Task 3056862
| Name | ParityModified-1606097356-5999-18_0 |
| Workunit | 1388327 |
| Created | 25 Nov 2020, 6:39:50 UTC |
| Sent | 25 Nov 2020, 6:53:23 UTC |
| Report deadline | 2 Dec 2020, 6:53:23 UTC |
| Received | 25 Nov 2020, 6:58:02 UTC |
| Server state | Over |
| Outcome | Success |
| Client state | Done |
| Exit status | 0 (0x00000000) |
| Computer ID | 4754 |
| Run time | 4 min 12 sec |
| CPU time | 4 min 7 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 | 2.33 GB |
| Peak swap size | 10.45 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 01:53:41 main:442] : INFO : Set logging level to 1 [2020-11-25 01:53:41 main:448] : INFO : Running in BOINC Client mode [2020-11-25 01:53:41 main:451] : INFO : Resolving all filenames [2020-11-25 01:53:41 main:459] : INFO : Resolved: dataset.hdf5 => ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 (exists = 1) [2020-11-25 01:53:41 main:459] : INFO : Resolved: model.cfg => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-18_0_r1544720596_1 (exists = 0) [2020-11-25 01:53:41 main:459] : INFO : Resolved: model-final.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-18_0_r1544720596_0 (exists = 0) [2020-11-25 01:53:41 main:459] : INFO : Resolved: model-input.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-18 (exists = 1) [2020-11-25 01:53:41 main:459] : INFO : Resolved: snapshot.pt => snapshot.pt (exists = 0) [2020-11-25 01:53:41 main:479] : INFO : Dataset filename: ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 [2020-11-25 01:53:41 main:481] : INFO : Configuration: [2020-11-25 01:53:41 main:482] : INFO : Model type: GRU [2020-11-25 01:53:41 main:483] : INFO : Validation Loss Threshold: 0.0001 [2020-11-25 01:53:41 main:484] : INFO : Max Epochs: 128 [2020-11-25 01:53:41 main:485] : INFO : Batch Size: 128 [2020-11-25 01:53:41 main:486] : INFO : Learning Rate: 0.01 [2020-11-25 01:53:41 main:487] : INFO : Patience: 10 [2020-11-25 01:53:41 main:488] : INFO : Hidden Width: 12 [2020-11-25 01:53:41 main:489] : INFO : # Recurrent Layers: 4 [2020-11-25 01:53:41 main:490] : INFO : # Backend Layers: 4 [2020-11-25 01:53:41 main:491] : INFO : # Threads: 1 [2020-11-25 01:53:41 main:493] : INFO : Preparing Dataset [2020-11-25 01:53:41 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 01:53:41 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 01:53:44 load:106] : INFO : Successfully loaded dataset of 2048 examples into memory. [2020-11-25 01:53:44 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 01:53:44 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 01:53:44 load:106] : INFO : Successfully loaded dataset of 512 examples into memory. [2020-11-25 01:53:44 main:501] : INFO : Creating Model [2020-11-25 01:53:44 main:514] : INFO : Preparing config file [2020-11-25 01:53:44 main:526] : INFO : Creating new config file [2020-11-25 01:53:44 main:545] : INFO : This is a continuation WU, loading previous network [2020-11-25 01:53:44 main:566] : INFO : Loading DataLoader into Memory [2020-11-25 01:53:44 main:569] : INFO : Starting Training [2020-11-25 01:53:47 main:581] : INFO : Epoch 1 | loss: 0.0311392 | val_loss: 0.0311682 | Time: 2740.82 ms [2020-11-25 01:53:49 main:581] : INFO : Epoch 2 | loss: 0.0311014 | val_loss: 0.0311648 | Time: 1879.49 ms [2020-11-25 01:53:51 main:581] : INFO : Epoch 3 | loss: 0.0310974 | val_loss: 0.0311615 | Time: 2030.5 ms [2020-11-25 01:53:53 main:581] : INFO : Epoch 4 | loss: 0.0310966 | val_loss: 0.0311643 | Time: 1784.33 ms [2020-11-25 01:53:55 main:581] : INFO : Epoch 5 | loss: 0.0311003 | val_loss: 0.03116 | Time: 1996.02 ms [2020-11-25 01:53:57 main:581] : INFO : Epoch 6 | loss: 0.031097 | val_loss: 0.0311631 | Time: 2028.67 ms [2020-11-25 01:53:59 main:581] : INFO : Epoch 7 | loss: 0.0310927 | val_loss: 0.0311606 | Time: 2054.24 ms [2020-11-25 01:54:01 main:581] : INFO : Epoch 8 | loss: 0.0310889 | val_loss: 0.0311656 | Time: 1870.12 ms [2020-11-25 01:54:03 main:581] : INFO : Epoch 9 | loss: 0.0310843 | val_loss: 0.0311703 | Time: 1961.93 ms [2020-11-25 01:54:05 main:581] : INFO : Epoch 10 | loss: 0.0310844 | val_loss: 0.0311663 | Time: 2040.76 ms [2020-11-25 01:54:07 main:581] : INFO : Epoch 11 | loss: 0.0310827 | val_loss: 0.0311702 | Time: 2024.18 ms [2020-11-25 01:54:09 main:581] : INFO : Epoch 12 | loss: 0.0310828 | val_loss: 0.0311705 | Time: 2042.48 ms [2020-11-25 01:54:11 main:581] : INFO : Epoch 13 | loss: 0.0311118 | val_loss: 0.0311536 | Time: 1973.88 ms [2020-11-25 01:54:13 main:581] : INFO : Epoch 14 | loss: 0.0311066 | val_loss: 0.0311629 | Time: 1960.79 ms [2020-11-25 01:54:15 main:581] : INFO : Epoch 15 | loss: 0.0311022 | val_loss: 0.0311715 | Time: 1980.09 ms [2020-11-25 01:54:17 main:581] : INFO : Epoch 16 | loss: 0.031109 | val_loss: 0.0311709 | Time: 2086.34 ms [2020-11-25 01:54:19 main:581] : INFO : Epoch 17 | loss: 0.0311114 | val_loss: 0.0311686 | Time: 2048.25 ms [2020-11-25 01:54:21 main:581] : INFO : Epoch 18 | loss: 0.0311069 | val_loss: 0.0311665 | Time: 1973.86 ms [2020-11-25 01:54:23 main:581] : INFO : Epoch 19 | loss: 0.0310996 | val_loss: 0.0311553 | Time: 2012.59 ms [2020-11-25 01:54:25 main:581] : INFO : Epoch 20 | loss: 0.031094 | val_loss: 0.0311601 | Time: 1878.28 ms [2020-11-25 01:54:27 main:581] : INFO : Epoch 21 | loss: 0.0310913 | val_loss: 0.0311608 | Time: 2073.74 ms [2020-11-25 01:54:29 main:581] : INFO : Epoch 22 | loss: 0.0310868 | val_loss: 0.0311605 | Time: 1909.86 ms [2020-11-25 01:54:31 main:581] : INFO : Epoch 23 | loss: 0.0310902 | val_loss: 0.0311705 | Time: 1719.77 ms [2020-11-25 01:54:32 main:581] : INFO : Epoch 24 | loss: 0.0310864 | val_loss: 0.0311699 | Time: 1902.85 ms [2020-11-25 01:54:34 main:581] : INFO : Epoch 25 | loss: 0.0310833 | val_loss: 0.0311606 | Time: 1834.03 ms [2020-11-25 01:54:36 main:581] : INFO : Epoch 26 | loss: 0.0310846 | val_loss: 0.0311663 | Time: 1842.96 ms [2020-11-25 01:54:38 main:581] : INFO : Epoch 27 | loss: 0.0310868 | val_loss: 0.0311744 | Time: 1721.79 ms [2020-11-25 01:54:40 main:581] : INFO : Epoch 28 | loss: 0.0310869 | val_loss: 0.0311671 | Time: 2046.62 ms [2020-11-25 01:54:42 main:581] : INFO : Epoch 29 | loss: 0.0310813 | val_loss: 0.0311712 | Time: 1874.19 ms [2020-11-25 01:54:44 main:581] : INFO : Epoch 30 | loss: 0.0310811 | val_loss: 0.031167 | Time: 1936.85 ms [2020-11-25 01:54:46 main:581] : INFO : Epoch 31 | loss: 0.0310797 | val_loss: 0.0311747 | Time: 1905.82 ms [2020-11-25 01:54:47 main:581] : INFO : Epoch 32 | loss: 0.0310805 | val_loss: 0.0311692 | Time: 1786.25 ms [2020-11-25 01:54:49 main:581] : INFO : Epoch 33 | loss: 0.0310815 | val_loss: 0.031177 | Time: 1940.14 ms [2020-11-25 01:54:51 main:581] : INFO : Epoch 34 | loss: 0.0310979 | val_loss: 0.031157 | Time: 1935.74 ms [2020-11-25 01:54:53 main:581] : INFO : Epoch 35 | loss: 0.0310925 | val_loss: 0.0311777 | Time: 2031.42 ms [2020-11-25 01:54:55 main:581] : INFO : Epoch 36 | loss: 0.031086 | val_loss: 0.0311766 | Time: 1975.78 ms [2020-11-25 01:54:57 main:581] : INFO : Epoch 37 | loss: 0.0310854 | val_loss: 0.0311724 | Time: 2028.4 ms [2020-11-25 01:54:59 main:581] : INFO : Epoch 38 | loss: 0.0310815 | val_loss: 0.0311741 | Time: 2026.82 ms [2020-11-25 01:55:01 main:581] : INFO : Epoch 39 | loss: 0.0310835 | val_loss: 0.0311751 | Time: 2017.78 ms [2020-11-25 01:55:03 main:581] : INFO : Epoch 40 | loss: 0.0310828 | val_loss: 0.0311725 | Time: 1678.36 ms [2020-11-25 01:55:05 main:581] : INFO : Epoch 41 | loss: 0.0310783 | val_loss: 0.0311723 | Time: 1710.99 ms [2020-11-25 01:55:06 main:581] : INFO : Epoch 42 | loss: 0.0310744 | val_loss: 0.0311688 | Time: 1699.54 ms [2020-11-25 01:55:08 main:581] : INFO : Epoch 43 | loss: 0.0310727 | val_loss: 0.031173 | Time: 1707.8 ms [2020-11-25 01:55:10 main:581] : INFO : Epoch 44 | loss: 0.0310732 | val_loss: 0.0311807 | Time: 1989.58 ms [2020-11-25 01:55:12 main:581] : INFO : Epoch 45 | loss: 0.0310712 | val_loss: 0.031178 | Time: 1990.37 ms [2020-11-25 01:55:14 main:581] : INFO : Epoch 46 | loss: 0.0310751 | val_loss: 0.0311784 | Time: 2001.42 ms [2020-11-25 01:55:16 main:581] : INFO : Epoch 47 | loss: 0.0310775 | val_loss: 0.0311798 | Time: 2047.55 ms [2020-11-25 01:55:18 main:581] : INFO : Epoch 48 | loss: 0.0310759 | val_loss: 0.0311703 | Time: 1760.06 ms [2020-11-25 01:55:20 main:581] : INFO : Epoch 49 | loss: 0.0310733 | val_loss: 0.0311749 | Time: 1909.57 ms [2020-11-25 01:55:22 main:581] : INFO : Epoch 50 | loss: 0.0310767 | val_loss: 0.0311733 | Time: 2044.12 ms [2020-11-25 01:55:24 main:581] : INFO : Epoch 51 | loss: 0.0310731 | val_loss: 0.0311714 | Time: 2012.08 ms [2020-11-25 01:55:26 main:581] : INFO : Epoch 52 | loss: 0.031075 | val_loss: 0.0311747 | Time: 2019.09 ms [2020-11-25 01:55:28 main:581] : INFO : Epoch 53 | loss: 0.031072 | val_loss: 0.0311747 | Time: 1985.92 ms [2020-11-25 01:55:30 main:581] : INFO : Epoch 54 | loss: 0.0310709 | val_loss: 0.031178 | Time: 2030.32 ms [2020-11-25 01:55:32 main:581] : INFO : Epoch 55 | loss: 0.0310745 | val_loss: 0.0311808 | Time: 2058.8 ms [2020-11-25 01:55:34 main:581] : INFO : Epoch 56 | loss: 0.0310765 | val_loss: 0.0311745 | Time: 1907.13 ms [2020-11-25 01:55:36 main:581] : INFO : Epoch 57 | loss: 0.0310764 | val_loss: 0.0311769 | Time: 2040.04 ms [2020-11-25 01:55:38 main:581] : INFO : Epoch 58 | loss: 0.0310903 | val_loss: 0.0311704 | Time: 2027.41 ms [2020-11-25 01:55:40 main:581] : INFO : Epoch 59 | loss: 0.0310819 | val_loss: 0.03117 | Time: 1701.8 ms [2020-11-25 01:55:41 main:581] : INFO : Epoch 60 | loss: 0.0310767 | val_loss: 0.0311751 | Time: 1837.59 ms [2020-11-25 01:55:43 main:581] : INFO : Epoch 61 | loss: 0.0310765 | val_loss: 0.031174 | Time: 1986.34 ms [2020-11-25 01:55:45 main:581] : INFO : Epoch 62 | loss: 0.0310769 | val_loss: 0.0311703 | Time: 1768.65 ms [2020-11-25 01:55:47 main:581] : INFO : Epoch 63 | loss: 0.0310725 | val_loss: 0.0311783 | Time: 1927.03 ms [2020-11-25 01:55:49 main:581] : INFO : Epoch 64 | loss: 0.0310729 | val_loss: 0.0311809 | Time: 1826.78 ms [2020-11-25 01:55:51 main:581] : INFO : Epoch 65 | loss: 0.0310713 | val_loss: 0.0311877 | Time: 1685.97 ms [2020-11-25 01:55:52 main:581] : INFO : Epoch 66 | loss: 0.0310687 | val_loss: 0.0311849 | Time: 1775.41 ms [2020-11-25 01:55:54 main:581] : INFO : Epoch 67 | loss: 0.031073 | val_loss: 0.0312005 | Time: 2023.94 ms [2020-11-25 01:55:57 main:581] : INFO : Epoch 68 | loss: 0.031074 | val_loss: 0.0311774 | Time: 2018.81 ms [2020-11-25 01:55:58 main:581] : INFO : Epoch 69 | loss: 0.0310697 | val_loss: 0.0311813 | Time: 1714.4 ms [2020-11-25 01:56:00 main:581] : INFO : Epoch 70 | loss: 0.0310683 | val_loss: 0.0311694 | Time: 1998.78 ms [2020-11-25 01:56:02 main:581] : INFO : Epoch 71 | loss: 0.0310735 | val_loss: 0.0311874 | Time: 1907.61 ms [2020-11-25 01:56:04 main:581] : INFO : Epoch 72 | loss: 0.031082 | val_loss: 0.031175 | Time: 2022.44 ms [2020-11-25 01:56:06 main:581] : INFO : Epoch 73 | loss: 0.0310828 | val_loss: 0.0311812 | Time: 1799.75 ms [2020-11-25 01:56:08 main:581] : INFO : Epoch 74 | loss: 0.0310829 | val_loss: 0.0311794 | Time: 1946.03 ms [2020-11-25 01:56:10 main:581] : INFO : Epoch 75 | loss: 0.0310796 | val_loss: 0.0311797 | Time: 1795.23 ms [2020-11-25 01:56:12 main:581] : INFO : Epoch 76 | loss: 0.0310747 | val_loss: 0.0311734 | Time: 1841.91 ms [2020-11-25 01:56:13 main:581] : INFO : Epoch 77 | loss: 0.0310791 | val_loss: 0.0311754 | Time: 1940.32 ms [2020-11-25 01:56:15 main:581] : INFO : Epoch 78 | loss: 0.0310767 | val_loss: 0.0311732 | Time: 1948.47 ms [2020-11-25 01:56:17 main:581] : INFO : Epoch 79 | loss: 0.0310776 | val_loss: 0.0311814 | Time: 1851.01 ms [2020-11-25 01:56:19 main:581] : INFO : Epoch 80 | loss: 0.0310816 | val_loss: 0.0311642 | Time: 1920.51 ms [2020-11-25 01:56:21 main:581] : INFO : Epoch 81 | loss: 0.031083 | val_loss: 0.0311728 | Time: 1992 ms [2020-11-25 01:56:23 main:581] : INFO : Epoch 82 | loss: 0.0310758 | val_loss: 0.0311723 | Time: 1889.48 ms [2020-11-25 01:56:25 main:581] : INFO : Epoch 83 | loss: 0.0310703 | val_loss: 0.0311761 | Time: 1859.42 ms [2020-11-25 01:56:27 main:581] : INFO : Epoch 84 | loss: 0.0310724 | val_loss: 0.0311741 | Time: 1729.66 ms [2020-11-25 01:56:29 main:581] : INFO : Epoch 85 | loss: 0.0310752 | val_loss: 0.0311744 | Time: 1980.26 ms [2020-11-25 01:56:31 main:581] : INFO : Epoch 86 | loss: 0.0310737 | val_loss: 0.0311762 | Time: 2022.8 ms [2020-11-25 01:56:33 main:581] : INFO : Epoch 87 | loss: 0.0310717 | val_loss: 0.031173 | Time: 1913.33 ms [2020-11-25 01:56:35 main:581] : INFO : Epoch 88 | loss: 0.0310724 | val_loss: 0.0311761 | Time: 1992.69 ms [2020-11-25 01:56:37 main:581] : INFO : Epoch 89 | loss: 0.0310718 | val_loss: 0.0311779 | Time: 1936.93 ms [2020-11-25 01:56:39 main:581] : INFO : Epoch 90 | loss: 0.0310754 | val_loss: 0.0311748 | Time: 2037.82 ms [2020-11-25 01:56:40 main:581] : INFO : Epoch 91 | loss: 0.031075 | val_loss: 0.0311767 | Time: 1893.07 ms [2020-11-25 01:56:42 main:581] : INFO : Epoch 92 | loss: 0.0310716 | val_loss: 0.0311743 | Time: 1925.39 ms [2020-11-25 01:56:44 main:581] : INFO : Epoch 93 | loss: 0.0310763 | val_loss: 0.0311865 | Time: 1692.08 ms [2020-11-25 01:56:46 main:581] : INFO : Epoch 94 | loss: 0.0310872 | val_loss: 0.0311631 | Time: 1820.03 ms [2020-11-25 01:56:48 main:581] : INFO : Epoch 95 | loss: 0.0310891 | val_loss: 0.0311811 | Time: 1778.54 ms [2020-11-25 01:56:50 main:581] : INFO : Epoch 96 | loss: 0.0310786 | val_loss: 0.0311778 | Time: 1882.32 ms [2020-11-25 01:56:52 main:581] : INFO : Epoch 97 | loss: 0.0310741 | val_loss: 0.0311743 | Time: 1955.07 ms [2020-11-25 01:56:53 main:581] : INFO : Epoch 98 | loss: 0.0310746 | val_loss: 0.0311741 | Time: 1862.57 ms [2020-11-25 01:56:55 main:581] : INFO : Epoch 99 | loss: 0.0310742 | val_loss: 0.0311683 | Time: 1778.36 ms [2020-11-25 01:56:57 main:581] : INFO : Epoch 100 | loss: 0.0310717 | val_loss: 0.0311771 | Time: 2071.65 ms [2020-11-25 01:56:59 main:581] : INFO : Epoch 101 | loss: 0.0310789 | val_loss: 0.0311695 | Time: 1843.58 ms [2020-11-25 01:57:01 main:581] : INFO : Epoch 102 | loss: 0.0310817 | val_loss: 0.0311794 | Time: 1812.37 ms [2020-11-25 01:57:03 main:581] : INFO : Epoch 103 | loss: 0.0310776 | val_loss: 0.031165 | Time: 1918.02 ms [2020-11-25 01:57:05 main:581] : INFO : Epoch 104 | loss: 0.0310704 | val_loss: 0.0311765 | Time: 2042.84 ms [2020-11-25 01:57:07 main:581] : INFO : Epoch 105 | loss: 0.0310686 | val_loss: 0.0311768 | Time: 1822.13 ms [2020-11-25 01:57:09 main:581] : INFO : Epoch 106 | loss: 0.0310836 | val_loss: 0.0311796 | Time: 1961.23 ms [2020-11-25 01:57:11 main:581] : INFO : Epoch 107 | loss: 0.031095 | val_loss: 0.0311617 | Time: 2001.23 ms [2020-11-25 01:57:12 main:581] : INFO : Epoch 108 | loss: 0.0310906 | val_loss: 0.0311671 | Time: 1853.7 ms [2020-11-25 01:57:14 main:581] : INFO : Epoch 109 | loss: 0.0310823 | val_loss: 0.0311664 | Time: 1963.3 ms [2020-11-25 01:57:16 main:581] : INFO : Epoch 110 | loss: 0.031078 | val_loss: 0.0311728 | Time: 2021.77 ms [2020-11-25 01:57:18 main:581] : INFO : Epoch 111 | loss: 0.0310784 | val_loss: 0.0311751 | Time: 2005.97 ms [2020-11-25 01:57:20 main:581] : INFO : Epoch 112 | loss: 0.0310786 | val_loss: 0.0311756 | Time: 1789.78 ms [2020-11-25 01:57:22 main:581] : INFO : Epoch 113 | loss: 0.0310863 | val_loss: 0.0311672 | Time: 1796.18 ms [2020-11-25 01:57:24 main:581] : INFO : Epoch 114 | loss: 0.0310892 | val_loss: 0.0311683 | Time: 1880.39 ms [2020-11-25 01:57:26 main:581] : INFO : Epoch 115 | loss: 0.0310802 | val_loss: 0.0311744 | Time: 1951.36 ms [2020-11-25 01:57:28 main:581] : INFO : Epoch 116 | loss: 0.0310742 | val_loss: 0.0311774 | Time: 1925.07 ms [2020-11-25 01:57:30 main:581] : INFO : Epoch 117 | loss: 0.0310737 | val_loss: 0.0311678 | Time: 1702.93 ms [2020-11-25 01:57:31 main:581] : INFO : Epoch 118 | loss: 0.0310769 | val_loss: 0.0311718 | Time: 1936.09 ms [2020-11-25 01:57:33 main:581] : INFO : Epoch 119 | loss: 0.0310746 | val_loss: 0.0311832 | Time: 1839.58 ms [2020-11-25 01:57:35 main:581] : INFO : Epoch 120 | loss: 0.0310863 | val_loss: 0.0311862 | Time: 1886.32 ms [2020-11-25 01:57:37 main:581] : INFO : Epoch 121 | loss: 0.0310833 | val_loss: 0.0311954 | Time: 1929.07 ms [2020-11-25 01:57:39 main:581] : INFO : Epoch 122 | loss: 0.0310836 | val_loss: 0.0312046 | Time: 1923.47 ms [2020-11-25 01:57:41 main:581] : INFO : Epoch 123 | loss: 0.0312168 | val_loss: 0.0312334 | Time: 1839.66 ms [2020-11-25 01:57:43 main:581] : INFO : Epoch 124 | loss: 0.0322215 | val_loss: 0.0316143 | Time: 1653.29 ms [2020-11-25 01:57:44 main:581] : INFO : Epoch 125 | loss: 0.0313562 | val_loss: 0.031208 | Time: 1890.85 ms [2020-11-25 01:57:46 main:581] : INFO : Epoch 126 | loss: 0.0311507 | val_loss: 0.0311778 | Time: 1805.39 ms [2020-11-25 01:57:48 main:581] : INFO : Epoch 127 | loss: 0.0311115 | val_loss: 0.0311658 | Time: 1988.31 ms [2020-11-25 01:57:50 main:581] : INFO : Epoch 128 | loss: 0.0310939 | val_loss: 0.0311692 | Time: 1805.02 ms [2020-11-25 01:57:50 main:604] : INFO : Saving trained model to model-final.pt, val_loss 0.0311692 [2020-11-25 01:57:50 main:610] : INFO : Saving end state to config to file [2020-11-25 01:57:50 main:615] : INFO : Success, exiting.. 01:57:50 (10183): 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)