Task 3056621
| Name | ParityModified-1606097356-5999-16_0 |
| Workunit | 1388104 |
| Created | 25 Nov 2020, 6:02:37 UTC |
| Sent | 25 Nov 2020, 6:15:41 UTC |
| Report deadline | 2 Dec 2020, 6:15:41 UTC |
| Received | 25 Nov 2020, 6:20:55 UTC |
| Server state | Over |
| Outcome | Success |
| Client state | Done |
| Exit status | 0 (0x00000000) |
| Computer ID | 4754 |
| Run time | 4 min 40 sec |
| CPU time | 4 min 36 sec |
| Validate state | Valid |
| Credit | 780.00 |
| Device peak FLOPS | 3,339.24 GFLOPS |
| Application version | Machine Learning Dataset Generator (test) v9.80 (cuda10200) x86_64-pc-linux-gnu |
| Peak working set size | 2.32 GB |
| Peak swap size | 10.43 GB |
| Peak disk usage | 2.98 GB |
Stderr output
<core_client_version>7.14.2</core_client_version> <![CDATA[ <stderr_txt> DEBUG: Args: ../../projects/www.mlcathome.org_mlcathome/mlds-gpu_9.80_x86_64-pc-linux-gnu__cuda10200 -c --maxepoch 128 nthreads: 1 gpudev: 0 Re-exec()-ing to set environment correctly Machine Learning Dataset Generator v9.80 (Linux/x86_64) (libTorch: release/1.7 GPU: GeForce GTX 1650) [2020-11-25 01:16:06 main:442] : INFO : Set logging level to 1 [2020-11-25 01:16:06 main:448] : INFO : Running in BOINC Client mode [2020-11-25 01:16:06 main:451] : INFO : Resolving all filenames [2020-11-25 01:16:06 main:459] : INFO : Resolved: dataset.hdf5 => ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 (exists = 1) [2020-11-25 01:16:06 main:459] : INFO : Resolved: model.cfg => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-16_0_r1223336329_1 (exists = 0) [2020-11-25 01:16:06 main:459] : INFO : Resolved: model-final.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-16_0_r1223336329_0 (exists = 0) [2020-11-25 01:16:06 main:459] : INFO : Resolved: model-input.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-16 (exists = 1) [2020-11-25 01:16:06 main:459] : INFO : Resolved: snapshot.pt => snapshot.pt (exists = 0) [2020-11-25 01:16:06 main:479] : INFO : Dataset filename: ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 [2020-11-25 01:16:06 main:481] : INFO : Configuration: [2020-11-25 01:16:06 main:482] : INFO : Model type: GRU [2020-11-25 01:16:06 main:483] : INFO : Validation Loss Threshold: 0.0001 [2020-11-25 01:16:06 main:484] : INFO : Max Epochs: 128 [2020-11-25 01:16:06 main:485] : INFO : Batch Size: 128 [2020-11-25 01:16:06 main:486] : INFO : Learning Rate: 0.01 [2020-11-25 01:16:06 main:487] : INFO : Patience: 10 [2020-11-25 01:16:06 main:488] : INFO : Hidden Width: 12 [2020-11-25 01:16:06 main:489] : INFO : # Recurrent Layers: 4 [2020-11-25 01:16:06 main:490] : INFO : # Backend Layers: 4 [2020-11-25 01:16:06 main:491] : INFO : # Threads: 1 [2020-11-25 01:16:06 main:493] : INFO : Preparing Dataset [2020-11-25 01:16:06 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Xt from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-25 01:16:06 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Yt from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-25 01:16:09 load:106] : INFO : Successfully loaded dataset of 2048 examples into memory. [2020-11-25 01:16:09 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Xv from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-25 01:16:09 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Yv from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-25 01:16:09 load:106] : INFO : Successfully loaded dataset of 512 examples into memory. [2020-11-25 01:16:09 main:501] : INFO : Creating Model [2020-11-25 01:16:09 main:514] : INFO : Preparing config file [2020-11-25 01:16:09 main:526] : INFO : Creating new config file [2020-11-25 01:16:09 main:545] : INFO : This is a continuation WU, loading previous network [2020-11-25 01:16:10 main:566] : INFO : Loading DataLoader into Memory [2020-11-25 01:16:10 main:569] : INFO : Starting Training [2020-11-25 01:16:13 main:581] : INFO : Epoch 1 | loss: 0.0311493 | val_loss: 0.03116 | Time: 3002.95 ms [2020-11-25 01:16:15 main:581] : INFO : Epoch 2 | loss: 0.0311168 | val_loss: 0.0311639 | Time: 2133.94 ms [2020-11-25 01:16:17 main:581] : INFO : Epoch 3 | loss: 0.0311146 | val_loss: 0.0311635 | Time: 2140.77 ms [2020-11-25 01:16:19 main:581] : INFO : Epoch 4 | loss: 0.0311109 | val_loss: 0.0311619 | Time: 2128.17 ms [2020-11-25 01:16:21 main:581] : INFO : Epoch 5 | loss: 0.0311095 | val_loss: 0.0311664 | Time: 2118.26 ms [2020-11-25 01:16:23 main:581] : INFO : Epoch 6 | loss: 0.0311151 | val_loss: 0.0311592 | Time: 2140.79 ms [2020-11-25 01:16:25 main:581] : INFO : Epoch 7 | loss: 0.0311092 | val_loss: 0.0311579 | Time: 2126.89 ms [2020-11-25 01:16:27 main:581] : INFO : Epoch 8 | loss: 0.0311047 | val_loss: 0.0311614 | Time: 2114.52 ms [2020-11-25 01:16:30 main:581] : INFO : Epoch 9 | loss: 0.0311031 | val_loss: 0.031162 | Time: 2105.24 ms [2020-11-25 01:16:32 main:581] : INFO : Epoch 10 | loss: 0.0311061 | val_loss: 0.0311626 | Time: 2123.44 ms [2020-11-25 01:16:34 main:581] : INFO : Epoch 11 | loss: 0.0311033 | val_loss: 0.0311595 | Time: 2117.72 ms [2020-11-25 01:16:36 main:581] : INFO : Epoch 12 | loss: 0.0310996 | val_loss: 0.0311621 | Time: 2124.87 ms [2020-11-25 01:16:38 main:581] : INFO : Epoch 13 | loss: 0.0310968 | val_loss: 0.0311609 | Time: 2118.15 ms [2020-11-25 01:16:40 main:581] : INFO : Epoch 14 | loss: 0.0310967 | val_loss: 0.031159 | Time: 2134.87 ms [2020-11-25 01:16:42 main:581] : INFO : Epoch 15 | loss: 0.0310979 | val_loss: 0.0311701 | Time: 2139.5 ms [2020-11-25 01:16:44 main:581] : INFO : Epoch 16 | loss: 0.0311004 | val_loss: 0.0311657 | Time: 2108.8 ms [2020-11-25 01:16:47 main:581] : INFO : Epoch 17 | loss: 0.0311009 | val_loss: 0.0311666 | Time: 2120.97 ms [2020-11-25 01:16:49 main:581] : INFO : Epoch 18 | loss: 0.0311001 | val_loss: 0.0311699 | Time: 2115.68 ms [2020-11-25 01:16:51 main:581] : INFO : Epoch 19 | loss: 0.0310998 | val_loss: 0.0311603 | Time: 2140.83 ms [2020-11-25 01:16:53 main:581] : INFO : Epoch 20 | loss: 0.0310961 | val_loss: 0.0311718 | Time: 2156.54 ms [2020-11-25 01:16:55 main:581] : INFO : Epoch 21 | loss: 0.031095 | val_loss: 0.0311614 | Time: 2162.71 ms [2020-11-25 01:16:57 main:581] : INFO : Epoch 22 | loss: 0.031097 | val_loss: 0.0311643 | Time: 2137.78 ms [2020-11-25 01:16:59 main:581] : INFO : Epoch 23 | loss: 0.0310965 | val_loss: 0.0311719 | Time: 2115.72 ms [2020-11-25 01:17:01 main:581] : INFO : Epoch 24 | loss: 0.0310926 | val_loss: 0.0311643 | Time: 2142.95 ms [2020-11-25 01:17:04 main:581] : INFO : Epoch 25 | loss: 0.0310913 | val_loss: 0.031171 | Time: 2138.53 ms [2020-11-25 01:17:06 main:581] : INFO : Epoch 26 | loss: 0.0310922 | val_loss: 0.0311702 | Time: 2139.75 ms [2020-11-25 01:17:08 main:581] : INFO : Epoch 27 | loss: 0.0310975 | val_loss: 0.0311667 | Time: 2136.73 ms [2020-11-25 01:17:10 main:581] : INFO : Epoch 28 | loss: 0.0311001 | val_loss: 0.0311652 | Time: 2154.47 ms [2020-11-25 01:17:12 main:581] : INFO : Epoch 29 | loss: 0.0310956 | val_loss: 0.0311651 | Time: 2133.91 ms [2020-11-25 01:17:14 main:581] : INFO : Epoch 30 | loss: 0.0310941 | val_loss: 0.0311601 | Time: 2109.46 ms [2020-11-25 01:17:16 main:581] : INFO : Epoch 31 | loss: 0.0310999 | val_loss: 0.0311642 | Time: 2110.32 ms [2020-11-25 01:17:19 main:581] : INFO : Epoch 32 | loss: 0.0311045 | val_loss: 0.0311672 | Time: 2105.2 ms [2020-11-25 01:17:21 main:581] : INFO : Epoch 33 | loss: 0.0311031 | val_loss: 0.0311654 | Time: 2153.98 ms [2020-11-25 01:17:23 main:581] : INFO : Epoch 34 | loss: 0.0310987 | val_loss: 0.0311745 | Time: 2136.72 ms [2020-11-25 01:17:25 main:581] : INFO : Epoch 35 | loss: 0.0311209 | val_loss: 0.0311667 | Time: 2122.94 ms [2020-11-25 01:17:27 main:581] : INFO : Epoch 36 | loss: 0.031115 | val_loss: 0.0311572 | Time: 2107.04 ms [2020-11-25 01:17:29 main:581] : INFO : Epoch 37 | loss: 0.0311103 | val_loss: 0.0311695 | Time: 2114.98 ms [2020-11-25 01:17:31 main:581] : INFO : Epoch 38 | loss: 0.0311019 | val_loss: 0.0311641 | Time: 2130.5 ms [2020-11-25 01:17:33 main:581] : INFO : Epoch 39 | loss: 0.0311006 | val_loss: 0.0311672 | Time: 2114.72 ms [2020-11-25 01:17:36 main:581] : INFO : Epoch 40 | loss: 0.0310983 | val_loss: 0.0311621 | Time: 2110.61 ms [2020-11-25 01:17:38 main:581] : INFO : Epoch 41 | loss: 0.0310966 | val_loss: 0.0311752 | Time: 2110.3 ms [2020-11-25 01:17:40 main:581] : INFO : Epoch 42 | loss: 0.0310919 | val_loss: 0.0311672 | Time: 2119.07 ms [2020-11-25 01:17:42 main:581] : INFO : Epoch 43 | loss: 0.031091 | val_loss: 0.0311602 | Time: 2134.91 ms [2020-11-25 01:17:44 main:581] : INFO : Epoch 44 | loss: 0.0310972 | val_loss: 0.0311751 | Time: 2127.58 ms [2020-11-25 01:17:46 main:581] : INFO : Epoch 45 | loss: 0.0311084 | val_loss: 0.0311561 | Time: 2118.7 ms [2020-11-25 01:17:48 main:581] : INFO : Epoch 46 | loss: 0.0311123 | val_loss: 0.0311575 | Time: 2149.52 ms [2020-11-25 01:17:50 main:581] : INFO : Epoch 47 | loss: 0.0311022 | val_loss: 0.0311552 | Time: 2140.06 ms [2020-11-25 01:17:53 main:581] : INFO : Epoch 48 | loss: 0.0310994 | val_loss: 0.0311612 | Time: 2144.97 ms [2020-11-25 01:17:55 main:581] : INFO : Epoch 49 | loss: 0.0310957 | val_loss: 0.0311635 | Time: 2148.76 ms [2020-11-25 01:17:57 main:581] : INFO : Epoch 50 | loss: 0.031096 | val_loss: 0.0311643 | Time: 2146.28 ms [2020-11-25 01:17:59 main:581] : INFO : Epoch 51 | loss: 0.0310926 | val_loss: 0.0311666 | Time: 2149.52 ms [2020-11-25 01:18:01 main:581] : INFO : Epoch 52 | loss: 0.0310989 | val_loss: 0.0311673 | Time: 2139.11 ms [2020-11-25 01:18:03 main:581] : INFO : Epoch 53 | loss: 0.0310943 | val_loss: 0.0311643 | Time: 2141.46 ms [2020-11-25 01:18:05 main:581] : INFO : Epoch 54 | loss: 0.0310924 | val_loss: 0.0311664 | Time: 2137.45 ms [2020-11-25 01:18:08 main:581] : INFO : Epoch 55 | loss: 0.0310907 | val_loss: 0.0311676 | Time: 2137.92 ms [2020-11-25 01:18:10 main:581] : INFO : Epoch 56 | loss: 0.0310884 | val_loss: 0.0311613 | Time: 2121.87 ms [2020-11-25 01:18:12 main:581] : INFO : Epoch 57 | loss: 0.0310916 | val_loss: 0.0311647 | Time: 2126.59 ms [2020-11-25 01:18:14 main:581] : INFO : Epoch 58 | loss: 0.031095 | val_loss: 0.0311733 | Time: 2136.35 ms [2020-11-25 01:18:16 main:581] : INFO : Epoch 59 | loss: 0.0310917 | val_loss: 0.0311692 | Time: 2144.77 ms [2020-11-25 01:18:18 main:581] : INFO : Epoch 60 | loss: 0.0310919 | val_loss: 0.0311722 | Time: 2138.22 ms [2020-11-25 01:18:20 main:581] : INFO : Epoch 61 | loss: 0.0310897 | val_loss: 0.031167 | Time: 2138.76 ms [2020-11-25 01:18:23 main:581] : INFO : Epoch 62 | loss: 0.0310944 | val_loss: 0.0311731 | Time: 2132.73 ms [2020-11-25 01:18:25 main:581] : INFO : Epoch 63 | loss: 0.0310883 | val_loss: 0.0311643 | Time: 2132.25 ms [2020-11-25 01:18:27 main:581] : INFO : Epoch 64 | loss: 0.0310849 | val_loss: 0.0311707 | Time: 2138.48 ms [2020-11-25 01:18:29 main:581] : INFO : Epoch 65 | loss: 0.0310894 | val_loss: 0.0311717 | Time: 2141.57 ms [2020-11-25 01:18:31 main:581] : INFO : Epoch 66 | loss: 0.0310955 | val_loss: 0.0311791 | Time: 2145.63 ms [2020-11-25 01:18:33 main:581] : INFO : Epoch 67 | loss: 0.0311232 | val_loss: 0.0311723 | Time: 2130.27 ms [2020-11-25 01:18:35 main:581] : INFO : Epoch 68 | loss: 0.031124 | val_loss: 0.0311614 | Time: 2152.18 ms [2020-11-25 01:18:37 main:581] : INFO : Epoch 69 | loss: 0.0311206 | val_loss: 0.0311702 | Time: 2143.76 ms [2020-11-25 01:18:40 main:581] : INFO : Epoch 70 | loss: 0.0311147 | val_loss: 0.0311674 | Time: 2135.16 ms [2020-11-25 01:18:42 main:581] : INFO : Epoch 71 | loss: 0.0311132 | val_loss: 0.0311695 | Time: 2137.16 ms [2020-11-25 01:18:44 main:581] : INFO : Epoch 72 | loss: 0.0311097 | val_loss: 0.0311619 | Time: 2150.41 ms [2020-11-25 01:18:46 main:581] : INFO : Epoch 73 | loss: 0.0311078 | val_loss: 0.0311639 | Time: 2128.29 ms [2020-11-25 01:18:48 main:581] : INFO : Epoch 74 | loss: 0.0311026 | val_loss: 0.0311699 | Time: 2133.36 ms [2020-11-25 01:18:50 main:581] : INFO : Epoch 75 | loss: 0.0310981 | val_loss: 0.0311689 | Time: 2138.87 ms [2020-11-25 01:18:52 main:581] : INFO : Epoch 76 | loss: 0.0310945 | val_loss: 0.0311744 | Time: 2128.98 ms [2020-11-25 01:18:55 main:581] : INFO : Epoch 77 | loss: 0.0310939 | val_loss: 0.0311637 | Time: 2134.15 ms [2020-11-25 01:18:57 main:581] : INFO : Epoch 78 | loss: 0.0310918 | val_loss: 0.0311647 | Time: 2115.56 ms [2020-11-25 01:18:59 main:581] : INFO : Epoch 79 | loss: 0.0310928 | val_loss: 0.0311605 | Time: 2129.62 ms [2020-11-25 01:19:01 main:581] : INFO : Epoch 80 | loss: 0.0310909 | val_loss: 0.0311701 | Time: 2108.96 ms [2020-11-25 01:19:03 main:581] : INFO : Epoch 81 | loss: 0.0310927 | val_loss: 0.0311722 | Time: 2109.61 ms [2020-11-25 01:19:05 main:581] : INFO : Epoch 82 | loss: 0.0310919 | val_loss: 0.031165 | Time: 2122.73 ms [2020-11-25 01:19:07 main:581] : INFO : Epoch 83 | loss: 0.0310938 | val_loss: 0.0311734 | Time: 2145.3 ms [2020-11-25 01:19:09 main:581] : INFO : Epoch 84 | loss: 0.0310905 | val_loss: 0.0311648 | Time: 2134.41 ms [2020-11-25 01:19:12 main:581] : INFO : Epoch 85 | loss: 0.0310868 | val_loss: 0.0311674 | Time: 2144.91 ms [2020-11-25 01:19:14 main:581] : INFO : Epoch 86 | loss: 0.0310857 | val_loss: 0.0311745 | Time: 2126.29 ms [2020-11-25 01:19:16 main:581] : INFO : Epoch 87 | loss: 0.0310878 | val_loss: 0.031164 | Time: 2120.08 ms [2020-11-25 01:19:18 main:581] : INFO : Epoch 88 | loss: 0.0310956 | val_loss: 0.0311777 | Time: 2127.68 ms [2020-11-25 01:19:20 main:581] : INFO : Epoch 89 | loss: 0.0310925 | val_loss: 0.0311733 | Time: 2117.65 ms [2020-11-25 01:19:22 main:581] : INFO : Epoch 90 | loss: 0.0310898 | val_loss: 0.0311689 | Time: 2127.04 ms [2020-11-25 01:19:24 main:581] : INFO : Epoch 91 | loss: 0.0310903 | val_loss: 0.03117 | Time: 2138.8 ms [2020-11-25 01:19:26 main:581] : INFO : Epoch 92 | loss: 0.0310877 | val_loss: 0.0311696 | Time: 2118.21 ms [2020-11-25 01:19:29 main:581] : INFO : Epoch 93 | loss: 0.0310876 | val_loss: 0.0311696 | Time: 2136.91 ms [2020-11-25 01:19:31 main:581] : INFO : Epoch 94 | loss: 0.0310879 | val_loss: 0.0311769 | Time: 2151.39 ms [2020-11-25 01:19:33 main:581] : INFO : Epoch 95 | loss: 0.0310903 | val_loss: 0.0311706 | Time: 2148.03 ms [2020-11-25 01:19:35 main:581] : INFO : Epoch 96 | loss: 0.0310899 | val_loss: 0.0311737 | Time: 2139.1 ms [2020-11-25 01:19:37 main:581] : INFO : Epoch 97 | loss: 0.0311005 | val_loss: 0.0311631 | Time: 2152.12 ms [2020-11-25 01:19:39 main:581] : INFO : Epoch 98 | loss: 0.0310954 | val_loss: 0.0311689 | Time: 2169.48 ms [2020-11-25 01:19:42 main:581] : INFO : Epoch 99 | loss: 0.031098 | val_loss: 0.0311707 | Time: 2153.12 ms [2020-11-25 01:19:44 main:581] : INFO : Epoch 100 | loss: 0.0310967 | val_loss: 0.0311739 | Time: 2143.04 ms [2020-11-25 01:19:46 main:581] : INFO : Epoch 101 | loss: 0.031097 | val_loss: 0.0311644 | Time: 2152.38 ms [2020-11-25 01:19:48 main:581] : INFO : Epoch 102 | loss: 0.0311016 | val_loss: 0.0311714 | Time: 2152.22 ms [2020-11-25 01:19:50 main:581] : INFO : Epoch 103 | loss: 0.0310971 | val_loss: 0.0311675 | Time: 2132.23 ms [2020-11-25 01:19:52 main:581] : INFO : Epoch 104 | loss: 0.0310907 | val_loss: 0.0311738 | Time: 2139.92 ms [2020-11-25 01:19:54 main:581] : INFO : Epoch 105 | loss: 0.0310881 | val_loss: 0.0311706 | Time: 2150.2 ms [2020-11-25 01:19:57 main:581] : INFO : Epoch 106 | loss: 0.031095 | val_loss: 0.0311674 | Time: 2152.16 ms [2020-11-25 01:19:59 main:581] : INFO : Epoch 107 | loss: 0.0310926 | val_loss: 0.0311737 | Time: 2167.46 ms [2020-11-25 01:20:01 main:581] : INFO : Epoch 108 | loss: 0.0310913 | val_loss: 0.0311668 | Time: 2124.83 ms [2020-11-25 01:20:03 main:581] : INFO : Epoch 109 | loss: 0.0310943 | val_loss: 0.0311703 | Time: 2122.05 ms [2020-11-25 01:20:05 main:581] : INFO : Epoch 110 | loss: 0.0310953 | val_loss: 0.031176 | Time: 2114.5 ms [2020-11-25 01:20:07 main:581] : INFO : Epoch 111 | loss: 0.0310992 | val_loss: 0.0311763 | Time: 2118.2 ms [2020-11-25 01:20:09 main:581] : INFO : Epoch 112 | loss: 0.0310924 | val_loss: 0.0311702 | Time: 2137.23 ms [2020-11-25 01:20:11 main:581] : INFO : Epoch 113 | loss: 0.0310912 | val_loss: 0.0311777 | Time: 2119.1 ms [2020-11-25 01:20:14 main:581] : INFO : Epoch 114 | loss: 0.0310856 | val_loss: 0.0311726 | Time: 2128.44 ms [2020-11-25 01:20:16 main:581] : INFO : Epoch 115 | loss: 0.0310848 | val_loss: 0.0311705 | Time: 2120.44 ms [2020-11-25 01:20:18 main:581] : INFO : Epoch 116 | loss: 0.0310862 | val_loss: 0.0311694 | Time: 2140.71 ms [2020-11-25 01:20:20 main:581] : INFO : Epoch 117 | loss: 0.0310838 | val_loss: 0.0311738 | Time: 2125.22 ms [2020-11-25 01:20:22 main:581] : INFO : Epoch 118 | loss: 0.0310874 | val_loss: 0.031175 | Time: 2148.21 ms [2020-11-25 01:20:24 main:581] : INFO : Epoch 119 | loss: 0.0310953 | val_loss: 0.0311703 | Time: 2143.78 ms [2020-11-25 01:20:26 main:581] : INFO : Epoch 120 | loss: 0.0310934 | val_loss: 0.0311773 | Time: 2161.02 ms [2020-11-25 01:20:29 main:581] : INFO : Epoch 121 | loss: 0.0310877 | val_loss: 0.0311712 | Time: 2138.27 ms [2020-11-25 01:20:31 main:581] : INFO : Epoch 122 | loss: 0.031087 | val_loss: 0.0311778 | Time: 2135.09 ms [2020-11-25 01:20:33 main:581] : INFO : Epoch 123 | loss: 0.0310868 | val_loss: 0.0311686 | Time: 2132.23 ms [2020-11-25 01:20:35 main:581] : INFO : Epoch 124 | loss: 0.0310836 | val_loss: 0.0311792 | Time: 2133.32 ms [2020-11-25 01:20:37 main:581] : INFO : Epoch 125 | loss: 0.0310825 | val_loss: 0.031177 | Time: 2157.76 ms [2020-11-25 01:20:39 main:581] : INFO : Epoch 126 | loss: 0.0310833 | val_loss: 0.0311766 | Time: 2160 ms [2020-11-25 01:20:41 main:581] : INFO : Epoch 127 | loss: 0.0310847 | val_loss: 0.0311753 | Time: 2150.73 ms [2020-11-25 01:20:44 main:581] : INFO : Epoch 128 | loss: 0.0310898 | val_loss: 0.0311707 | Time: 2159.46 ms [2020-11-25 01:20:44 main:604] : INFO : Saving trained model to model-final.pt, val_loss 0.0311707 [2020-11-25 01:20:44 main:610] : INFO : Saving end state to config to file [2020-11-25 01:20:44 main:615] : INFO : Success, exiting.. 01:20:44 (10086): called boinc_finish(0) </stderr_txt> ]]>
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A project of the Cognition, Robotics, and Learning (CORAL) Lab at the University of Maryland, Baltimore County (UMBC)