renaissance-movie-lens_0
[2024-10-30T21:37:57.793Z] Running test renaissance-movie-lens_0 ...
[2024-10-30T21:37:57.793Z] ===============================================
[2024-10-30T21:37:57.793Z] renaissance-movie-lens_0 Start Time: Wed Oct 30 17:37:57 2024 Epoch Time (ms): 1730324277307
[2024-10-30T21:37:57.793Z] variation: NoOptions
[2024-10-30T21:37:57.793Z] JVM_OPTIONS:
[2024-10-30T21:37:57.793Z] { \
[2024-10-30T21:37:57.793Z] echo ""; echo "TEST SETUP:"; \
[2024-10-30T21:37:57.793Z] echo "Nothing to be done for setup."; \
[2024-10-30T21:37:57.793Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17303239888217/renaissance-movie-lens_0"; \
[2024-10-30T21:37:57.794Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17303239888217/renaissance-movie-lens_0"; \
[2024-10-30T21:37:57.794Z] echo ""; echo "TESTING:"; \
[2024-10-30T21:37:57.794Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/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_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17303239888217/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-10-30T21:37:57.794Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17303239888217/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-10-30T21:37:57.794Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-10-30T21:37:57.794Z] echo "Nothing to be done for teardown."; \
[2024-10-30T21:37:57.794Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17303239888217/TestTargetResult";
[2024-10-30T21:37:57.794Z]
[2024-10-30T21:37:57.794Z] TEST SETUP:
[2024-10-30T21:37:57.794Z] Nothing to be done for setup.
[2024-10-30T21:37:57.794Z]
[2024-10-30T21:37:57.794Z] TESTING:
[2024-10-30T21:37:59.060Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-10-30T21:37:59.432Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-10-30T21:38:00.774Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-10-30T21:38:00.774Z] Training: 60056, validation: 20285, test: 19854
[2024-10-30T21:38:00.774Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-10-30T21:38:00.774Z] GC before operation: completed in 17.224 ms, heap usage 91.717 MB -> 37.231 MB.
[2024-10-30T21:38:03.250Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:05.105Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:06.402Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:07.673Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:08.042Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:08.838Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:09.659Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:10.491Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:10.491Z] 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.
[2024-10-30T21:38:10.491Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:10.491Z] Movies recommended for you:
[2024-10-30T21:38:10.491Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:10.491Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:10.491Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (9790.357 ms) ======
[2024-10-30T21:38:10.491Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-10-30T21:38:10.491Z] GC before operation: completed in 29.010 ms, heap usage 280.890 MB -> 50.550 MB.
[2024-10-30T21:38:11.800Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:13.160Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:14.447Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:15.731Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:16.522Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:16.891Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:17.703Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:18.502Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:18.502Z] 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.
[2024-10-30T21:38:18.882Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:18.882Z] Movies recommended for you:
[2024-10-30T21:38:18.882Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:18.882Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:18.882Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8159.054 ms) ======
[2024-10-30T21:38:18.882Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-10-30T21:38:18.882Z] GC before operation: completed in 27.351 ms, heap usage 234.816 MB -> 49.625 MB.
[2024-10-30T21:38:20.175Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:20.975Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:22.829Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:23.652Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:24.459Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:25.257Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:26.066Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:26.875Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:27.248Z] 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.
[2024-10-30T21:38:27.248Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:27.248Z] Movies recommended for you:
[2024-10-30T21:38:27.248Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:27.248Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:27.248Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8487.150 ms) ======
[2024-10-30T21:38:27.248Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-10-30T21:38:27.248Z] GC before operation: completed in 50.687 ms, heap usage 92.957 MB -> 49.692 MB.
[2024-10-30T21:38:28.533Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:30.405Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:31.202Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:32.536Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:32.908Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:33.707Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:34.084Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:34.891Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:34.891Z] 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.
[2024-10-30T21:38:34.891Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:35.269Z] Movies recommended for you:
[2024-10-30T21:38:35.269Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:35.269Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:35.269Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (7798.640 ms) ======
[2024-10-30T21:38:35.269Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-10-30T21:38:35.269Z] GC before operation: completed in 36.524 ms, heap usage 228.073 MB -> 50.267 MB.
[2024-10-30T21:38:36.568Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:37.890Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:39.192Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:40.471Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:41.284Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:42.079Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:42.883Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:43.685Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:44.065Z] 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.
[2024-10-30T21:38:44.065Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:44.065Z] Movies recommended for you:
[2024-10-30T21:38:44.065Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:44.065Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:44.065Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8837.521 ms) ======
[2024-10-30T21:38:44.065Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-10-30T21:38:44.065Z] GC before operation: completed in 34.041 ms, heap usage 70.854 MB -> 50.472 MB.
[2024-10-30T21:38:45.364Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:46.164Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:47.445Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:48.248Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:49.124Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:49.502Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:50.302Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:51.105Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:51.105Z] 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.
[2024-10-30T21:38:51.105Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:51.105Z] Movies recommended for you:
[2024-10-30T21:38:51.105Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:51.105Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:51.105Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (7169.270 ms) ======
[2024-10-30T21:38:51.105Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-10-30T21:38:51.105Z] GC before operation: completed in 31.775 ms, heap usage 362.391 MB -> 53.748 MB.
[2024-10-30T21:38:52.412Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:38:53.205Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:38:54.484Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:38:55.278Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:38:56.083Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:38:56.883Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:38:57.685Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:38:58.486Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:38:58.486Z] 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.
[2024-10-30T21:38:58.486Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:38:58.486Z] Movies recommended for you:
[2024-10-30T21:38:58.486Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:38:58.486Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:38:58.486Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7345.544 ms) ======
[2024-10-30T21:38:58.486Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-10-30T21:38:58.486Z] GC before operation: completed in 42.991 ms, heap usage 324.777 MB -> 50.672 MB.
[2024-10-30T21:38:59.772Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:01.073Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:02.382Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:03.684Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:04.147Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:04.946Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:05.811Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:06.185Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:06.554Z] 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.
[2024-10-30T21:39:06.554Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:06.554Z] Movies recommended for you:
[2024-10-30T21:39:06.554Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:06.554Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:06.554Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (7887.402 ms) ======
[2024-10-30T21:39:06.554Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-10-30T21:39:06.554Z] GC before operation: completed in 34.052 ms, heap usage 71.453 MB -> 50.598 MB.
[2024-10-30T21:39:07.859Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:09.143Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:09.966Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:11.252Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:12.054Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:12.850Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:13.649Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:14.470Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:14.470Z] 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.
[2024-10-30T21:39:14.470Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:14.846Z] Movies recommended for you:
[2024-10-30T21:39:14.846Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:14.846Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:14.846Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8147.881 ms) ======
[2024-10-30T21:39:14.846Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-10-30T21:39:14.846Z] GC before operation: completed in 31.673 ms, heap usage 261.682 MB -> 50.675 MB.
[2024-10-30T21:39:15.639Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:16.920Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:18.197Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:19.484Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:20.296Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:20.663Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:21.467Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:21.841Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:21.841Z] 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.
[2024-10-30T21:39:21.841Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:21.841Z] Movies recommended for you:
[2024-10-30T21:39:21.841Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:21.841Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:21.841Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7254.378 ms) ======
[2024-10-30T21:39:21.841Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-10-30T21:39:21.841Z] GC before operation: completed in 34.256 ms, heap usage 302.950 MB -> 50.874 MB.
[2024-10-30T21:39:23.123Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:24.486Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:25.396Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:26.194Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:27.001Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:27.798Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:28.595Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:28.968Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:29.341Z] 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.
[2024-10-30T21:39:29.341Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:29.341Z] Movies recommended for you:
[2024-10-30T21:39:29.341Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:29.341Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:29.341Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (7256.910 ms) ======
[2024-10-30T21:39:29.341Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-10-30T21:39:29.341Z] GC before operation: completed in 40.132 ms, heap usage 298.618 MB -> 50.787 MB.
[2024-10-30T21:39:30.134Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:31.451Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:32.727Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:34.001Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:34.376Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:35.170Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:35.589Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:36.382Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:36.382Z] 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.
[2024-10-30T21:39:36.382Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:36.382Z] Movies recommended for you:
[2024-10-30T21:39:36.382Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:36.382Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:36.382Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (7251.907 ms) ======
[2024-10-30T21:39:36.382Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-10-30T21:39:36.382Z] GC before operation: completed in 0.332 ms, heap usage 71.063 MB -> 71.133 MB.
[2024-10-30T21:39:37.191Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:38.487Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:39.274Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:40.059Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:40.869Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:41.241Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:42.026Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:42.429Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:42.802Z] 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.
[2024-10-30T21:39:42.802Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:42.802Z] Movies recommended for you:
[2024-10-30T21:39:42.802Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:42.802Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:42.802Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (6130.907 ms) ======
[2024-10-30T21:39:42.802Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-10-30T21:39:42.802Z] GC before operation: completed in 29.364 ms, heap usage 74.364 MB -> 50.666 MB.
[2024-10-30T21:39:43.590Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:44.864Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:45.658Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:46.446Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:47.234Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:47.608Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:48.413Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:48.783Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:49.170Z] 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.
[2024-10-30T21:39:49.170Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:49.170Z] Movies recommended for you:
[2024-10-30T21:39:49.170Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:49.170Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:49.170Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (6386.336 ms) ======
[2024-10-30T21:39:49.170Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-10-30T21:39:49.170Z] GC before operation: completed in 31.164 ms, heap usage 365.666 MB -> 54.023 MB.
[2024-10-30T21:39:49.960Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:50.748Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:52.031Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:52.829Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:53.639Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:54.010Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:39:54.380Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:39:55.184Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:39:55.184Z] 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.
[2024-10-30T21:39:55.184Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:39:55.184Z] Movies recommended for you:
[2024-10-30T21:39:55.184Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:39:55.184Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:39:55.184Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (6025.524 ms) ======
[2024-10-30T21:39:55.184Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-10-30T21:39:55.184Z] GC before operation: completed in 29.892 ms, heap usage 205.415 MB -> 50.770 MB.
[2024-10-30T21:39:55.968Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:39:56.769Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:39:57.590Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:39:58.954Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:39:59.351Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:39:59.721Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:40:00.094Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:40:00.929Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:40:00.929Z] 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.
[2024-10-30T21:40:00.929Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:40:00.930Z] Movies recommended for you:
[2024-10-30T21:40:00.930Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:40:00.930Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:40:00.930Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (5663.453 ms) ======
[2024-10-30T21:40:00.930Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-10-30T21:40:00.930Z] GC before operation: completed in 28.930 ms, heap usage 234.331 MB -> 51.097 MB.
[2024-10-30T21:40:01.735Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:40:02.553Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:40:03.876Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:40:04.739Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:40:05.112Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:40:05.910Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:40:06.283Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:40:07.094Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:40:07.095Z] 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.
[2024-10-30T21:40:07.095Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:40:07.095Z] Movies recommended for you:
[2024-10-30T21:40:07.095Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:40:07.095Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:40:07.095Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (6192.135 ms) ======
[2024-10-30T21:40:07.095Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-10-30T21:40:07.095Z] GC before operation: completed in 30.015 ms, heap usage 297.367 MB -> 50.884 MB.
[2024-10-30T21:40:07.889Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:40:09.176Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:40:09.986Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:40:10.789Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:40:11.575Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:40:11.949Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:40:12.739Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:40:13.542Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:40:13.542Z] 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.
[2024-10-30T21:40:13.542Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:40:13.542Z] Movies recommended for you:
[2024-10-30T21:40:13.542Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:40:13.542Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:40:13.542Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (6470.502 ms) ======
[2024-10-30T21:40:13.542Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-10-30T21:40:13.542Z] GC before operation: completed in 32.646 ms, heap usage 69.873 MB -> 50.901 MB.
[2024-10-30T21:40:14.826Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:40:15.621Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:40:16.909Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:40:18.214Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:40:18.583Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:40:18.958Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:40:19.752Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:40:20.124Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:40:20.493Z] 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.
[2024-10-30T21:40:20.493Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:40:20.493Z] Movies recommended for you:
[2024-10-30T21:40:20.493Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:40:20.493Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:40:20.493Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (6850.012 ms) ======
[2024-10-30T21:40:20.493Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-10-30T21:40:20.493Z] GC before operation: completed in 35.554 ms, heap usage 409.277 MB -> 54.416 MB.
[2024-10-30T21:40:21.765Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-30T21:40:22.552Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-30T21:40:23.849Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-30T21:40:24.641Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-30T21:40:25.437Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-30T21:40:25.824Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-30T21:40:26.630Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-30T21:40:27.418Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-30T21:40:27.418Z] 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.
[2024-10-30T21:40:27.418Z] The best model improves the baseline by 14.52%.
[2024-10-30T21:40:27.418Z] Movies recommended for you:
[2024-10-30T21:40:27.418Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-30T21:40:27.418Z] There is no way to check that no silent failure occurred.
[2024-10-30T21:40:27.418Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (6909.554 ms) ======
[2024-10-30T21:40:27.418Z] -----------------------------------
[2024-10-30T21:40:27.418Z] renaissance-movie-lens_0_PASSED
[2024-10-30T21:40:27.418Z] -----------------------------------
[2024-10-30T21:40:27.418Z]
[2024-10-30T21:40:27.418Z] TEST TEARDOWN:
[2024-10-30T21:40:27.418Z] Nothing to be done for teardown.
[2024-10-30T21:40:27.418Z] renaissance-movie-lens_0 Finish Time: Wed Oct 30 17:40:27 2024 Epoch Time (ms): 1730324427329