Task 3053312
| Name | ParityModified-1606097356-5999-9_0 |
| Workunit | 1385392 |
| Created | 24 Nov 2020, 20:38:12 UTC |
| Sent | 24 Nov 2020, 20:43:27 UTC |
| Report deadline | 1 Dec 2020, 20:43:27 UTC |
| Received | 24 Nov 2020, 20:48:23 UTC |
| Server state | Over |
| Outcome | Success |
| Client state | Done |
| Exit status | 0 (0x00000000) |
| Computer ID | 4754 |
| Run time | 4 min 20 sec |
| CPU time | 4 min 13 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 | 10.44 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) [2020-11-24 15:43:56 main:442] : INFO : Set logging level to 1 [2020-11-24 15:43:56 main:448] : INFO : Running in BOINC Client mode [2020-11-24 15:43:56 main:451] : INFO : Resolving all filenames [2020-11-24 15:43:56 main:459] : INFO : Resolved: dataset.hdf5 => ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 (exists = 1) [2020-11-24 15:43:56 main:459] : INFO : Resolved: model.cfg => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-9_0_r1459137733_1 (exists = 0) [2020-11-24 15:43:56 main:459] : INFO : Resolved: model-final.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-9_0_r1459137733_0 (exists = 0) [2020-11-24 15:43:56 main:459] : INFO : Resolved: model-input.pt => ../../projects/www.mlcathome.org_mlcathome/ParityModified-1606097356-5999-9 (exists = 1) [2020-11-24 15:43:56 main:459] : INFO : Resolved: snapshot.pt => snapshot.pt (exists = 0) [2020-11-24 15:43:56 main:479] : INFO : Dataset filename: ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 [2020-11-24 15:43:56 main:481] : INFO : Configuration: [2020-11-24 15:43:56 main:482] : INFO : Model type: GRU [2020-11-24 15:43:56 main:483] : INFO : Validation Loss Threshold: 0.0001 [2020-11-24 15:43:56 main:484] : INFO : Max Epochs: 128 [2020-11-24 15:43:56 main:485] : INFO : Batch Size: 128 [2020-11-24 15:43:56 main:486] : INFO : Learning Rate: 0.01 [2020-11-24 15:43:56 main:487] : INFO : Patience: 10 [2020-11-24 15:43:56 main:488] : INFO : Hidden Width: 12 [2020-11-24 15:43:56 main:489] : INFO : # Recurrent Layers: 4 [2020-11-24 15:43:56 main:490] : INFO : # Backend Layers: 4 [2020-11-24 15:43:56 main:491] : INFO : # Threads: 1 [2020-11-24 15:43:56 main:493] : INFO : Preparing Dataset [2020-11-24 15:43:56 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Xt from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-24 15:43:57 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Yt from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-24 15:43:59 load:106] : INFO : Successfully loaded dataset of 2048 examples into memory. [2020-11-24 15:43:59 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Xv from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-24 15:44:00 load_hdf5_ds_into_tensor:28] : INFO : Loading Dataset /Yv from ../../projects/www.mlcathome.org_mlcathome/ParityModified-train-val-dataset.hdf5 into memory [2020-11-24 15:44:00 load:106] : INFO : Successfully loaded dataset of 512 examples into memory. [2020-11-24 15:44:00 main:501] : INFO : Creating Model [2020-11-24 15:44:00 main:514] : INFO : Preparing config file [2020-11-24 15:44:00 main:526] : INFO : Creating new config file [2020-11-24 15:44:00 main:545] : INFO : This is a continuation WU, loading previous network [2020-11-24 15:44:00 main:566] : INFO : Loading DataLoader into Memory [2020-11-24 15:44:00 main:569] : INFO : Starting Training [2020-11-24 15:44:04 main:581] : INFO : Epoch 1 | loss: 0.0311604 | val_loss: 0.0312171 | Time: 4231.25 ms [2020-11-24 15:44:06 main:581] : INFO : Epoch 2 | loss: 0.031088 | val_loss: 0.031214 | Time: 2049.14 ms [2020-11-24 15:44:08 main:581] : INFO : Epoch 3 | loss: 0.0310785 | val_loss: 0.0312119 | Time: 1943.43 ms [2020-11-24 15:44:10 main:581] : INFO : Epoch 4 | loss: 0.0310758 | val_loss: 0.0312079 | Time: 1940.21 ms [2020-11-24 15:44:12 main:581] : INFO : Epoch 5 | loss: 0.0310781 | val_loss: 0.0312115 | Time: 2027.86 ms [2020-11-24 15:44:14 main:581] : INFO : Epoch 6 | loss: 0.0310799 | val_loss: 0.0312049 | Time: 1997.63 ms [2020-11-24 15:44:16 main:581] : INFO : Epoch 7 | loss: 0.0310739 | val_loss: 0.0312137 | Time: 1884.94 ms [2020-11-24 15:44:18 main:581] : INFO : Epoch 8 | loss: 0.0310734 | val_loss: 0.0312209 | Time: 1861.99 ms [2020-11-24 15:44:20 main:581] : INFO : Epoch 9 | loss: 0.0310689 | val_loss: 0.0312279 | Time: 1832.83 ms [2020-11-24 15:44:22 main:581] : INFO : Epoch 10 | loss: 0.0310714 | val_loss: 0.0312081 | Time: 2164.15 ms [2020-11-24 15:44:24 main:581] : INFO : Epoch 11 | loss: 0.0310687 | val_loss: 0.0312143 | Time: 2134.6 ms [2020-11-24 15:44:26 main:581] : INFO : Epoch 12 | loss: 0.0310712 | val_loss: 0.0312247 | Time: 2036.97 ms [2020-11-24 15:44:28 main:581] : INFO : Epoch 13 | loss: 0.0310694 | val_loss: 0.0312059 | Time: 2160.71 ms [2020-11-24 15:44:30 main:581] : INFO : Epoch 14 | loss: 0.0310745 | val_loss: 0.0312232 | Time: 1895.22 ms [2020-11-24 15:44:32 main:581] : INFO : Epoch 15 | loss: 0.0310649 | val_loss: 0.0312304 | Time: 2014.34 ms [2020-11-24 15:44:34 main:581] : INFO : Epoch 16 | loss: 0.0310684 | val_loss: 0.0312158 | Time: 2018.79 ms [2020-11-24 15:44:36 main:581] : INFO : Epoch 17 | loss: 0.0310625 | val_loss: 0.0312209 | Time: 1920.86 ms [2020-11-24 15:44:38 main:581] : INFO : Epoch 18 | loss: 0.031064 | val_loss: 0.031219 | Time: 1922.05 ms [2020-11-24 15:44:40 main:581] : INFO : Epoch 19 | loss: 0.0310777 | val_loss: 0.0311935 | Time: 1890 ms [2020-11-24 15:44:42 main:581] : INFO : Epoch 20 | loss: 0.0310976 | val_loss: 0.031203 | Time: 1887.77 ms [2020-11-24 15:44:44 main:581] : INFO : Epoch 21 | loss: 0.0310878 | val_loss: 0.0312139 | Time: 1992.72 ms [2020-11-24 15:44:46 main:581] : INFO : Epoch 22 | loss: 0.0310806 | val_loss: 0.0312062 | Time: 2004.05 ms [2020-11-24 15:44:48 main:581] : INFO : Epoch 23 | loss: 0.0310649 | val_loss: 0.0312161 | Time: 1921.99 ms [2020-11-24 15:44:50 main:581] : INFO : Epoch 24 | loss: 0.0310631 | val_loss: 0.031219 | Time: 1993.1 ms [2020-11-24 15:44:52 main:581] : INFO : Epoch 25 | loss: 0.0310657 | val_loss: 0.0312145 | Time: 2067.92 ms [2020-11-24 15:44:54 main:581] : INFO : Epoch 26 | loss: 0.0310802 | val_loss: 0.0311967 | Time: 2041.17 ms [2020-11-24 15:44:56 main:581] : INFO : Epoch 27 | loss: 0.0310869 | val_loss: 0.0311992 | Time: 2098.13 ms [2020-11-24 15:44:58 main:581] : INFO : Epoch 28 | loss: 0.0310776 | val_loss: 0.0312122 | Time: 1992.16 ms [2020-11-24 15:45:00 main:581] : INFO : Epoch 29 | loss: 0.0310707 | val_loss: 0.0312095 | Time: 1972.75 ms [2020-11-24 15:45:02 main:581] : INFO : Epoch 30 | loss: 0.0310681 | val_loss: 0.0312052 | Time: 2017.48 ms [2020-11-24 15:45:04 main:581] : INFO : Epoch 31 | loss: 0.0310664 | val_loss: 0.0312217 | Time: 1917.76 ms [2020-11-24 15:45:06 main:581] : INFO : Epoch 32 | loss: 0.0310624 | val_loss: 0.0312138 | Time: 2108.86 ms [2020-11-24 15:45:08 main:581] : INFO : Epoch 33 | loss: 0.0310608 | val_loss: 0.03122 | Time: 1838.45 ms [2020-11-24 15:45:10 main:581] : INFO : Epoch 34 | loss: 0.0310604 | val_loss: 0.0312348 | Time: 1957.43 ms [2020-11-24 15:45:12 main:581] : INFO : Epoch 35 | loss: 0.0310619 | val_loss: 0.0312148 | Time: 1711.06 ms [2020-11-24 15:45:13 main:581] : INFO : Epoch 36 | loss: 0.0310639 | val_loss: 0.0312127 | Time: 1810.92 ms [2020-11-24 15:45:15 main:581] : INFO : Epoch 37 | loss: 0.031063 | val_loss: 0.0312259 | Time: 1909.05 ms [2020-11-24 15:45:17 main:581] : INFO : Epoch 38 | loss: 0.0310665 | val_loss: 0.0312171 | Time: 1747.68 ms [2020-11-24 15:45:19 main:581] : INFO : Epoch 39 | loss: 0.0310693 | val_loss: 0.0312062 | Time: 1911.74 ms [2020-11-24 15:45:21 main:581] : INFO : Epoch 40 | loss: 0.0310659 | val_loss: 0.0312302 | Time: 1958.68 ms [2020-11-24 15:45:23 main:581] : INFO : Epoch 41 | loss: 0.0310663 | val_loss: 0.0312198 | Time: 2008.5 ms [2020-11-24 15:45:25 main:581] : INFO : Epoch 42 | loss: 0.0310647 | val_loss: 0.0312195 | Time: 2040.52 ms [2020-11-24 15:45:27 main:581] : INFO : Epoch 43 | loss: 0.0310641 | val_loss: 0.0312193 | Time: 1892.19 ms [2020-11-24 15:45:29 main:581] : INFO : Epoch 44 | loss: 0.0310624 | val_loss: 0.0312196 | Time: 1984.7 ms [2020-11-24 15:45:31 main:581] : INFO : Epoch 45 | loss: 0.0310677 | val_loss: 0.0312134 | Time: 1975.65 ms [2020-11-24 15:45:33 main:581] : INFO : Epoch 46 | loss: 0.0310652 | val_loss: 0.031228 | Time: 1923.11 ms [2020-11-24 15:45:35 main:581] : INFO : Epoch 47 | loss: 0.0310661 | val_loss: 0.0312132 | Time: 1932.73 ms [2020-11-24 15:45:37 main:581] : INFO : Epoch 48 | loss: 0.0310762 | val_loss: 0.0312148 | Time: 2023.19 ms [2020-11-24 15:45:39 main:581] : INFO : Epoch 49 | loss: 0.0310713 | val_loss: 0.0312125 | Time: 2000.92 ms [2020-11-24 15:45:41 main:581] : INFO : Epoch 50 | loss: 0.0310762 | val_loss: 0.0312113 | Time: 2089.36 ms [2020-11-24 15:45:43 main:581] : INFO : Epoch 51 | loss: 0.031074 | val_loss: 0.0312107 | Time: 1962.73 ms [2020-11-24 15:45:45 main:581] : INFO : Epoch 52 | loss: 0.0310757 | val_loss: 0.0311954 | Time: 2032.65 ms [2020-11-24 15:45:47 main:581] : INFO : Epoch 53 | loss: 0.0310674 | val_loss: 0.0312357 | Time: 1944.2 ms [2020-11-24 15:45:49 main:581] : INFO : Epoch 54 | loss: 0.0310651 | val_loss: 0.0312249 | Time: 2049.95 ms [2020-11-24 15:45:51 main:581] : INFO : Epoch 55 | loss: 0.0310637 | val_loss: 0.0312148 | Time: 2035.49 ms [2020-11-24 15:45:53 main:581] : INFO : Epoch 56 | loss: 0.0310621 | val_loss: 0.0312233 | Time: 1996.37 ms [2020-11-24 15:45:55 main:581] : INFO : Epoch 57 | loss: 0.0310605 | val_loss: 0.0312435 | Time: 2005.59 ms [2020-11-24 15:45:57 main:581] : INFO : Epoch 58 | loss: 0.0310668 | val_loss: 0.0312225 | Time: 2010.7 ms [2020-11-24 15:45:59 main:581] : INFO : Epoch 59 | loss: 0.0310632 | val_loss: 0.0312258 | Time: 1940.53 ms [2020-11-24 15:46:01 main:581] : INFO : Epoch 60 | loss: 0.0310586 | val_loss: 0.031209 | Time: 1960.88 ms [2020-11-24 15:46:03 main:581] : INFO : Epoch 61 | loss: 0.0310546 | val_loss: 0.0312363 | Time: 2019.92 ms [2020-11-24 15:46:05 main:581] : INFO : Epoch 62 | loss: 0.03108 | val_loss: 0.0312005 | Time: 1978.25 ms [2020-11-24 15:46:07 main:581] : INFO : Epoch 63 | loss: 0.0310935 | val_loss: 0.0311961 | Time: 2010.87 ms [2020-11-24 15:46:09 main:581] : INFO : Epoch 64 | loss: 0.0310836 | val_loss: 0.031204 | Time: 1860.67 ms [2020-11-24 15:46:11 main:581] : INFO : Epoch 65 | loss: 0.0310677 | val_loss: 0.0312076 | Time: 1915.68 ms [2020-11-24 15:46:13 main:581] : INFO : Epoch 66 | loss: 0.0310681 | val_loss: 0.0312192 | Time: 1982.5 ms [2020-11-24 15:46:15 main:581] : INFO : Epoch 67 | loss: 0.0310605 | val_loss: 0.0312211 | Time: 2007.72 ms [2020-11-24 15:46:16 main:581] : INFO : Epoch 68 | loss: 0.0310588 | val_loss: 0.0312249 | Time: 1945.35 ms [2020-11-24 15:46:18 main:581] : INFO : Epoch 69 | loss: 0.0310665 | val_loss: 0.0312194 | Time: 1954.12 ms [2020-11-24 15:46:20 main:581] : INFO : Epoch 70 | loss: 0.0310619 | val_loss: 0.0312088 | Time: 1983.34 ms [2020-11-24 15:46:22 main:581] : INFO : Epoch 71 | loss: 0.0310783 | val_loss: 0.0311931 | Time: 1977.38 ms [2020-11-24 15:46:24 main:581] : INFO : Epoch 72 | loss: 0.0310839 | val_loss: 0.0312247 | Time: 1891.25 ms [2020-11-24 15:46:26 main:581] : INFO : Epoch 73 | loss: 0.0310861 | val_loss: 0.0312142 | Time: 1988.16 ms [2020-11-24 15:46:28 main:581] : INFO : Epoch 74 | loss: 0.0310785 | val_loss: 0.0312099 | Time: 1942.81 ms [2020-11-24 15:46:30 main:581] : INFO : Epoch 75 | loss: 0.0310847 | val_loss: 0.0312111 | Time: 1909.05 ms [2020-11-24 15:46:32 main:581] : INFO : Epoch 76 | loss: 0.0310847 | val_loss: 0.0312252 | Time: 1721.82 ms [2020-11-24 15:46:34 main:581] : INFO : Epoch 77 | loss: 0.0310717 | val_loss: 0.0312126 | Time: 1828.9 ms [2020-11-24 15:46:36 main:581] : INFO : Epoch 78 | loss: 0.0310625 | val_loss: 0.0312248 | Time: 1891.03 ms [2020-11-24 15:46:38 main:581] : INFO : Epoch 79 | loss: 0.0310596 | val_loss: 0.031238 | Time: 1971.15 ms [2020-11-24 15:46:40 main:581] : INFO : Epoch 80 | loss: 0.0310557 | val_loss: 0.0312296 | Time: 2011.88 ms [2020-11-24 15:46:42 main:581] : INFO : Epoch 81 | loss: 0.0310649 | val_loss: 0.0312149 | Time: 2037.01 ms [2020-11-24 15:46:44 main:581] : INFO : Epoch 82 | loss: 0.0310754 | val_loss: 0.0312159 | Time: 1913.65 ms [2020-11-24 15:46:45 main:581] : INFO : Epoch 83 | loss: 0.0310626 | val_loss: 0.0312199 | Time: 1865.55 ms [2020-11-24 15:46:47 main:581] : INFO : Epoch 84 | loss: 0.0310653 | val_loss: 0.0312164 | Time: 1980.69 ms [2020-11-24 15:46:49 main:581] : INFO : Epoch 85 | loss: 0.0310604 | val_loss: 0.0312415 | Time: 1989.72 ms [2020-11-24 15:46:51 main:581] : INFO : Epoch 86 | loss: 0.0310664 | val_loss: 0.0312353 | Time: 2013.84 ms [2020-11-24 15:46:53 main:581] : INFO : Epoch 87 | loss: 0.0310658 | val_loss: 0.0312362 | Time: 1877.56 ms [2020-11-24 15:46:55 main:581] : INFO : Epoch 88 | loss: 0.0310686 | val_loss: 0.0312229 | Time: 1829.93 ms [2020-11-24 15:46:57 main:581] : INFO : Epoch 89 | loss: 0.0310587 | val_loss: 0.0312337 | Time: 2003.39 ms [2020-11-24 15:46:59 main:581] : INFO : Epoch 90 | loss: 0.0310612 | val_loss: 0.0312273 | Time: 2005.04 ms [2020-11-24 15:47:01 main:581] : INFO : Epoch 91 | loss: 0.0310656 | val_loss: 0.0312168 | Time: 1999.48 ms [2020-11-24 15:47:03 main:581] : INFO : Epoch 92 | loss: 0.0310579 | val_loss: 0.0312063 | Time: 2020.26 ms [2020-11-24 15:47:05 main:581] : INFO : Epoch 93 | loss: 0.0310624 | val_loss: 0.0312192 | Time: 1832.3 ms [2020-11-24 15:47:07 main:581] : INFO : Epoch 94 | loss: 0.031071 | val_loss: 0.0312192 | Time: 1845.48 ms [2020-11-24 15:47:09 main:581] : INFO : Epoch 95 | loss: 0.0310639 | val_loss: 0.0312155 | Time: 1932.13 ms [2020-11-24 15:47:11 main:581] : INFO : Epoch 96 | loss: 0.0310594 | val_loss: 0.0312136 | Time: 1984.78 ms [2020-11-24 15:47:13 main:581] : INFO : Epoch 97 | loss: 0.0310557 | val_loss: 0.0312231 | Time: 2008.43 ms [2020-11-24 15:47:15 main:581] : INFO : Epoch 98 | loss: 0.0310615 | val_loss: 0.0312253 | Time: 1991.28 ms [2020-11-24 15:47:17 main:581] : INFO : Epoch 99 | loss: 0.0310823 | val_loss: 0.0312136 | Time: 2033.95 ms [2020-11-24 15:47:19 main:581] : INFO : Epoch 100 | loss: 0.031085 | val_loss: 0.0312099 | Time: 1974.9 ms [2020-11-24 15:47:21 main:581] : INFO : Epoch 101 | loss: 0.0310683 | val_loss: 0.0312124 | Time: 1857.51 ms [2020-11-24 15:47:22 main:581] : INFO : Epoch 102 | loss: 0.0310652 | val_loss: 0.0312302 | Time: 1899.7 ms [2020-11-24 15:47:24 main:581] : INFO : Epoch 103 | loss: 0.0310624 | val_loss: 0.0312207 | Time: 1996.91 ms [2020-11-24 15:47:26 main:581] : INFO : Epoch 104 | loss: 0.031075 | val_loss: 0.0312221 | Time: 1905.14 ms [2020-11-24 15:47:28 main:581] : INFO : Epoch 105 | loss: 0.0310721 | val_loss: 0.0312051 | Time: 1861.11 ms [2020-11-24 15:47:30 main:581] : INFO : Epoch 106 | loss: 0.0310654 | val_loss: 0.0312105 | Time: 1928.84 ms [2020-11-24 15:47:32 main:581] : INFO : Epoch 107 | loss: 0.0310588 | val_loss: 0.0312301 | Time: 1978.44 ms [2020-11-24 15:47:34 main:581] : INFO : Epoch 108 | loss: 0.0310691 | val_loss: 0.0312169 | Time: 2069.35 ms [2020-11-24 15:47:36 main:581] : INFO : Epoch 109 | loss: 0.0310637 | val_loss: 0.0312262 | Time: 2013.79 ms [2020-11-24 15:47:38 main:581] : INFO : Epoch 110 | loss: 0.0310599 | val_loss: 0.0312153 | Time: 1970.21 ms [2020-11-24 15:47:40 main:581] : INFO : Epoch 111 | loss: 0.0310559 | val_loss: 0.0312419 | Time: 1940.69 ms [2020-11-24 15:47:42 main:581] : INFO : Epoch 112 | loss: 0.0310655 | val_loss: 0.03121 | Time: 1941.95 ms [2020-11-24 15:47:44 main:581] : INFO : Epoch 113 | loss: 0.0310662 | val_loss: 0.0312323 | Time: 2038.68 ms [2020-11-24 15:47:46 main:581] : INFO : Epoch 114 | loss: 0.0310716 | val_loss: 0.0312149 | Time: 1820.5 ms [2020-11-24 15:47:48 main:581] : INFO : Epoch 115 | loss: 0.0310631 | val_loss: 0.0312166 | Time: 1850.75 ms [2020-11-24 15:47:50 main:581] : INFO : Epoch 116 | loss: 0.0310579 | val_loss: 0.0312157 | Time: 1900.78 ms [2020-11-24 15:47:52 main:581] : INFO : Epoch 117 | loss: 0.0310585 | val_loss: 0.0312187 | Time: 1904.96 ms [2020-11-24 15:47:54 main:581] : INFO : Epoch 118 | loss: 0.031052 | val_loss: 0.0312217 | Time: 1961.15 ms [2020-11-24 15:47:55 main:581] : INFO : Epoch 119 | loss: 0.0310561 | val_loss: 0.0312166 | Time: 1908.97 ms [2020-11-24 15:47:57 main:581] : INFO : Epoch 120 | loss: 0.0310535 | val_loss: 0.0312288 | Time: 1889.56 ms [2020-11-24 15:47:59 main:581] : INFO : Epoch 121 | loss: 0.0310528 | val_loss: 0.0312332 | Time: 1988.74 ms [2020-11-24 15:48:01 main:581] : INFO : Epoch 122 | loss: 0.0310554 | val_loss: 0.0312286 | Time: 1938.15 ms [2020-11-24 15:48:03 main:581] : INFO : Epoch 123 | loss: 0.0310599 | val_loss: 0.0312387 | Time: 2001.47 ms [2020-11-24 15:48:05 main:581] : INFO : Epoch 124 | loss: 0.031057 | val_loss: 0.0312254 | Time: 2047.92 ms [2020-11-24 15:48:07 main:581] : INFO : Epoch 125 | loss: 0.0310531 | val_loss: 0.031227 | Time: 1962.41 ms [2020-11-24 15:48:09 main:581] : INFO : Epoch 126 | loss: 0.0310552 | val_loss: 0.0312191 | Time: 1935.74 ms [2020-11-24 15:48:11 main:581] : INFO : Epoch 127 | loss: 0.0310608 | val_loss: 0.0312154 | Time: 2077.63 ms [2020-11-24 15:48:13 main:581] : INFO : Epoch 128 | loss: 0.0310606 | val_loss: 0.0312358 | Time: 1963.67 ms [2020-11-24 15:48:13 main:604] : INFO : Saving trained model to model-final.pt, val_loss 0.0312358 [2020-11-24 15:48:13 main:610] : INFO : Saving end state to config to file [2020-11-24 15:48:13 main:615] : INFO : Success, exiting.. 15:48:13 (8928): 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)