Task 3056504
| Name | ParityModified-1606097356-5999-15_0 |
| Workunit | 1388017 |
| Created | 25 Nov 2020, 5:44:15 UTC |
| Sent | 25 Nov 2020, 5:57:34 UTC |
| Report deadline | 2 Dec 2020, 5:57:34 UTC |
| Received | 25 Nov 2020, 6:02:22 UTC |
| Server state | Over |
| Outcome | Success |
| Client state | Done |
| Exit status | 0 (0x00000000) |
| Computer ID | 4754 |
| Run time | 4 min 23 sec |
| CPU time | 4 min 20 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 | 10.43 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 00:57:52 main:442] : INFO : Set logging level to 1 [2020-11-25 00:57:52 main:448] : INFO : Running in BOINC Client mode [2020-11-25 00:57:52 main:451] : INFO : Resolving all filenames [2020-11-25 00:57:52 main:459] : INFO : Resolved: dataset.hdf5 => ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 (exists = 1) [2020-11-25 00:57:52 main:459] : INFO : Resolved: model.cfg => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-15_0_r1658768653_1 (exists = 0) [2020-11-25 00:57:52 main:459] : INFO : Resolved: model-final.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-15_0_r1658768653_0 (exists = 0) [2020-11-25 00:57:52 main:459] : INFO : Resolved: model-input.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-15 (exists = 1) [2020-11-25 00:57:52 main:459] : INFO : Resolved: snapshot.pt => snapshot.pt (exists = 0) [2020-11-25 00:57:52 main:479] : INFO : Dataset filename: ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 [2020-11-25 00:57:52 main:481] : INFO : Configuration: [2020-11-25 00:57:52 main:482] : INFO : Model type: GRU [2020-11-25 00:57:52 main:483] : INFO : Validation Loss Threshold: 0.0001 [2020-11-25 00:57:52 main:484] : INFO : Max Epochs: 128 [2020-11-25 00:57:52 main:485] : INFO : Batch Size: 128 [2020-11-25 00:57:52 main:486] : INFO : Learning Rate: 0.01 [2020-11-25 00:57:52 main:487] : INFO : Patience: 10 [2020-11-25 00:57:52 main:488] : INFO : Hidden Width: 12 [2020-11-25 00:57:52 main:489] : INFO : # Recurrent Layers: 4 [2020-11-25 00:57:52 main:490] : INFO : # Backend Layers: 4 [2020-11-25 00:57:52 main:491] : INFO : # Threads: 1 [2020-11-25 00:57:52 main:493] : INFO : Preparing Dataset [2020-11-25 00:57:52 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 00:57:52 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 00:57:55 load:106] : INFO : Successfully loaded dataset of 2048 examples into memory. [2020-11-25 00:57:55 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 00:57:55 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 00:57:55 load:106] : INFO : Successfully loaded dataset of 512 examples into memory. [2020-11-25 00:57:55 main:501] : INFO : Creating Model [2020-11-25 00:57:55 main:514] : INFO : Preparing config file [2020-11-25 00:57:55 main:526] : INFO : Creating new config file [2020-11-25 00:57:55 main:545] : INFO : This is a continuation WU, loading previous network [2020-11-25 00:57:55 main:566] : INFO : Loading DataLoader into Memory [2020-11-25 00:57:55 main:569] : INFO : Starting Training [2020-11-25 00:57:58 main:581] : INFO : Epoch 1 | loss: 0.0311687 | val_loss: 0.0311799 | Time: 2761.92 ms [2020-11-25 00:58:00 main:581] : INFO : Epoch 2 | loss: 0.0311244 | val_loss: 0.0311577 | Time: 2000.47 ms [2020-11-25 00:58:02 main:581] : INFO : Epoch 3 | loss: 0.0311157 | val_loss: 0.0311603 | Time: 1983.6 ms [2020-11-25 00:58:04 main:581] : INFO : Epoch 4 | loss: 0.0311105 | val_loss: 0.0311594 | Time: 2015.27 ms [2020-11-25 00:58:06 main:581] : INFO : Epoch 5 | loss: 0.0311073 | val_loss: 0.0311617 | Time: 2008.65 ms [2020-11-25 00:58:08 main:581] : INFO : Epoch 6 | loss: 0.0311071 | val_loss: 0.031162 | Time: 2049.14 ms [2020-11-25 00:58:10 main:581] : INFO : Epoch 7 | loss: 0.031109 | val_loss: 0.0311619 | Time: 1977.68 ms [2020-11-25 00:58:12 main:581] : INFO : Epoch 8 | loss: 0.0311115 | val_loss: 0.0311639 | Time: 2006.27 ms [2020-11-25 00:58:14 main:581] : INFO : Epoch 9 | loss: 0.0311101 | val_loss: 0.0311583 | Time: 2045.02 ms [2020-11-25 00:58:16 main:581] : INFO : Epoch 10 | loss: 0.0311091 | val_loss: 0.031163 | Time: 2090.64 ms [2020-11-25 00:58:18 main:581] : INFO : Epoch 11 | loss: 0.0311056 | val_loss: 0.0311591 | Time: 2023.15 ms [2020-11-25 00:58:20 main:581] : INFO : Epoch 12 | loss: 0.031105 | val_loss: 0.0311622 | Time: 1994.9 ms [2020-11-25 00:58:22 main:581] : INFO : Epoch 13 | loss: 0.0311048 | val_loss: 0.0311625 | Time: 2019.12 ms [2020-11-25 00:58:24 main:581] : INFO : Epoch 14 | loss: 0.0311043 | val_loss: 0.031159 | Time: 2049.8 ms [2020-11-25 00:58:26 main:581] : INFO : Epoch 15 | loss: 0.0311031 | val_loss: 0.031164 | Time: 2027.81 ms [2020-11-25 00:58:28 main:581] : INFO : Epoch 16 | loss: 0.0311033 | val_loss: 0.0311632 | Time: 2047.45 ms [2020-11-25 00:58:30 main:581] : INFO : Epoch 17 | loss: 0.031106 | val_loss: 0.0311608 | Time: 1985.71 ms [2020-11-25 00:58:32 main:581] : INFO : Epoch 18 | loss: 0.0311061 | val_loss: 0.0311597 | Time: 2060.17 ms [2020-11-25 00:58:34 main:581] : INFO : Epoch 19 | loss: 0.0311075 | val_loss: 0.0311619 | Time: 2010.73 ms [2020-11-25 00:58:36 main:581] : INFO : Epoch 20 | loss: 0.0311109 | val_loss: 0.0311594 | Time: 2017.36 ms [2020-11-25 00:58:39 main:581] : INFO : Epoch 21 | loss: 0.0311105 | val_loss: 0.0311584 | Time: 2088.81 ms [2020-11-25 00:58:41 main:581] : INFO : Epoch 22 | loss: 0.0311071 | val_loss: 0.0311644 | Time: 2020.59 ms [2020-11-25 00:58:43 main:581] : INFO : Epoch 23 | loss: 0.0311081 | val_loss: 0.0311669 | Time: 2045.22 ms [2020-11-25 00:58:45 main:581] : INFO : Epoch 24 | loss: 0.0311087 | val_loss: 0.0311711 | Time: 1992.35 ms [2020-11-25 00:58:47 main:581] : INFO : Epoch 25 | loss: 0.0311081 | val_loss: 0.0311622 | Time: 2005.2 ms [2020-11-25 00:58:49 main:581] : INFO : Epoch 26 | loss: 0.0311065 | val_loss: 0.0311633 | Time: 2005.56 ms [2020-11-25 00:58:51 main:581] : INFO : Epoch 27 | loss: 0.0311044 | val_loss: 0.0311655 | Time: 1955.44 ms [2020-11-25 00:58:53 main:581] : INFO : Epoch 28 | loss: 0.031105 | val_loss: 0.0311704 | Time: 1999.95 ms [2020-11-25 00:58:55 main:581] : INFO : Epoch 29 | loss: 0.0311034 | val_loss: 0.0311783 | Time: 2043.31 ms [2020-11-25 00:58:57 main:581] : INFO : Epoch 30 | loss: 0.0311087 | val_loss: 0.0311665 | Time: 2015.26 ms [2020-11-25 00:58:59 main:581] : INFO : Epoch 31 | loss: 0.031114 | val_loss: 0.03116 | Time: 2019.69 ms [2020-11-25 00:59:01 main:581] : INFO : Epoch 32 | loss: 0.0311088 | val_loss: 0.0311641 | Time: 2007.69 ms [2020-11-25 00:59:03 main:581] : INFO : Epoch 33 | loss: 0.0311037 | val_loss: 0.0311625 | Time: 2008.35 ms [2020-11-25 00:59:05 main:581] : INFO : Epoch 34 | loss: 0.0311033 | val_loss: 0.0311577 | Time: 1984.6 ms [2020-11-25 00:59:07 main:581] : INFO : Epoch 35 | loss: 0.0311041 | val_loss: 0.0311608 | Time: 2009.95 ms [2020-11-25 00:59:09 main:581] : INFO : Epoch 36 | loss: 0.031105 | val_loss: 0.031164 | Time: 2029.46 ms [2020-11-25 00:59:11 main:581] : INFO : Epoch 37 | loss: 0.0311015 | val_loss: 0.0311577 | Time: 1990.06 ms [2020-11-25 00:59:13 main:581] : INFO : Epoch 38 | loss: 0.0311048 | val_loss: 0.0311666 | Time: 2009.71 ms [2020-11-25 00:59:15 main:581] : INFO : Epoch 39 | loss: 0.0311102 | val_loss: 0.0311685 | Time: 2006.24 ms [2020-11-25 00:59:17 main:581] : INFO : Epoch 40 | loss: 0.0311091 | val_loss: 0.03116 | Time: 2013.89 ms [2020-11-25 00:59:19 main:581] : INFO : Epoch 41 | loss: 0.0311048 | val_loss: 0.0311614 | Time: 2021.18 ms [2020-11-25 00:59:21 main:581] : INFO : Epoch 42 | loss: 0.0311007 | val_loss: 0.0311637 | Time: 2049.6 ms [2020-11-25 00:59:23 main:581] : INFO : Epoch 43 | loss: 0.0310989 | val_loss: 0.0311689 | Time: 1981.89 ms [2020-11-25 00:59:25 main:581] : INFO : Epoch 44 | loss: 0.0311001 | val_loss: 0.0311653 | Time: 2007.04 ms [2020-11-25 00:59:27 main:581] : INFO : Epoch 45 | loss: 0.0311001 | val_loss: 0.0311708 | Time: 1988.93 ms [2020-11-25 00:59:29 main:581] : INFO : Epoch 46 | loss: 0.031097 | val_loss: 0.0311678 | Time: 2031.26 ms [2020-11-25 00:59:31 main:581] : INFO : Epoch 47 | loss: 0.0311009 | val_loss: 0.0311645 | Time: 2001.18 ms [2020-11-25 00:59:33 main:581] : INFO : Epoch 48 | loss: 0.0311029 | val_loss: 0.0311664 | Time: 2025.13 ms [2020-11-25 00:59:35 main:581] : INFO : Epoch 49 | loss: 0.0311176 | val_loss: 0.0311674 | Time: 2040.32 ms [2020-11-25 00:59:37 main:581] : INFO : Epoch 50 | loss: 0.0311151 | val_loss: 0.0311669 | Time: 2005.63 ms [2020-11-25 00:59:39 main:581] : INFO : Epoch 51 | loss: 0.0311037 | val_loss: 0.0311661 | Time: 2013.18 ms [2020-11-25 00:59:41 main:581] : INFO : Epoch 52 | loss: 0.0310977 | val_loss: 0.0311653 | Time: 2015.4 ms [2020-11-25 00:59:43 main:581] : INFO : Epoch 53 | loss: 0.0310974 | val_loss: 0.0311698 | Time: 1966.25 ms [2020-11-25 00:59:45 main:581] : INFO : Epoch 54 | loss: 0.0310967 | val_loss: 0.0311727 | Time: 1990.37 ms [2020-11-25 00:59:47 main:581] : INFO : Epoch 55 | loss: 0.0310979 | val_loss: 0.0311683 | Time: 1990.7 ms [2020-11-25 00:59:49 main:581] : INFO : Epoch 56 | loss: 0.0310971 | val_loss: 0.0311712 | Time: 1996.27 ms [2020-11-25 00:59:51 main:581] : INFO : Epoch 57 | loss: 0.0310961 | val_loss: 0.0311631 | Time: 1990.84 ms [2020-11-25 00:59:53 main:581] : INFO : Epoch 58 | loss: 0.031102 | val_loss: 0.0311639 | Time: 2062.08 ms [2020-11-25 00:59:55 main:581] : INFO : Epoch 59 | loss: 0.0310974 | val_loss: 0.0311606 | Time: 2027.27 ms [2020-11-25 00:59:57 main:581] : INFO : Epoch 60 | loss: 0.0311109 | val_loss: 0.0311675 | Time: 1974.49 ms [2020-11-25 00:59:59 main:581] : INFO : Epoch 61 | loss: 0.0311068 | val_loss: 0.0311673 | Time: 1978.02 ms [2020-11-25 01:00:01 main:581] : INFO : Epoch 62 | loss: 0.0311003 | val_loss: 0.0311719 | Time: 2011.8 ms [2020-11-25 01:00:03 main:581] : INFO : Epoch 63 | loss: 0.0310969 | val_loss: 0.0311636 | Time: 2009.78 ms [2020-11-25 01:00:05 main:581] : INFO : Epoch 64 | loss: 0.0310944 | val_loss: 0.0311767 | Time: 2032.41 ms [2020-11-25 01:00:07 main:581] : INFO : Epoch 65 | loss: 0.0310991 | val_loss: 0.0311702 | Time: 1990.03 ms [2020-11-25 01:00:09 main:581] : INFO : Epoch 66 | loss: 0.0311047 | val_loss: 0.0311691 | Time: 2046.04 ms [2020-11-25 01:00:11 main:581] : INFO : Epoch 67 | loss: 0.0310986 | val_loss: 0.0311711 | Time: 1951.3 ms [2020-11-25 01:00:13 main:581] : INFO : Epoch 68 | loss: 0.0311023 | val_loss: 0.031162 | Time: 2007.99 ms [2020-11-25 01:00:15 main:581] : INFO : Epoch 69 | loss: 0.0311011 | val_loss: 0.0311677 | Time: 1973.28 ms [2020-11-25 01:00:17 main:581] : INFO : Epoch 70 | loss: 0.0310957 | val_loss: 0.0311641 | Time: 2001.71 ms [2020-11-25 01:00:19 main:581] : INFO : Epoch 71 | loss: 0.0310957 | val_loss: 0.0311686 | Time: 2006.3 ms [2020-11-25 01:00:21 main:581] : INFO : Epoch 72 | loss: 0.0311013 | val_loss: 0.0311619 | Time: 1992.65 ms [2020-11-25 01:00:23 main:581] : INFO : Epoch 73 | loss: 0.0310989 | val_loss: 0.0311688 | Time: 2024.7 ms [2020-11-25 01:00:25 main:581] : INFO : Epoch 74 | loss: 0.0310958 | val_loss: 0.0311664 | Time: 1988.54 ms [2020-11-25 01:00:27 main:581] : INFO : Epoch 75 | loss: 0.0310946 | val_loss: 0.0311694 | Time: 2000.57 ms [2020-11-25 01:00:29 main:581] : INFO : Epoch 76 | loss: 0.0310954 | val_loss: 0.0311705 | Time: 1973.66 ms [2020-11-25 01:00:31 main:581] : INFO : Epoch 77 | loss: 0.0310942 | val_loss: 0.0311725 | Time: 1988.25 ms [2020-11-25 01:00:33 main:581] : INFO : Epoch 78 | loss: 0.0310935 | val_loss: 0.0311623 | Time: 1952.17 ms [2020-11-25 01:00:35 main:581] : INFO : Epoch 79 | loss: 0.0310915 | val_loss: 0.0311678 | Time: 2021.71 ms [2020-11-25 01:00:37 main:581] : INFO : Epoch 80 | loss: 0.031098 | val_loss: 0.0311696 | Time: 2003.57 ms [2020-11-25 01:00:39 main:581] : INFO : Epoch 81 | loss: 0.0310918 | val_loss: 0.0311636 | Time: 2023.14 ms [2020-11-25 01:00:41 main:581] : INFO : Epoch 82 | loss: 0.0310921 | val_loss: 0.0311625 | Time: 1960.42 ms [2020-11-25 01:00:43 main:581] : INFO : Epoch 83 | loss: 0.0310906 | val_loss: 0.0311707 | Time: 1971.09 ms [2020-11-25 01:00:45 main:581] : INFO : Epoch 84 | loss: 0.0310919 | val_loss: 0.0311729 | Time: 2015.43 ms [2020-11-25 01:00:47 main:581] : INFO : Epoch 85 | loss: 0.0310986 | val_loss: 0.0311631 | Time: 1956.07 ms [2020-11-25 01:00:49 main:581] : INFO : Epoch 86 | loss: 0.031101 | val_loss: 0.031169 | Time: 1996.29 ms [2020-11-25 01:00:51 main:581] : INFO : Epoch 87 | loss: 0.0311025 | val_loss: 0.0311597 | Time: 2026.17 ms [2020-11-25 01:00:53 main:581] : INFO : Epoch 88 | loss: 0.0310973 | val_loss: 0.0311605 | Time: 2006.99 ms [2020-11-25 01:00:55 main:581] : INFO : Epoch 89 | loss: 0.0310898 | val_loss: 0.0311644 | Time: 2039.41 ms [2020-11-25 01:00:57 main:581] : INFO : Epoch 90 | loss: 0.0310921 | val_loss: 0.031164 | Time: 1994.2 ms [2020-11-25 01:00:59 main:581] : INFO : Epoch 91 | loss: 0.0310971 | val_loss: 0.0311811 | Time: 2062.16 ms [2020-11-25 01:01:01 main:581] : INFO : Epoch 92 | loss: 0.031098 | val_loss: 0.0311605 | Time: 2043.14 ms [2020-11-25 01:01:03 main:581] : INFO : Epoch 93 | loss: 0.0310907 | val_loss: 0.0311735 | Time: 2022.95 ms [2020-11-25 01:01:05 main:581] : INFO : Epoch 94 | loss: 0.0310938 | val_loss: 0.0311673 | Time: 1996.55 ms [2020-11-25 01:01:07 main:581] : INFO : Epoch 95 | loss: 0.0311224 | val_loss: 0.0311571 | Time: 2015.1 ms [2020-11-25 01:01:09 main:581] : INFO : Epoch 96 | loss: 0.0311196 | val_loss: 0.031161 | Time: 2008.46 ms [2020-11-25 01:01:11 main:581] : INFO : Epoch 97 | loss: 0.0311127 | val_loss: 0.0311593 | Time: 2006.29 ms [2020-11-25 01:01:13 main:581] : INFO : Epoch 98 | loss: 0.0311062 | val_loss: 0.0311623 | Time: 2050.21 ms [2020-11-25 01:01:15 main:581] : INFO : Epoch 99 | loss: 0.0311097 | val_loss: 0.0311651 | Time: 2057.6 ms [2020-11-25 01:01:17 main:581] : INFO : Epoch 100 | loss: 0.031116 | val_loss: 0.0311585 | Time: 2024.28 ms [2020-11-25 01:01:19 main:581] : INFO : Epoch 101 | loss: 0.0311115 | val_loss: 0.0311594 | Time: 2028.3 ms [2020-11-25 01:01:21 main:581] : INFO : Epoch 102 | loss: 0.0311044 | val_loss: 0.0311604 | Time: 2005.85 ms [2020-11-25 01:01:23 main:581] : INFO : Epoch 103 | loss: 0.0311003 | val_loss: 0.0311611 | Time: 2092.05 ms [2020-11-25 01:01:25 main:581] : INFO : Epoch 104 | loss: 0.0310978 | val_loss: 0.0311629 | Time: 2021.83 ms [2020-11-25 01:01:27 main:581] : INFO : Epoch 105 | loss: 0.0310971 | val_loss: 0.0311673 | Time: 2057.17 ms [2020-11-25 01:01:29 main:581] : INFO : Epoch 106 | loss: 0.0311005 | val_loss: 0.0311638 | Time: 1891.89 ms [2020-11-25 01:01:31 main:581] : INFO : Epoch 107 | loss: 0.0311142 | val_loss: 0.0311613 | Time: 1875.03 ms [2020-11-25 01:01:33 main:581] : INFO : Epoch 108 | loss: 0.0311087 | val_loss: 0.0311648 | Time: 1954.28 ms [2020-11-25 01:01:35 main:581] : INFO : Epoch 109 | loss: 0.0311117 | val_loss: 0.0311518 | Time: 2037.88 ms [2020-11-25 01:01:37 main:581] : INFO : Epoch 110 | loss: 0.0311138 | val_loss: 0.0311616 | Time: 1955.88 ms [2020-11-25 01:01:39 main:581] : INFO : Epoch 111 | loss: 0.0311082 | val_loss: 0.0311564 | Time: 1922.25 ms [2020-11-25 01:01:41 main:581] : INFO : Epoch 112 | loss: 0.0311028 | val_loss: 0.0311663 | Time: 1781.55 ms [2020-11-25 01:01:43 main:581] : INFO : Epoch 113 | loss: 0.0310996 | val_loss: 0.03116 | Time: 2040.94 ms [2020-11-25 01:01:45 main:581] : INFO : Epoch 114 | loss: 0.0310955 | val_loss: 0.0311661 | Time: 2103.04 ms [2020-11-25 01:01:47 main:581] : INFO : Epoch 115 | loss: 0.0310982 | val_loss: 0.0311607 | Time: 2036.83 ms [2020-11-25 01:01:49 main:581] : INFO : Epoch 116 | loss: 0.0310973 | val_loss: 0.0311658 | Time: 1994.74 ms [2020-11-25 01:01:51 main:581] : INFO : Epoch 117 | loss: 0.0310942 | val_loss: 0.031168 | Time: 2064.37 ms [2020-11-25 01:01:53 main:581] : INFO : Epoch 118 | loss: 0.0310906 | val_loss: 0.0311631 | Time: 2029.24 ms [2020-11-25 01:01:55 main:581] : INFO : Epoch 119 | loss: 0.0310942 | val_loss: 0.0311725 | Time: 2052.92 ms [2020-11-25 01:01:57 main:581] : INFO : Epoch 120 | loss: 0.0310936 | val_loss: 0.0311597 | Time: 1989.31 ms [2020-11-25 01:01:59 main:581] : INFO : Epoch 121 | loss: 0.0310875 | val_loss: 0.031165 | Time: 1972.19 ms [2020-11-25 01:02:01 main:581] : INFO : Epoch 122 | loss: 0.0310866 | val_loss: 0.0311612 | Time: 2051.14 ms [2020-11-25 01:02:03 main:581] : INFO : Epoch 123 | loss: 0.0310915 | val_loss: 0.0311643 | Time: 2043.96 ms [2020-11-25 01:02:05 main:581] : INFO : Epoch 124 | loss: 0.0310909 | val_loss: 0.0311652 | Time: 1996.79 ms [2020-11-25 01:02:07 main:581] : INFO : Epoch 125 | loss: 0.0311125 | val_loss: 0.0311662 | Time: 2029.65 ms [2020-11-25 01:02:09 main:581] : INFO : Epoch 126 | loss: 0.0311216 | val_loss: 0.0311608 | Time: 2041.51 ms [2020-11-25 01:02:11 main:581] : INFO : Epoch 127 | loss: 0.0311177 | val_loss: 0.0311609 | Time: 2016.34 ms [2020-11-25 01:02:13 main:581] : INFO : Epoch 128 | loss: 0.0311157 | val_loss: 0.0311628 | Time: 2019.37 ms [2020-11-25 01:02:13 main:604] : INFO : Saving trained model to model-final.pt, val_loss 0.0311628 [2020-11-25 01:02:13 main:610] : INFO : Saving end state to config to file [2020-11-25 01:02:13 main:615] : INFO : Success, exiting.. 01:02:13 (10043): 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)