renaissance-movie-lens_0
[2024-11-14T05:35:45.672Z] Running test renaissance-movie-lens_0 ...
[2024-11-14T05:35:45.672Z] ===============================================
[2024-11-14T05:35:45.672Z] renaissance-movie-lens_0 Start Time: Wed Nov 13 21:35:44 2024 Epoch Time (ms): 1731562544165
[2024-11-14T05:35:45.672Z] variation: NoOptions
[2024-11-14T05:35:45.672Z] JVM_OPTIONS:
[2024-11-14T05:35:45.672Z] { \
[2024-11-14T05:35:45.672Z] echo ""; echo "TEST SETUP:"; \
[2024-11-14T05:35:45.672Z] echo "Nothing to be done for setup."; \
[2024-11-14T05:35:45.672Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17315584057472/renaissance-movie-lens_0"; \
[2024-11-14T05:35:45.672Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17315584057472/renaissance-movie-lens_0"; \
[2024-11-14T05:35:45.672Z] echo ""; echo "TESTING:"; \
[2024-11-14T05:35:45.672Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17315584057472/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-14T05:35:45.672Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17315584057472/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-14T05:35:45.672Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-14T05:35:45.672Z] echo "Nothing to be done for teardown."; \
[2024-11-14T05:35:45.672Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17315584057472/TestTargetResult";
[2024-11-14T05:35:45.672Z]
[2024-11-14T05:35:45.672Z] TEST SETUP:
[2024-11-14T05:35:45.672Z] Nothing to be done for setup.
[2024-11-14T05:35:45.672Z]
[2024-11-14T05:35:45.672Z] TESTING:
[2024-11-14T05:36:04.521Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-14T05:36:10.982Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-11-14T05:36:30.165Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-14T05:36:31.375Z] Training: 60056, validation: 20285, test: 19854
[2024-11-14T05:36:31.375Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-14T05:36:31.375Z] GC before operation: completed in 339.017 ms, heap usage 208.416 MB -> 36.678 MB.
[2024-11-14T05:37:17.026Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:37:44.499Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:38:12.702Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:38:32.962Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:38:42.817Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:38:55.104Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:39:10.203Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:39:25.330Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:39:26.310Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:39:26.890Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:39:28.327Z] Movies recommended for you:
[2024-11-14T05:39:28.327Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:39:28.327Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:39:28.327Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (176938.160 ms) ======
[2024-11-14T05:39:28.327Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-14T05:39:28.829Z] GC before operation: completed in 348.176 ms, heap usage 293.125 MB -> 46.955 MB.
[2024-11-14T05:39:48.250Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:40:07.681Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:40:35.849Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:40:55.300Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:41:05.087Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:41:16.802Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:41:30.398Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:41:38.919Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:41:40.891Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:41:40.891Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:41:41.324Z] Movies recommended for you:
[2024-11-14T05:41:41.324Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:41:41.324Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:41:41.324Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (132346.815 ms) ======
[2024-11-14T05:41:41.324Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-14T05:41:41.324Z] GC before operation: completed in 220.721 ms, heap usage 173.658 MB -> 48.886 MB.
[2024-11-14T05:42:00.844Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:42:27.643Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:42:46.511Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:43:09.670Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:43:21.031Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:43:32.074Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:43:39.735Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:43:52.799Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:43:52.799Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:43:52.799Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:43:53.410Z] Movies recommended for you:
[2024-11-14T05:43:53.410Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:43:53.410Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:43:53.410Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (132096.242 ms) ======
[2024-11-14T05:43:53.410Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-14T05:43:54.743Z] GC before operation: completed in 716.249 ms, heap usage 97.194 MB -> 50.667 MB.
[2024-11-14T05:44:23.352Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:44:55.916Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:45:07.603Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:45:26.671Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:45:36.361Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:45:53.015Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:46:01.132Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:46:13.357Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:46:13.357Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:46:13.933Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:46:13.933Z] Movies recommended for you:
[2024-11-14T05:46:13.934Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:46:13.934Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:46:13.934Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (139757.964 ms) ======
[2024-11-14T05:46:13.934Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-14T05:46:14.457Z] GC before operation: completed in 451.547 ms, heap usage 389.077 MB -> 52.825 MB.
[2024-11-14T05:46:41.513Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:46:56.852Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:47:13.247Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:47:32.088Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:47:47.162Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:47:56.489Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:48:04.799Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:48:15.000Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:48:15.000Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:48:15.000Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:48:15.000Z] Movies recommended for you:
[2024-11-14T05:48:15.000Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:48:15.000Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:48:15.000Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (120584.992 ms) ======
[2024-11-14T05:48:15.000Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-14T05:48:16.174Z] GC before operation: completed in 1303.211 ms, heap usage 143.339 MB -> 49.612 MB.
[2024-11-14T05:48:31.740Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:48:50.695Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:49:06.937Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:49:26.081Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:49:32.574Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:49:44.724Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:49:58.610Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:50:08.696Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:50:10.651Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:50:10.651Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:50:12.371Z] Movies recommended for you:
[2024-11-14T05:50:12.371Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:50:12.371Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:50:12.371Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (115618.016 ms) ======
[2024-11-14T05:50:12.371Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-14T05:50:12.371Z] GC before operation: completed in 293.707 ms, heap usage 118.080 MB -> 49.515 MB.
[2024-11-14T05:50:34.768Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:50:51.021Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:51:09.897Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:51:29.530Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:51:46.688Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:51:56.394Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:52:08.468Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:52:17.031Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:52:19.229Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:52:19.229Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:52:19.750Z] Movies recommended for you:
[2024-11-14T05:52:19.750Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:52:19.750Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:52:19.750Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (127538.972 ms) ======
[2024-11-14T05:52:19.750Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-14T05:52:20.291Z] GC before operation: completed in 203.233 ms, heap usage 100.014 MB -> 51.252 MB.
[2024-11-14T05:52:42.953Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:53:01.954Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:53:30.140Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:53:45.932Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:53:54.047Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:54:05.120Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:54:16.990Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:54:24.874Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:54:25.836Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:54:26.330Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:54:26.330Z] Movies recommended for you:
[2024-11-14T05:54:26.330Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:54:26.330Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:54:26.330Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (126322.401 ms) ======
[2024-11-14T05:54:26.330Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-14T05:54:27.374Z] GC before operation: completed in 557.890 ms, heap usage 475.264 MB -> 53.599 MB.
[2024-11-14T05:54:55.193Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:55:11.723Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:55:44.102Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:56:01.071Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:56:08.629Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:56:20.047Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:56:31.069Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:56:41.332Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:56:41.332Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:56:41.332Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:56:42.059Z] Movies recommended for you:
[2024-11-14T05:56:42.059Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:56:42.059Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:56:42.059Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (135251.114 ms) ======
[2024-11-14T05:56:42.059Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-14T05:56:43.352Z] GC before operation: completed in 1358.542 ms, heap usage 331.507 MB -> 50.026 MB.
[2024-11-14T05:57:06.517Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:57:33.624Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T05:57:50.641Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T05:58:06.403Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T05:58:15.201Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T05:58:25.585Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T05:58:42.121Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T05:58:55.647Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T05:58:56.848Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T05:58:57.411Z] The best model improves the baseline by 14.52%.
[2024-11-14T05:58:58.441Z] Movies recommended for you:
[2024-11-14T05:58:58.441Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T05:58:58.441Z] There is no way to check that no silent failure occurred.
[2024-11-14T05:58:58.441Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (134959.101 ms) ======
[2024-11-14T05:58:58.441Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-14T05:58:58.932Z] GC before operation: completed in 423.650 ms, heap usage 234.144 MB -> 50.031 MB.
[2024-11-14T05:59:19.086Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T05:59:38.314Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:00:06.046Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:00:22.514Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:00:31.057Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:00:43.127Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:00:54.125Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:01:05.147Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:01:05.147Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:01:05.147Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:01:05.147Z] Movies recommended for you:
[2024-11-14T06:01:05.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:01:05.147Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:01:05.147Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (125969.796 ms) ======
[2024-11-14T06:01:05.147Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-14T06:01:05.652Z] GC before operation: completed in 672.874 ms, heap usage 108.613 MB -> 49.634 MB.
[2024-11-14T06:01:28.100Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:01:44.801Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:02:04.319Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:02:20.912Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:02:30.621Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:02:42.274Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:02:50.416Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:02:59.861Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:03:02.144Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:03:02.672Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:03:02.672Z] Movies recommended for you:
[2024-11-14T06:03:02.672Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:03:02.672Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:03:02.672Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (117169.786 ms) ======
[2024-11-14T06:03:02.672Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-14T06:03:03.140Z] GC before operation: completed in 391.034 ms, heap usage 229.178 MB -> 49.949 MB.
[2024-11-14T06:03:24.658Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:03:40.538Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:04:03.336Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:04:26.789Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:04:36.347Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:04:50.557Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:05:10.982Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:05:20.526Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:05:21.284Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:05:21.284Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:05:21.880Z] Movies recommended for you:
[2024-11-14T06:05:21.880Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:05:21.880Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:05:21.880Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (138809.582 ms) ======
[2024-11-14T06:05:21.880Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-14T06:05:22.374Z] GC before operation: completed in 424.357 ms, heap usage 141.367 MB -> 50.004 MB.
[2024-11-14T06:05:44.878Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:06:01.031Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:06:24.690Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:06:48.890Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:06:58.862Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:07:09.065Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:07:20.864Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:07:27.462Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:07:29.926Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:07:29.926Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:07:30.404Z] Movies recommended for you:
[2024-11-14T06:07:30.404Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:07:30.404Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:07:30.404Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (127860.773 ms) ======
[2024-11-14T06:07:30.404Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-14T06:07:30.404Z] GC before operation: completed in 318.906 ms, heap usage 461.540 MB -> 54.974 MB.
[2024-11-14T06:07:54.277Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:08:10.375Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:08:33.170Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:08:56.496Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:09:06.928Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:09:14.880Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:09:35.522Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:09:42.039Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:09:42.486Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:09:42.948Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:09:42.948Z] Movies recommended for you:
[2024-11-14T06:09:42.948Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:09:42.948Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:09:42.948Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (132566.385 ms) ======
[2024-11-14T06:09:42.948Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-14T06:09:43.465Z] GC before operation: completed in 383.570 ms, heap usage 260.966 MB -> 50.036 MB.
[2024-11-14T06:10:10.929Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:10:34.924Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:10:55.039Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:11:09.548Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:11:29.090Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:11:35.104Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:11:50.678Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:12:08.438Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:12:08.438Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:12:08.844Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:12:08.844Z] Movies recommended for you:
[2024-11-14T06:12:08.844Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:12:08.844Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:12:08.844Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (145452.693 ms) ======
[2024-11-14T06:12:08.844Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-14T06:12:09.375Z] GC before operation: completed in 288.547 ms, heap usage 329.875 MB -> 50.240 MB.
[2024-11-14T06:12:28.620Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:12:45.058Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:13:05.007Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:13:20.943Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:13:32.097Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:13:39.062Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:13:50.824Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:14:04.550Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:14:05.041Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:14:05.041Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:14:05.463Z] Movies recommended for you:
[2024-11-14T06:14:05.463Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:14:05.463Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:14:05.463Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (116093.511 ms) ======
[2024-11-14T06:14:05.463Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-14T06:14:06.153Z] GC before operation: completed in 355.407 ms, heap usage 252.907 MB -> 49.966 MB.
[2024-11-14T06:14:25.340Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:14:45.045Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:15:14.204Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:15:31.527Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:15:41.049Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:15:52.286Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:16:00.717Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:16:12.730Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:16:12.731Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:16:12.731Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:16:14.511Z] Movies recommended for you:
[2024-11-14T06:16:14.511Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:16:14.511Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:16:14.511Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (128064.015 ms) ======
[2024-11-14T06:16:14.511Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-14T06:16:14.511Z] GC before operation: completed in 657.111 ms, heap usage 115.774 MB -> 49.885 MB.
[2024-11-14T06:16:38.152Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:16:58.209Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:17:21.399Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:17:35.751Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:17:47.333Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:18:01.258Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:18:18.787Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:18:27.257Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:18:28.315Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:18:28.315Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:18:29.022Z] Movies recommended for you:
[2024-11-14T06:18:29.022Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:18:29.022Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:18:29.022Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (134333.965 ms) ======
[2024-11-14T06:18:29.022Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-14T06:18:30.437Z] GC before operation: completed in 1403.114 ms, heap usage 158.567 MB -> 50.147 MB.
[2024-11-14T06:18:49.861Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-14T06:19:09.433Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-14T06:19:23.783Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-14T06:19:48.112Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-14T06:19:56.545Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-14T06:20:08.117Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-14T06:20:17.719Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-14T06:20:27.421Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-14T06:20:28.793Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-11-14T06:20:28.793Z] The best model improves the baseline by 14.52%.
[2024-11-14T06:20:29.209Z] Movies recommended for you:
[2024-11-14T06:20:29.209Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-14T06:20:29.209Z] There is no way to check that no silent failure occurred.
[2024-11-14T06:20:29.209Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (119103.944 ms) ======
[2024-11-14T06:20:33.902Z] -----------------------------------
[2024-11-14T06:20:33.902Z] renaissance-movie-lens_0_PASSED
[2024-11-14T06:20:33.902Z] -----------------------------------
[2024-11-14T06:20:34.978Z]
[2024-11-14T06:20:34.978Z] TEST TEARDOWN:
[2024-11-14T06:20:34.978Z] Nothing to be done for teardown.
[2024-11-14T06:20:35.422Z] renaissance-movie-lens_0 Finish Time: Wed Nov 13 22:20:34 2024 Epoch Time (ms): 1731565234379