renaissance-movie-lens_0
[2025-02-12T21:42:40.148Z] Running test renaissance-movie-lens_0 ...
[2025-02-12T21:42:40.148Z] ===============================================
[2025-02-12T21:42:40.148Z] renaissance-movie-lens_0 Start Time: Wed Feb 12 16:42:39 2025 Epoch Time (ms): 1739396559893
[2025-02-12T21:42:40.148Z] variation: NoOptions
[2025-02-12T21:42:40.148Z] JVM_OPTIONS:
[2025-02-12T21:42:40.148Z] { \
[2025-02-12T21:42:40.148Z] echo ""; echo "TEST SETUP:"; \
[2025-02-12T21:42:40.148Z] echo "Nothing to be done for setup."; \
[2025-02-12T21:42:40.148Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17393962263427/renaissance-movie-lens_0"; \
[2025-02-12T21:42:40.148Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17393962263427/renaissance-movie-lens_0"; \
[2025-02-12T21:42:40.148Z] echo ""; echo "TESTING:"; \
[2025-02-12T21:42:40.148Z] "/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_17393962263427/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2025-02-12T21:42:40.148Z] 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_17393962263427/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2025-02-12T21:42:40.148Z] echo ""; echo "TEST TEARDOWN:"; \
[2025-02-12T21:42:40.148Z] echo "Nothing to be done for teardown."; \
[2025-02-12T21:42:40.148Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17393962263427/TestTargetResult";
[2025-02-12T21:42:40.148Z]
[2025-02-12T21:42:40.148Z] TEST SETUP:
[2025-02-12T21:42:40.148Z] Nothing to be done for setup.
[2025-02-12T21:42:40.148Z]
[2025-02-12T21:42:40.148Z] TESTING:
[2025-02-12T21:42:41.958Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2025-02-12T21:42:42.729Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2025-02-12T21:42:44.044Z] Got 100004 ratings from 671 users on 9066 movies.
[2025-02-12T21:42:44.044Z] Training: 60056, validation: 20285, test: 19854
[2025-02-12T21:42:44.044Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2025-02-12T21:42:44.044Z] GC before operation: completed in 20.244 ms, heap usage 70.658 MB -> 37.222 MB.
[2025-02-12T21:42:46.608Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:42:48.410Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:42:50.190Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:42:50.964Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:42:51.734Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:42:52.499Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:42:53.285Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:42:54.055Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:42:54.055Z] 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.
[2025-02-12T21:42:54.420Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:42:54.420Z] Movies recommended for you:
[2025-02-12T21:42:54.420Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:42:54.420Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:42:54.420Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (10235.837 ms) ======
[2025-02-12T21:42:54.420Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2025-02-12T21:42:54.420Z] GC before operation: completed in 41.174 ms, heap usage 200.675 MB -> 52.655 MB.
[2025-02-12T21:42:55.675Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:42:56.927Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:42:57.709Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:42:58.949Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:42:59.748Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:00.125Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:00.906Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:01.742Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:01.742Z] 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.
[2025-02-12T21:43:01.742Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:01.742Z] Movies recommended for you:
[2025-02-12T21:43:01.742Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:01.742Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:01.742Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (7539.781 ms) ======
[2025-02-12T21:43:01.742Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2025-02-12T21:43:02.115Z] GC before operation: completed in 34.629 ms, heap usage 277.705 MB -> 49.573 MB.
[2025-02-12T21:43:02.904Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:04.153Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:04.930Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:06.219Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:06.580Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:07.352Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:08.118Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:08.494Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:08.887Z] 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.
[2025-02-12T21:43:08.888Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:08.888Z] Movies recommended for you:
[2025-02-12T21:43:08.888Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:08.888Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:08.888Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (6802.502 ms) ======
[2025-02-12T21:43:08.888Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2025-02-12T21:43:08.888Z] GC before operation: completed in 40.447 ms, heap usage 191.907 MB -> 49.836 MB.
[2025-02-12T21:43:09.686Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:10.946Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:11.776Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:13.057Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:13.436Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:14.219Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:15.013Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:15.408Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:15.408Z] 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.
[2025-02-12T21:43:15.408Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:15.774Z] Movies recommended for you:
[2025-02-12T21:43:15.774Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:15.774Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:15.774Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (6822.190 ms) ======
[2025-02-12T21:43:15.774Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2025-02-12T21:43:15.774Z] GC before operation: completed in 38.030 ms, heap usage 236.360 MB -> 50.328 MB.
[2025-02-12T21:43:16.558Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:17.837Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:18.621Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:19.886Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:20.256Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:21.022Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:21.809Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:22.167Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:22.527Z] 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.
[2025-02-12T21:43:22.527Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:22.527Z] Movies recommended for you:
[2025-02-12T21:43:22.527Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:22.527Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:22.527Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (6819.593 ms) ======
[2025-02-12T21:43:22.527Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2025-02-12T21:43:22.527Z] GC before operation: completed in 29.708 ms, heap usage 126.635 MB -> 50.360 MB.
[2025-02-12T21:43:23.792Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:25.058Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:25.853Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:27.103Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:27.463Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:28.236Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:28.598Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:29.379Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:29.379Z] 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.
[2025-02-12T21:43:29.379Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:29.379Z] Movies recommended for you:
[2025-02-12T21:43:29.379Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:29.379Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:29.379Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (6996.085 ms) ======
[2025-02-12T21:43:29.379Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2025-02-12T21:43:29.379Z] GC before operation: completed in 30.715 ms, heap usage 260.658 MB -> 50.355 MB.
[2025-02-12T21:43:30.649Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:31.437Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:32.695Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:33.473Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:34.266Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:34.626Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:35.394Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:36.174Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:36.174Z] 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.
[2025-02-12T21:43:36.174Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:36.174Z] Movies recommended for you:
[2025-02-12T21:43:36.174Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:36.174Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:36.174Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (6606.618 ms) ======
[2025-02-12T21:43:36.174Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2025-02-12T21:43:36.174Z] GC before operation: completed in 29.620 ms, heap usage 133.519 MB -> 50.557 MB.
[2025-02-12T21:43:36.937Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:38.729Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:39.998Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:41.236Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:42.006Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:42.775Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:43.548Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:44.362Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:44.362Z] 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.
[2025-02-12T21:43:44.362Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:44.718Z] Movies recommended for you:
[2025-02-12T21:43:44.718Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:44.718Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:44.718Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (8456.615 ms) ======
[2025-02-12T21:43:44.718Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2025-02-12T21:43:44.718Z] GC before operation: completed in 29.573 ms, heap usage 58.878 MB -> 50.936 MB.
[2025-02-12T21:43:45.978Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:46.752Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:47.995Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:49.225Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:49.591Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:50.383Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:51.166Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:51.929Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:51.929Z] 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.
[2025-02-12T21:43:51.929Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:51.929Z] Movies recommended for you:
[2025-02-12T21:43:51.929Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:51.929Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:51.929Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (7233.753 ms) ======
[2025-02-12T21:43:51.929Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2025-02-12T21:43:51.929Z] GC before operation: completed in 30.575 ms, heap usage 259.308 MB -> 50.731 MB.
[2025-02-12T21:43:53.166Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:43:53.949Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:43:55.205Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:43:55.999Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:43:56.777Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:43:57.150Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:43:57.954Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:43:58.314Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:43:58.314Z] 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.
[2025-02-12T21:43:58.314Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:43:58.314Z] Movies recommended for you:
[2025-02-12T21:43:58.314Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:43:58.314Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:43:58.314Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (6470.228 ms) ======
[2025-02-12T21:43:58.314Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2025-02-12T21:43:58.314Z] GC before operation: completed in 29.804 ms, heap usage 99.734 MB -> 52.326 MB.
[2025-02-12T21:43:59.083Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:00.323Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:01.588Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:02.369Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:02.740Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:03.514Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:03.883Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:04.688Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:04.688Z] 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.
[2025-02-12T21:44:04.688Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:04.688Z] Movies recommended for you:
[2025-02-12T21:44:04.688Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:04.688Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:04.688Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (6212.868 ms) ======
[2025-02-12T21:44:04.688Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2025-02-12T21:44:04.688Z] GC before operation: completed in 29.222 ms, heap usage 239.218 MB -> 50.614 MB.
[2025-02-12T21:44:05.456Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:06.355Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:07.651Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:08.415Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:09.191Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:09.975Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:10.338Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:11.103Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:11.103Z] 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.
[2025-02-12T21:44:11.103Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:11.103Z] Movies recommended for you:
[2025-02-12T21:44:11.103Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:11.103Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:11.103Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (6431.127 ms) ======
[2025-02-12T21:44:11.103Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2025-02-12T21:44:11.103Z] GC before operation: completed in 31.044 ms, heap usage 125.298 MB -> 50.573 MB.
[2025-02-12T21:44:12.353Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:13.145Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:14.400Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:15.639Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:16.426Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:17.212Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:18.005Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:18.804Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:18.804Z] 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.
[2025-02-12T21:44:18.804Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:19.163Z] Movies recommended for you:
[2025-02-12T21:44:19.163Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:19.163Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:19.163Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7917.168 ms) ======
[2025-02-12T21:44:19.163Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2025-02-12T21:44:19.163Z] GC before operation: completed in 34.683 ms, heap usage 241.432 MB -> 50.860 MB.
[2025-02-12T21:44:20.458Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:21.235Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:22.516Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:23.771Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:24.567Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:25.365Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:26.607Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:26.970Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:27.329Z] 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.
[2025-02-12T21:44:27.329Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:27.329Z] Movies recommended for you:
[2025-02-12T21:44:27.329Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:27.329Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:27.329Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8201.842 ms) ======
[2025-02-12T21:44:27.329Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2025-02-12T21:44:27.329Z] GC before operation: completed in 30.750 ms, heap usage 126.391 MB -> 50.625 MB.
[2025-02-12T21:44:28.567Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:29.815Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:31.111Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:32.380Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:33.632Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:33.997Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:34.797Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:35.576Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:35.940Z] 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.
[2025-02-12T21:44:35.940Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:35.940Z] Movies recommended for you:
[2025-02-12T21:44:35.940Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:35.940Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:35.940Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8630.972 ms) ======
[2025-02-12T21:44:35.940Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2025-02-12T21:44:35.940Z] GC before operation: completed in 40.959 ms, heap usage 330.402 MB -> 50.965 MB.
[2025-02-12T21:44:37.743Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:38.994Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:40.239Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:41.489Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:42.736Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:43.511Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:44.297Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:45.067Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:45.431Z] 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.
[2025-02-12T21:44:45.431Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:45.431Z] Movies recommended for you:
[2025-02-12T21:44:45.431Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:45.431Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:45.431Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (9408.009 ms) ======
[2025-02-12T21:44:45.431Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2025-02-12T21:44:45.431Z] GC before operation: completed in 50.537 ms, heap usage 124.566 MB -> 50.804 MB.
[2025-02-12T21:44:46.674Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:47.939Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:49.756Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:44:51.004Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:44:51.778Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:44:52.554Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:44:53.799Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:44:54.632Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:44:54.632Z] 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.
[2025-02-12T21:44:54.632Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:44:54.632Z] Movies recommended for you:
[2025-02-12T21:44:54.632Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:44:54.632Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:44:54.632Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (9329.160 ms) ======
[2025-02-12T21:44:54.632Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2025-02-12T21:44:54.632Z] GC before operation: completed in 29.856 ms, heap usage 126.054 MB -> 50.652 MB.
[2025-02-12T21:44:56.435Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:44:57.710Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:44:58.974Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:45:00.766Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:45:01.546Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:45:02.336Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:45:03.638Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:45:04.441Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:45:04.441Z] 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.
[2025-02-12T21:45:04.441Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:45:04.441Z] Movies recommended for you:
[2025-02-12T21:45:04.441Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:45:04.441Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:45:04.441Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (9765.250 ms) ======
[2025-02-12T21:45:04.441Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2025-02-12T21:45:04.441Z] GC before operation: completed in 45.741 ms, heap usage 292.656 MB -> 50.912 MB.
[2025-02-12T21:45:06.247Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:45:07.495Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:45:08.750Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:45:10.548Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:45:11.339Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:45:12.160Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:45:12.956Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:45:13.754Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:45:13.754Z] 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.
[2025-02-12T21:45:13.754Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:45:13.754Z] Movies recommended for you:
[2025-02-12T21:45:13.754Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:45:13.754Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:45:13.754Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (9217.699 ms) ======
[2025-02-12T21:45:13.754Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2025-02-12T21:45:13.754Z] GC before operation: completed in 40.166 ms, heap usage 131.964 MB -> 50.894 MB.
[2025-02-12T21:45:15.017Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2025-02-12T21:45:16.813Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2025-02-12T21:45:18.076Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2025-02-12T21:45:19.333Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2025-02-12T21:45:20.126Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2025-02-12T21:45:20.906Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2025-02-12T21:45:21.685Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2025-02-12T21:45:22.473Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2025-02-12T21:45:22.857Z] 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.
[2025-02-12T21:45:22.857Z] The best model improves the baseline by 14.52%.
[2025-02-12T21:45:22.857Z] Movies recommended for you:
[2025-02-12T21:45:22.857Z] WARNING: This benchmark provides no result that can be validated.
[2025-02-12T21:45:22.857Z] There is no way to check that no silent failure occurred.
[2025-02-12T21:45:22.857Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (8930.252 ms) ======
[2025-02-12T21:45:23.238Z] -----------------------------------
[2025-02-12T21:45:23.238Z] renaissance-movie-lens_0_PASSED
[2025-02-12T21:45:23.238Z] -----------------------------------
[2025-02-12T21:45:23.238Z]
[2025-02-12T21:45:23.238Z] TEST TEARDOWN:
[2025-02-12T21:45:23.238Z] Nothing to be done for teardown.
[2025-02-12T21:45:23.238Z] renaissance-movie-lens_0 Finish Time: Wed Feb 12 16:45:22 2025 Epoch Time (ms): 1739396722981