time: 91.30418 +[RESULT]: Val. Epoch: 51, summary_loss: 0.69760, final_score: 0.26124, time: 26.13857 + +2021-06-26T09:42:15.411032 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.36959, final_score: 0.13684, time: 91.16274 +[RESULT]: Val. Epoch: 52, summary_loss: 0.65894, final_score: 0.25425, time: 25.80189 + +2021-06-26T09:44:12.584525 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.36389, final_score: 0.13122, time: 92.38176 +[RESULT]: Val. Epoch: 53, summary_loss: 0.66341, final_score: 0.26024, time: 25.94878 + +2021-06-26T09:46:11.089750 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.36069, final_score: 0.13059, time: 91.08972 +[RESULT]: Val. Epoch: 54, summary_loss: 0.66229, final_score: 0.25724, time: 26.05637 + +2021-06-26T09:48:08.398566 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.35871, final_score: 0.12909, time: 92.09954 +[RESULT]: Val. Epoch: 55, summary_loss: 0.66439, final_score: 0.25774, time: 26.62786 + +2021-06-26T09:50:07.303339 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.35464, final_score: 0.12609, time: 92.84459 +[RESULT]: Val. Epoch: 56, summary_loss: 0.67217, final_score: 0.25624, time: 26.37938 + +2021-06-26T09:52:06.696349 +LR: 1.5625e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.35542, final_score: 0.12759, time: 91.58040 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T13:12:29.983949 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.71078, final_score: 0.49763, time: 103.35291 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.48951, time: 30.46630 + +2021-06-25T13:14:44.188466 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69308, final_score: 0.49163, time: 93.41091 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69323, final_score: 0.48501, time: 26.89489 + +2021-06-25T13:16:44.669262 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69294, final_score: 0.48788, time: 92.62869 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69365, final_score: 0.48152, time: 26.15033 + +2021-06-25T13:18:43.613752 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69260, final_score: 0.48213, time: 94.26429 +[RESULT]: Val. Epoch: 3, summary_loss: 0.69404, final_score: 0.48851, time: 26.56330 + +2021-06-25T13:20:44.623720 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69191, final_score: 0.47413, time: 92.49376 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69895, final_score: 0.47003, time: 26.62501 + +2021-06-25T13:22:43.912060 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69125, final_score: 0.46951, time: 91.02570 +[RESULT]: Val. Epoch: 5, summary_loss: 0.72248, final_score: 0.49550, time: 26.07988 + +2021-06-25T13:24:41.183372 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.68931, final_score: 0.46101, time: 91.74795 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69166, final_score: 0.47303, time: 26.63301 + +2021-06-25T13:26:40.084297 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.68574, final_score: 0.44726, time: 94.77355 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69412, final_score: 0.46803, time: 27.00278 + +2021-06-25T13:28:42.043054 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.68019, final_score: 0.43764, time: 93.62301 +[RESULT]: Val. Epoch: 8, summary_loss: 0.67833, final_score: 0.42358, time: 27.01054 + +2021-06-25T13:30:43.035741 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.67469, final_score: 0.42339, time: 93.88971 +[RESULT]: Val. Epoch: 9, summary_loss: 0.70040, final_score: 0.47552, time: 26.61366 + +2021-06-25T13:32:43.718552 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.66887, final_score: 0.41177, time: 92.61757 +[RESULT]: Val. Epoch: 10, summary_loss: 1.26395, final_score: 0.44056, time: 26.48445 + +2021-06-25T13:34:43.073788 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.66306, final_score: 0.40815, time: 92.74181 +[RESULT]: Val. Epoch: 11, summary_loss: 0.69250, final_score: 0.45405, time: 26.81018 + +2021-06-25T13:36:42.806878 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.66016, final_score: 0.39590, time: 94.95226 +[RESULT]: Val. Epoch: 12, summary_loss: 0.66952, final_score: 0.40310, time: 26.78192 + +2021-06-25T13:38:44.882645 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.65439, final_score: 0.39053, time: 93.13996 +[RESULT]: Val. Epoch: 13, summary_loss: 0.69517, final_score: 0.41558, time: 26.55885 + +2021-06-25T13:40:44.744949 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.64812, final_score: 0.38278, time: 93.67645 +[RESULT]: Val. Epoch: 14, summary_loss: 1.26342, final_score: 0.44106, time: 26.87184 + +2021-06-25T13:42:45.477046 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64608, final_score: 0.37991, time: 93.90932 +[RESULT]: Val. Epoch: 15, summary_loss: 1.23189, final_score: 0.39560, time: 26.86631 + +2021-06-25T13:44:46.436963 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64371, final_score: 0.37241, time: 93.74308 +[RESULT]: Val. Epoch: 16, summary_loss: 0.75085, final_score: 0.40210, time: 26.64621 + +2021-06-25T13:46:47.039147 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.63657, final_score: 0.36841, time: 93.49397 +[RESULT]: Val. Epoch: 17, summary_loss: 1.02548, final_score: 0.42308, time: 27.48435 + +2021-06-25T13:48:48.201031 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.63510, final_score: 0.36328, time: 94.30813 +[RESULT]: Val. Epoch: 18, summary_loss: 0.86365, final_score: 0.45105, time: 28.24331 + +2021-06-25T13:50:50.936676 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.62896, final_score: 0.36341, time: 95.79042 +[RESULT]: Val. Epoch: 19, summary_loss: 0.70173, final_score: 0.37313, time: 27.37891 + +2021-06-25T13:52:54.279724 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.62507, final_score: 0.35341, time: 95.71481 +[RESULT]: Val. Epoch: 20, summary_loss: 0.73935, final_score: 0.36813, time: 27.52638 + +2021-06-25T13:54:57.690430 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.62044, final_score: 0.34591, time: 92.34195 +[RESULT]: Val. Epoch: 21, summary_loss: 1.41212, final_score: 0.42757, time: 26.88355 + +2021-06-25T13:56:57.082251 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.61134, final_score: 0.34054, time: 93.89312 +[RESULT]: Val. Epoch: 22, summary_loss: 0.66169, final_score: 0.36464, time: 28.11879 + +2021-06-25T13:58:59.447853 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.61260, final_score: 0.34354, time: 96.84469 +[RESULT]: Val. Epoch: 23, summary_loss: 0.90563, final_score: 0.40010, time: 26.93366 + +2021-06-25T14:01:03.430902 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.60865, final_score: 0.33967, time: 93.70751 +[RESULT]: Val. Epoch: 24, summary_loss: 0.89307, final_score: 0.43257, time: 26.43749 + +2021-06-25T14:03:03.745775 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.59091, final_score: 0.32042, time: 91.29315 +[RESULT]: Val. Epoch: 25, summary_loss: 0.83134, final_score: 0.37712, time: 26.35493 + +2021-06-25T14:05:01.577567 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.58245, final_score: 0.31167, time: 93.35357 +[RESULT]: Val. Epoch: 26, summary_loss: 0.66633, final_score: 0.35065, time: 26.37146 + +2021-06-25T14:07:01.468159 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.56763, final_score: 0.30392, time: 93.43541 +[RESULT]: Val. Epoch: 27, summary_loss: 0.72403, final_score: 0.33766, time: 26.71978 + +2021-06-25T14:09:01.786076 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.56047, final_score: 0.29168, time: 93.09140 +[RESULT]: Val. Epoch: 28, summary_loss: 0.76532, final_score: 0.37213, time: 26.29591 + +2021-06-25T14:11:01.353374 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.55456, final_score: 0.28768, time: 94.56469 +[RESULT]: Val. Epoch: 29, summary_loss: 0.79524, final_score: 0.34316, time: 26.83384 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:44.671880 +LR: 0.0005 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 26, summary_loss: 0.64559, final_score: 0.37878, time: 93.02643 +[RESULT]: Val. Epoch: 26, summary_loss: 0.69745, final_score: 0.39311, time: 30.02341 + +2021-06-26T08:56:47.894137 +LR: 0.0005 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 27, summary_loss: 0.64036, final_score: 0.37391, time: 94.56875 +[RESULT]: Val. Epoch: 27, summary_loss: 0.68689, final_score: 0.39860, time: 26.96292 + +2021-06-26T08:58:49.584281 +LR: 0.0005 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 28, summary_loss: 0.63674, final_score: 0.36991, time: 93.62800 +[RESULT]: Val. Epoch: 28, summary_loss: 0.66377, final_score: 0.39211, time: 26.96509 + +2021-06-26T09:00:50.336175 +LR: 0.0005 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 29, summary_loss: 0.63222, final_score: 0.36378, time: 93.08542 +[RESULT]: Val. Epoch: 29, summary_loss: 1.71708, final_score: 0.42857, time: 26.47426 + +2021-06-26T09:02:50.105704 +LR: 0.0005 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 30, summary_loss: 0.63165, final_score: 0.36478, time: 93.66819 +[RESULT]: Val. Epoch: 30, summary_loss: 0.75643, final_score: 0.39361, time: 26.79681 + +2021-06-26T09:04:50.766781 +LR: 0.0005 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.62658, final_score: 0.35391, time: 92.02761 +[RESULT]: Val. Epoch: 31, summary_loss: 0.84837, final_score: 0.40410, time: 26.70724 + +2021-06-26T09:06:49.699822 +LR: 0.0005 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.62521, final_score: 0.35266, time: 93.86496 +[RESULT]: Val. Epoch: 32, summary_loss: 0.65490, final_score: 0.37962, time: 26.53874 + +2021-06-26T09:08:50.258513 +LR: 0.0005 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.62218, final_score: 0.35079, time: 94.21391 +[RESULT]: Val. Epoch: 33, summary_loss: 0.66931, final_score: 0.37762, time: 27.57215 + +2021-06-26T09:10:52.200270 +LR: 0.0005 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.61631, final_score: 0.34379, time: 91.47123 +[RESULT]: Val. Epoch: 34, summary_loss: 0.73802, final_score: 0.40609, time: 26.35364 + +2021-06-26T09:12:50.239325 +LR: 0.0005 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.61098, final_score: 0.33954, time: 91.96607 +[RESULT]: Val. Epoch: 35, summary_loss: 0.67565, final_score: 0.38312, time: 26.86524 + +2021-06-26T09:14:49.251222 +LR: 0.0005 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.60892, final_score: 0.34216, time: 94.48896 +[RESULT]: Val. Epoch: 36, summary_loss: 0.84297, final_score: 0.40709, time: 26.97912 + +2021-06-26T09:16:50.879261 +LR: 0.0005 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.60903, final_score: 0.33954, time: 93.31868 +[RESULT]: Val. Epoch: 37, summary_loss: 0.64019, final_score: 0.36064, time: 26.87423 + +2021-06-26T09:18:51.447691 +LR: 0.0005 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.59783, final_score: 0.32579, time: 92.79666 +[RESULT]: Val. Epoch: 38, summary_loss: 0.66182, final_score: 0.35714, time: 26.94057 + +2021-06-26T09:20:51.367521 +LR: 0.0005 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.59383, final_score: 0.31967, time: 92.92308 +[RESULT]: Val. Epoch: 39, summary_loss: 0.70992, final_score: 0.38761, time: 26.71907 + +2021-06-26T09:22:51.180622 +LR: 0.0005 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.59179, final_score: 0.31542, time: 92.03749 +[RESULT]: Val. Epoch: 40, summary_loss: 0.88503, final_score: 0.40010, time: 26.18716 + +2021-06-26T09:24:49.571360 +LR: 0.0005 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.58948, final_score: 0.32279, time: 94.01663 +[RESULT]: Val. Epoch: 41, summary_loss: 0.64298, final_score: 0.36913, time: 27.05980 + +2021-06-26T09:26:50.810000 +LR: 0.0005 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.58476, final_score: 0.31392, time: 94.05662 +[RESULT]: Val. Epoch: 42, summary_loss: 0.70108, final_score: 0.38811, time: 26.79744 + +2021-06-26T09:28:51.814706 +LR: 0.0005 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 43, summary_loss: 0.58009, final_score: 0.31105, time: 94.13987 +[RESULT]: Val. Epoch: 43, summary_loss: 0.66194, final_score: 0.36364, time: 26.85305 + +2021-06-26T09:30:53.005198 +LR: 0.0005 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 44, summary_loss: 0.57278, final_score: 0.30392, time: 91.96618 +[RESULT]: Val. Epoch: 44, summary_loss: 1.03941, final_score: 0.42807, time: 26.71078 + +2021-06-26T09:32:51.856356 +LR: 0.0005 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 45, summary_loss: 0.57624, final_score: 0.30367, time: 94.99889 +[RESULT]: Val. Epoch: 45, summary_loss: 0.66519, final_score: 0.36064, time: 26.65314 + +2021-06-26T09:34:53.689457 +LR: 0.0005 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 46, summary_loss: 0.56568, final_score: 0.29930, time: 91.72576 +[RESULT]: Val. Epoch: 46, summary_loss: 0.65758, final_score: 0.36364, time: 26.75529 + +2021-06-26T09:36:52.350376 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 47, summary_loss: 0.55916, final_score: 0.29618, time: 93.11897 +[RESULT]: Val. Epoch: 47, summary_loss: 1.09184, final_score: 0.40609, time: 27.24711 + +2021-06-26T09:38:52.918659 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 48, summary_loss: 0.55684, final_score: 0.28755, time: 94.35508 +[RESULT]: Val. Epoch: 48, summary_loss: 0.83137, final_score: 0.36763, time: 26.57548 + +2021-06-26T09:40:54.044496 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.53440, final_score: 0.27118, time: 94.76781 +[RESULT]: Val. Epoch: 49, summary_loss: 0.75302, final_score: 0.35015, time: 26.84535 + +2021-06-26T09:42:55.821090 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.52159, final_score: 0.25981, time: 94.99221 +[RESULT]: Val. Epoch: 50, summary_loss: 0.82627, final_score: 0.35914, time: 27.14904 + +2021-06-26T09:44:58.138874 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.50310, final_score: 0.24244, time: 95.45624 +[RESULT]: Val. Epoch: 51, summary_loss: 0.70181, final_score: 0.33916, time: 26.69992 + +2021-06-26T09:47:00.473808 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.49786, final_score: 0.24119, time: 93.98369 +[RESULT]: Val. Epoch: 52, summary_loss: 0.77534, final_score: 0.34865, time: 26.73334 + +2021-06-26T09:49:01.352903 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.48757, final_score: 0.23094, time: 92.90616 +[RESULT]: Val. Epoch: 53, summary_loss: 0.71028, final_score: 0.33367, time: 26.95148 + +2021-06-26T09:51:01.377529 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.48487, final_score: 0.23169, time: 93.67087 +[RESULT]: Val. Epoch: 54, summary_loss: 0.70485, final_score: 0.32967, time: 26.67503 + +2021-06-26T09:53:01.923974 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.47754, final_score: 0.22569, time: 91.50838 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T16:58:10.589210 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.71468, final_score: 0.49688, time: 96.45045 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69411, final_score: 0.49001, time: 27.60300 + +2021-06-25T17:00:15.022725 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69312, final_score: 0.48925, time: 91.54730 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69789, final_score: 0.48701, time: 26.62558 + +2021-06-25T17:02:13.404121 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69267, final_score: 0.48250, time: 94.46304 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69854, final_score: 0.47952, time: 26.75848 + +2021-06-25T17:04:14.786890 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69243, final_score: 0.47913, time: 91.39766 +[RESULT]: Val. Epoch: 3, summary_loss: 0.73541, final_score: 0.49251, time: 26.13572 + +2021-06-25T17:06:12.479501 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.69149, final_score: 0.46888, time: 92.51854 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69615, final_score: 0.47952, time: 27.08503 + +2021-06-25T17:08:12.248344 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69006, final_score: 0.46288, time: 92.03778 +[RESULT]: Val. Epoch: 5, summary_loss: 0.70388, final_score: 0.46703, time: 26.33616 + +2021-06-25T17:10:10.804329 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.68892, final_score: 0.45414, time: 91.56247 +[RESULT]: Val. Epoch: 6, summary_loss: 0.72798, final_score: 0.48252, time: 26.66158 + +2021-06-25T17:12:09.215559 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.68614, final_score: 0.45039, time: 93.66914 +[RESULT]: Val. Epoch: 7, summary_loss: 0.69650, final_score: 0.46054, time: 26.02269 + +2021-06-25T17:14:09.123150 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.68013, final_score: 0.43464, time: 93.00147 +[RESULT]: Val. Epoch: 8, summary_loss: 1.21081, final_score: 0.47303, time: 26.12485 + +2021-06-25T17:16:08.423066 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.67864, final_score: 0.43314, time: 91.82144 +[RESULT]: Val. Epoch: 9, summary_loss: 0.75112, final_score: 0.43606, time: 27.15334 + +2021-06-25T17:18:07.589533 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.67396, final_score: 0.42089, time: 93.42614 +[RESULT]: Val. Epoch: 10, summary_loss: 0.79132, final_score: 0.47403, time: 26.28408 + +2021-06-25T17:20:07.555655 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.66712, final_score: 0.40902, time: 92.55543 +[RESULT]: Val. Epoch: 11, summary_loss: 0.75529, final_score: 0.42108, time: 26.74637 + +2021-06-25T17:22:07.021174 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.66316, final_score: 0.40365, time: 94.21768 +[RESULT]: Val. Epoch: 12, summary_loss: 0.67142, final_score: 0.39760, time: 26.16014 + +2021-06-25T17:24:07.720272 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.65491, final_score: 0.38603, time: 92.75517 +[RESULT]: Val. Epoch: 13, summary_loss: 0.70984, final_score: 0.39760, time: 26.44517 + +2021-06-25T17:26:07.094037 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.65121, final_score: 0.38415, time: 91.57588 +[RESULT]: Val. Epoch: 14, summary_loss: 1.31842, final_score: 0.46703, time: 26.58391 + +2021-06-25T17:28:05.433593 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.64823, final_score: 0.37841, time: 91.94640 +[RESULT]: Val. Epoch: 15, summary_loss: 0.71559, final_score: 0.38312, time: 26.54493 + +2021-06-25T17:30:04.125290 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.64107, final_score: 0.37428, time: 90.66460 +[RESULT]: Val. Epoch: 16, summary_loss: 0.68852, final_score: 0.38112, time: 26.60009 + +2021-06-25T17:32:01.572828 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.64055, final_score: 0.36853, time: 92.97776 +[RESULT]: Val. Epoch: 17, summary_loss: 1.03854, final_score: 0.45455, time: 26.53291 + +2021-06-25T17:34:01.246867 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.63785, final_score: 0.36991, time: 92.29761 +[RESULT]: Val. Epoch: 18, summary_loss: 0.69509, final_score: 0.39910, time: 26.14614 + +2021-06-25T17:35:59.856852 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.63000, final_score: 0.35854, time: 92.47999 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69155, final_score: 0.39610, time: 26.96618 + +2021-06-25T17:37:59.471911 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.62807, final_score: 0.35929, time: 92.62954 +[RESULT]: Val. Epoch: 20, summary_loss: 1.42760, final_score: 0.38212, time: 26.91643 + +2021-06-25T17:39:59.204523 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.62008, final_score: 0.35204, time: 91.65493 +[RESULT]: Val. Epoch: 21, summary_loss: 0.68825, final_score: 0.37163, time: 26.85503 + +2021-06-25T17:41:57.897451 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.61831, final_score: 0.34316, time: 90.92122 +[RESULT]: Val. Epoch: 22, summary_loss: 0.69517, final_score: 0.35165, time: 27.09367 + +2021-06-25T17:43:56.078752 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.61205, final_score: 0.33954, time: 90.83309 +[RESULT]: Val. Epoch: 23, summary_loss: 0.89299, final_score: 0.37313, time: 26.83126 + +2021-06-25T17:45:53.906793 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.58838, final_score: 0.32204, time: 93.05860 +[RESULT]: Val. Epoch: 24, summary_loss: 0.71669, final_score: 0.37912, time: 26.57467 + +2021-06-25T17:47:53.707503 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.58419, final_score: 0.31442, time: 93.28963 +[RESULT]: Val. Epoch: 25, summary_loss: 0.69011, final_score: 0.35764, time: 26.45782 + +2021-06-25T17:49:53.620807 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.56618, final_score: 0.29318, time: 91.87462 +[RESULT]: Val. Epoch: 26, summary_loss: 0.66529, final_score: 0.33966, time: 26.26889 + +2021-06-25T17:51:52.087107 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.55818, final_score: 0.29030, time: 90.78031 +[RESULT]: Val. Epoch: 27, summary_loss: 0.84170, final_score: 0.35664, time: 26.47275 + +2021-06-25T17:53:49.528018 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.55541, final_score: 0.29043, time: 91.98535 +[RESULT]: Val. Epoch: 28, summary_loss: 0.78065, final_score: 0.36314, time: 26.92619 + +2021-06-25T17:55:48.630349 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.54269, final_score: 0.27718, time: 91.66981 +[RESULT]: Val. Epoch: 29, summary_loss: 0.67896, final_score: 0.33467, time: 26.23342 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:40.981141 +LR: 0.00025 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 28, summary_loss: 0.63341, final_score: 0.36953, time: 94.40691 +[RESULT]: Val. Epoch: 28, summary_loss: 0.66619, final_score: 0.38412, time: 32.33561 + +2021-06-26T08:56:47.906535 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 29, summary_loss: 0.62819, final_score: 0.36366, time: 92.78656 +[RESULT]: Val. Epoch: 29, summary_loss: 0.65997, final_score: 0.39211, time: 27.06141 + +2021-06-26T08:58:48.100458 +LR: 0.00025 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 30, summary_loss: 0.62284, final_score: 0.35841, time: 92.97034 +[RESULT]: Val. Epoch: 30, summary_loss: 0.66414, final_score: 0.38112, time: 27.22401 + +2021-06-26T09:00:48.455906 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.62185, final_score: 0.35654, time: 93.77335 +[RESULT]: Val. Epoch: 31, summary_loss: 0.83361, final_score: 0.39960, time: 27.05791 + +2021-06-26T09:02:49.467067 +LR: 0.00025 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.62061, final_score: 0.35291, time: 92.44691 +[RESULT]: Val. Epoch: 32, summary_loss: 0.68077, final_score: 0.37962, time: 26.84642 + +2021-06-26T09:04:48.922500 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.61810, final_score: 0.35066, time: 94.60907 +[RESULT]: Val. Epoch: 33, summary_loss: 0.69798, final_score: 0.37862, time: 26.89001 + +2021-06-26T09:06:50.579267 +LR: 0.00025 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.61250, final_score: 0.34004, time: 93.67855 +[RESULT]: Val. Epoch: 34, summary_loss: 0.65729, final_score: 0.37313, time: 26.71497 + +2021-06-26T09:08:51.332655 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.60982, final_score: 0.34129, time: 94.19896 +[RESULT]: Val. Epoch: 35, summary_loss: 0.68305, final_score: 0.38062, time: 26.84441 + +2021-06-26T09:10:52.549341 +LR: 0.00025 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.60379, final_score: 0.33554, time: 93.12524 +[RESULT]: Val. Epoch: 36, summary_loss: 0.70012, final_score: 0.38412, time: 27.00511 + +2021-06-26T09:12:52.836425 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.60449, final_score: 0.33092, time: 92.77548 +[RESULT]: Val. Epoch: 37, summary_loss: 0.66946, final_score: 0.36763, time: 27.07823 + +2021-06-26T09:14:52.849970 +LR: 0.00025 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.60220, final_score: 0.33329, time: 95.77374 +[RESULT]: Val. Epoch: 38, summary_loss: 0.76971, final_score: 0.37163, time: 26.86022 + +2021-06-26T09:16:55.639141 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.59467, final_score: 0.32667, time: 92.22996 +[RESULT]: Val. Epoch: 39, summary_loss: 0.68541, final_score: 0.36613, time: 27.30371 + +2021-06-26T09:18:55.346427 +LR: 0.00025 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.59692, final_score: 0.32442, time: 93.96221 +[RESULT]: Val. Epoch: 40, summary_loss: 0.65119, final_score: 0.35814, time: 27.20194 + +2021-06-26T09:20:56.912247 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.59330, final_score: 0.32379, time: 94.00207 +[RESULT]: Val. Epoch: 41, summary_loss: 0.68343, final_score: 0.36813, time: 26.81554 + +2021-06-26T09:22:57.892720 +LR: 0.00025 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.58544, final_score: 0.31442, time: 93.91226 +[RESULT]: Val. Epoch: 42, summary_loss: 0.78728, final_score: 0.38012, time: 26.33470 + +2021-06-26T09:24:58.312352 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 43, summary_loss: 0.58110, final_score: 0.30767, time: 93.13773 +[RESULT]: Val. Epoch: 43, summary_loss: 0.66946, final_score: 0.36364, time: 26.92105 + +2021-06-26T09:26:58.547836 +LR: 0.00025 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 44, summary_loss: 0.58153, final_score: 0.31017, time: 93.75330 +[RESULT]: Val. Epoch: 44, summary_loss: 0.66849, final_score: 0.38112, time: 26.79230 + +2021-06-26T09:28:59.265680 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 45, summary_loss: 0.57653, final_score: 0.30742, time: 94.91473 +[RESULT]: Val. Epoch: 45, summary_loss: 0.67493, final_score: 0.34915, time: 27.00571 + +2021-06-26T09:31:01.343170 +LR: 0.00025 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 46, summary_loss: 0.57596, final_score: 0.30742, time: 93.06475 +[RESULT]: Val. Epoch: 46, summary_loss: 1.01886, final_score: 0.38811, time: 26.98095 + +2021-06-26T09:33:01.547332 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 47, summary_loss: 0.57603, final_score: 0.31392, time: 93.41572 +[RESULT]: Val. Epoch: 47, summary_loss: 0.64742, final_score: 0.35415, time: 26.58674 + +2021-06-26T09:35:01.894143 +LR: 0.00025 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 48, summary_loss: 0.56178, final_score: 0.29430, time: 93.76755 +[RESULT]: Val. Epoch: 48, summary_loss: 0.69792, final_score: 0.36214, time: 26.91062 + +2021-06-26T09:37:02.763220 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.56338, final_score: 0.29768, time: 92.16812 +[RESULT]: Val. Epoch: 49, summary_loss: 0.66908, final_score: 0.34715, time: 27.23368 + +2021-06-26T09:39:02.349149 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.56485, final_score: 0.29480, time: 93.84362 +[RESULT]: Val. Epoch: 50, summary_loss: 0.65128, final_score: 0.35065, time: 26.86967 + +2021-06-26T09:41:03.235921 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.55337, final_score: 0.28693, time: 94.19626 +[RESULT]: Val. Epoch: 51, summary_loss: 1.18951, final_score: 0.40210, time: 26.88552 + +2021-06-26T09:43:04.480459 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.55618, final_score: 0.29218, time: 92.04545 +[RESULT]: Val. Epoch: 52, summary_loss: 0.69321, final_score: 0.35764, time: 27.30256 + +2021-06-26T09:45:04.000064 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.53387, final_score: 0.27331, time: 92.91569 +[RESULT]: Val. Epoch: 53, summary_loss: 0.68705, final_score: 0.35065, time: 27.35629 + +2021-06-26T09:47:04.436517 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.53327, final_score: 0.27031, time: 95.62069 +[RESULT]: Val. Epoch: 54, summary_loss: 0.68066, final_score: 0.34116, time: 26.71274 + +2021-06-26T09:49:06.945269 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.52019, final_score: 0.25969, time: 92.04044 +[RESULT]: Val. Epoch: 55, summary_loss: 0.69182, final_score: 0.34166, time: 26.88256 + +2021-06-26T09:51:06.041521 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.51110, final_score: 0.25406, time: 95.86147 +[RESULT]: Val. Epoch: 56, summary_loss: 0.69746, final_score: 0.33516, time: 26.87931 + +2021-06-26T09:53:08.969243 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.50561, final_score: 0.24244, time: 92.96468 +[RESULT]: Val. 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Device is cuda:0 + +2021-06-25T16:58:41.159124 +LR: 0.001 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 0, summary_loss: 0.73520, final_score: 0.49688, time: 95.21252 +[RESULT]: Val. Epoch: 0, summary_loss: 0.69315, final_score: 0.49101, time: 27.12609 + +2021-06-25T17:00:43.920227 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 1, summary_loss: 0.69306, final_score: 0.49100, time: 93.04697 +[RESULT]: Val. Epoch: 1, summary_loss: 0.69304, final_score: 0.48352, time: 26.64544 + +2021-06-25T17:02:43.949087 +LR: 0.001 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 2, summary_loss: 0.69271, final_score: 0.48300, time: 90.86807 +[RESULT]: Val. Epoch: 2, summary_loss: 0.69590, final_score: 0.48002, time: 27.40147 + +2021-06-25T17:04:42.411822 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 3, summary_loss: 0.69167, final_score: 0.47688, time: 93.61025 +[RESULT]: Val. Epoch: 3, summary_loss: 0.73618, final_score: 0.46853, time: 26.43063 + +2021-06-25T17:06:42.627046 +LR: 0.001 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 4, summary_loss: 0.68982, final_score: 0.46976, time: 93.59109 +[RESULT]: Val. Epoch: 4, summary_loss: 0.69721, final_score: 0.47852, time: 26.91850 + +2021-06-25T17:08:43.293972 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 5, summary_loss: 0.69211, final_score: 0.47913, time: 92.84872 +[RESULT]: Val. Epoch: 5, summary_loss: 0.69176, final_score: 0.46004, time: 26.60076 + +2021-06-25T17:10:43.094845 +LR: 0.001 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 6, summary_loss: 0.69125, final_score: 0.47401, time: 92.39806 +[RESULT]: Val. Epoch: 6, summary_loss: 0.69276, final_score: 0.45005, time: 26.23754 + +2021-06-25T17:12:41.905266 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 7, summary_loss: 0.68825, final_score: 0.45989, time: 91.81298 +[RESULT]: Val. Epoch: 7, summary_loss: 0.77191, final_score: 0.46104, time: 26.86178 + +2021-06-25T17:14:40.745731 +LR: 0.001 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 8, summary_loss: 0.68520, final_score: 0.44701, time: 91.37273 +[RESULT]: Val. Epoch: 8, summary_loss: 1.40044, final_score: 0.47053, time: 26.55374 + +2021-06-25T17:16:38.841234 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 9, summary_loss: 0.68263, final_score: 0.44576, time: 91.86969 +[RESULT]: Val. Epoch: 9, summary_loss: 0.99067, final_score: 0.47103, time: 26.81184 + +2021-06-25T17:18:37.692061 +LR: 0.001 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 10, summary_loss: 0.67917, final_score: 0.43589, time: 91.65219 +[RESULT]: Val. Epoch: 10, summary_loss: 0.70260, final_score: 0.47802, time: 27.13233 + +2021-06-25T17:20:36.643088 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 11, summary_loss: 0.67505, final_score: 0.42889, time: 93.54137 +[RESULT]: Val. Epoch: 11, summary_loss: 0.73454, final_score: 0.42757, time: 26.61853 + +2021-06-25T17:22:36.973233 +LR: 0.001 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 12, summary_loss: 0.66992, final_score: 0.41377, time: 91.00299 +[RESULT]: Val. Epoch: 12, summary_loss: 0.69335, final_score: 0.41908, time: 26.31430 + +2021-06-25T17:24:34.459698 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 13, summary_loss: 0.66566, final_score: 0.40940, time: 93.23484 +[RESULT]: Val. Epoch: 13, summary_loss: 0.78469, final_score: 0.46154, time: 26.06900 + +2021-06-25T17:26:33.924265 +LR: 0.001 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 14, summary_loss: 0.66177, final_score: 0.40352, time: 90.67511 +[RESULT]: Val. Epoch: 14, summary_loss: 0.67287, final_score: 0.40759, time: 26.63251 + +2021-06-25T17:28:31.661393 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 15, summary_loss: 0.66162, final_score: 0.40202, time: 93.08614 +[RESULT]: Val. Epoch: 15, summary_loss: 0.72969, final_score: 0.44955, time: 25.93172 + +2021-06-25T17:30:30.851750 +LR: 0.001 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 16, summary_loss: 0.65633, final_score: 0.39865, time: 92.52313 +[RESULT]: Val. Epoch: 16, summary_loss: 0.71627, final_score: 0.42208, time: 26.60461 + +2021-06-25T17:32:30.160540 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 17, summary_loss: 0.65626, final_score: 0.39478, time: 92.12560 +[RESULT]: Val. Epoch: 17, summary_loss: 0.84604, final_score: 0.43307, time: 26.24162 + +2021-06-25T17:34:28.689516 +LR: 0.001 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 18, summary_loss: 0.64979, final_score: 0.38740, time: 91.44420 +[RESULT]: Val. Epoch: 18, summary_loss: 0.66119, final_score: 0.39061, time: 26.56512 + +2021-06-25T17:36:27.057355 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 19, summary_loss: 0.64730, final_score: 0.38378, time: 93.60628 +[RESULT]: Val. Epoch: 19, summary_loss: 0.69502, final_score: 0.42258, time: 26.06603 + +2021-06-25T17:38:26.892070 +LR: 0.001 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 20, summary_loss: 0.64393, final_score: 0.38440, time: 92.94526 +[RESULT]: Val. Epoch: 20, summary_loss: 0.77769, final_score: 0.44256, time: 26.09689 + +2021-06-25T17:40:26.108239 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 21, summary_loss: 0.63799, final_score: 0.37028, time: 93.53843 +[RESULT]: Val. Epoch: 21, summary_loss: 0.85309, final_score: 0.45305, time: 26.23910 + +2021-06-25T17:42:26.044453 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 22, summary_loss: 0.63757, final_score: 0.37628, time: 95.50904 +[RESULT]: Val. Epoch: 22, summary_loss: 0.66926, final_score: 0.38262, time: 26.56160 + +2021-06-25T17:44:28.285327 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 23, summary_loss: 0.63488, final_score: 0.36903, time: 94.39697 +[RESULT]: Val. Epoch: 23, summary_loss: 0.86658, final_score: 0.44655, time: 26.30430 + +2021-06-25T17:46:29.156973 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 24, summary_loss: 0.63006, final_score: 0.36166, time: 90.13190 +[RESULT]: Val. Epoch: 24, summary_loss: 0.65088, final_score: 0.36913, time: 27.66184 + +2021-06-25T17:48:27.310384 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 25, summary_loss: 0.62678, final_score: 0.35879, time: 93.78113 +[RESULT]: Val. Epoch: 25, summary_loss: 0.72419, final_score: 0.41508, time: 26.81470 + +2021-06-25T17:50:28.069764 +LR: 0.001 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 26, summary_loss: 0.62798, final_score: 0.35841, time: 90.89512 +[RESULT]: Val. Epoch: 26, summary_loss: 0.77097, final_score: 0.45205, time: 26.52522 + +2021-06-25T17:52:25.667718 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 27, summary_loss: 0.60423, final_score: 0.33379, time: 91.30385 +[RESULT]: Val. Epoch: 27, summary_loss: 0.64588, final_score: 0.35764, time: 26.04634 + +2021-06-25T17:54:23.359401 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 28, summary_loss: 0.60060, final_score: 0.32904, time: 92.77143 +[RESULT]: Val. Epoch: 28, summary_loss: 0.64957, final_score: 0.35764, time: 26.72790 + +2021-06-25T17:56:23.017958 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 29, summary_loss: 0.59548, final_score: 0.32554, time: 95.05364 +[RESULT]: Val. Epoch: 29, summary_loss: 0.66295, final_score: 0.37213, time: 28.72861 +Fitter prepared. Device is cuda:0 + +2021-06-26T08:54:45.532813 +LR: 0.0005 +Emb_rate: 1.2 +[RESULT]: Train. Epoch: 28, summary_loss: 0.64595, final_score: 0.38553, time: 95.28391 +[RESULT]: Val. Epoch: 28, summary_loss: 0.67999, final_score: 0.39860, time: 26.93565 + +2021-06-26T08:56:47.919486 +LR: 0.0005 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 29, summary_loss: 0.63727, final_score: 0.37303, time: 95.89335 +[RESULT]: Val. Epoch: 29, summary_loss: 0.66967, final_score: 0.40110, time: 26.19428 + +2021-06-26T08:58:50.174621 +LR: 0.0005 +Emb_rate: 1.08 +[RESULT]: Train. Epoch: 30, summary_loss: 0.63507, final_score: 0.37141, time: 93.81126 +[RESULT]: Val. Epoch: 30, summary_loss: 0.66911, final_score: 0.40809, time: 26.86840 + +2021-06-26T09:00:51.020626 +LR: 0.0005 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 31, summary_loss: 0.63206, final_score: 0.36966, time: 95.05546 +[RESULT]: Val. Epoch: 31, summary_loss: 0.67791, final_score: 0.40609, time: 26.16288 + +2021-06-26T09:02:52.413821 +LR: 0.0005 +Emb_rate: 0.9720000000000001 +[RESULT]: Train. Epoch: 32, summary_loss: 0.62928, final_score: 0.36878, time: 95.48339 +[RESULT]: Val. Epoch: 32, summary_loss: 0.67715, final_score: 0.39510, time: 26.61435 + +2021-06-26T09:04:54.673886 +LR: 0.0005 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 33, summary_loss: 0.62387, final_score: 0.36041, time: 94.93352 +[RESULT]: Val. Epoch: 33, summary_loss: 0.66178, final_score: 0.39610, time: 26.30066 + +2021-06-26T09:06:56.082676 +LR: 0.0005 +Emb_rate: 0.8748000000000001 +[RESULT]: Train. Epoch: 34, summary_loss: 0.62552, final_score: 0.36328, time: 97.09656 +[RESULT]: Val. Epoch: 34, summary_loss: 0.67647, final_score: 0.39311, time: 26.37876 + +2021-06-26T09:08:59.730977 +LR: 0.0005 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 35, summary_loss: 0.62016, final_score: 0.35279, time: 93.83566 +[RESULT]: Val. Epoch: 35, summary_loss: 0.67780, final_score: 0.41359, time: 26.49402 + +2021-06-26T09:11:00.233999 +LR: 0.0005 +Emb_rate: 0.7873200000000001 +[RESULT]: Train. Epoch: 36, summary_loss: 0.61605, final_score: 0.34791, time: 95.89333 +[RESULT]: Val. Epoch: 36, summary_loss: 0.68132, final_score: 0.38911, time: 26.49422 + +2021-06-26T09:13:02.784085 +LR: 0.0005 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 37, summary_loss: 0.61021, final_score: 0.34329, time: 93.52761 +[RESULT]: Val. Epoch: 37, summary_loss: 0.70939, final_score: 0.41858, time: 26.35232 + +2021-06-26T09:15:02.829843 +LR: 0.0005 +Emb_rate: 0.7085880000000001 +[RESULT]: Train. Epoch: 38, summary_loss: 0.61163, final_score: 0.34629, time: 95.22022 +[RESULT]: Val. Epoch: 38, summary_loss: 0.69477, final_score: 0.40759, time: 26.42527 + +2021-06-26T09:17:04.644833 +LR: 0.0005 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 39, summary_loss: 0.60489, final_score: 0.34216, time: 94.69657 +[RESULT]: Val. Epoch: 39, summary_loss: 0.65758, final_score: 0.37562, time: 26.67467 + +2021-06-26T09:19:06.360491 +LR: 0.0005 +Emb_rate: 0.6377292000000001 +[RESULT]: Train. Epoch: 40, summary_loss: 0.60246, final_score: 0.33904, time: 94.23796 +[RESULT]: Val. Epoch: 40, summary_loss: 0.84930, final_score: 0.40909, time: 26.50383 + +2021-06-26T09:21:07.273004 +LR: 0.0005 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 41, summary_loss: 0.59631, final_score: 0.33129, time: 93.60920 +[RESULT]: Val. Epoch: 41, summary_loss: 0.74863, final_score: 0.39161, time: 27.27740 + +2021-06-26T09:23:08.322591 +LR: 0.0005 +Emb_rate: 0.5739562800000001 +[RESULT]: Train. Epoch: 42, summary_loss: 0.59315, final_score: 0.32692, time: 95.23748 +[RESULT]: Val. Epoch: 42, summary_loss: 0.79510, final_score: 0.40609, time: 26.64147 + +2021-06-26T09:25:10.376095 +LR: 0.0005 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 43, summary_loss: 0.59229, final_score: 0.32029, time: 95.02045 +[RESULT]: Val. Epoch: 43, summary_loss: 0.76681, final_score: 0.39610, time: 26.31017 + +2021-06-26T09:27:11.871989 +LR: 0.0005 +Emb_rate: 0.5165606520000001 +[RESULT]: Train. Epoch: 44, summary_loss: 0.58279, final_score: 0.31130, time: 95.47593 +[RESULT]: Val. Epoch: 44, summary_loss: 0.67924, final_score: 0.38312, time: 26.73752 + +2021-06-26T09:29:14.264247 +LR: 0.0005 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 45, summary_loss: 0.58291, final_score: 0.31117, time: 95.57675 +[RESULT]: Val. Epoch: 45, summary_loss: 0.77155, final_score: 0.41359, time: 26.11944 + +2021-06-26T09:31:16.122309 +LR: 0.0005 +Emb_rate: 0.46490458680000013 +[RESULT]: Train. Epoch: 46, summary_loss: 0.57644, final_score: 0.31230, time: 94.31031 +[RESULT]: Val. Epoch: 46, summary_loss: 0.71888, final_score: 0.38661, time: 26.38289 + +2021-06-26T09:33:16.995200 +LR: 0.0005 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 47, summary_loss: 0.57141, final_score: 0.30080, time: 95.64550 +[RESULT]: Val. Epoch: 47, summary_loss: 0.87186, final_score: 0.38611, time: 26.39645 + +2021-06-26T09:35:19.199814 +LR: 0.0005 +Emb_rate: 0.4184141281200001 +[RESULT]: Train. Epoch: 48, summary_loss: 0.56688, final_score: 0.30192, time: 93.92024 +[RESULT]: Val. Epoch: 48, summary_loss: 0.73663, final_score: 0.37962, time: 26.16328 + +2021-06-26T09:37:19.451624 +LR: 0.0005 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 49, summary_loss: 0.55961, final_score: 0.29793, time: 94.07254 +[RESULT]: Val. Epoch: 49, summary_loss: 0.73642, final_score: 0.37962, time: 26.91921 + +2021-06-26T09:39:20.622625 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 50, summary_loss: 0.53956, final_score: 0.27931, time: 95.08114 +[RESULT]: Val. Epoch: 50, summary_loss: 0.78716, final_score: 0.38511, time: 26.35582 + +2021-06-26T09:41:22.242457 +LR: 0.00025 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 51, summary_loss: 0.52745, final_score: 0.26718, time: 97.89264 +[RESULT]: Val. Epoch: 51, summary_loss: 0.70853, final_score: 0.37313, time: 26.29456 + +2021-06-26T09:43:26.598687 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 52, summary_loss: 0.51205, final_score: 0.25294, time: 92.25798 +[RESULT]: Val. Epoch: 52, summary_loss: 0.80418, final_score: 0.37363, time: 26.41416 + +2021-06-26T09:45:25.465353 +LR: 0.000125 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 53, summary_loss: 0.49827, final_score: 0.24881, time: 93.49706 +[RESULT]: Val. Epoch: 53, summary_loss: 0.72076, final_score: 0.36014, time: 26.93145 + +2021-06-26T09:47:26.061890 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 54, summary_loss: 0.48582, final_score: 0.23469, time: 96.33958 +[RESULT]: Val. Epoch: 54, summary_loss: 0.75542, final_score: 0.35864, time: 26.58252 + +2021-06-26T09:49:29.154160 +LR: 6.25e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 55, summary_loss: 0.48271, final_score: 0.23357, time: 95.84486 +[RESULT]: Val. Epoch: 55, summary_loss: 0.74706, final_score: 0.35514, time: 26.33549 + +2021-06-26T09:51:31.504518 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 56, summary_loss: 0.47893, final_score: 0.23319, time: 92.95418 +[RESULT]: Val. Epoch: 56, summary_loss: 0.74524, final_score: 0.35365, time: 26.25441 + +2021-06-26T09:53:30.895555 +LR: 3.125e-05 +Emb_rate: 0.4 +[RESULT]: Train. Epoch: 57, summary_loss: 0.47454, final_score: 0.22669, time: 93.05884 +[RESULT]: Val. Epoch: 57, summary_loss: 0.74395, final_score: 0.35564, time: 26.54376