renaissance-movie-lens_0
[2024-11-27T22:13:42.654Z] Running test renaissance-movie-lens_0 ...
[2024-11-27T22:13:42.654Z] ===============================================
[2024-11-27T22:13:42.654Z] renaissance-movie-lens_0 Start Time: Wed Nov 27 17:13:42 2024 Epoch Time (ms): 1732745622112
[2024-11-27T22:13:42.654Z] variation: NoOptions
[2024-11-27T22:13:42.654Z] JVM_OPTIONS:
[2024-11-27T22:13:42.654Z] { \
[2024-11-27T22:13:42.654Z] echo ""; echo "TEST SETUP:"; \
[2024-11-27T22:13:42.654Z] echo "Nothing to be done for setup."; \
[2024-11-27T22:13:42.654Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17327452733710/renaissance-movie-lens_0"; \
[2024-11-27T22:13:42.655Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17327452733710/renaissance-movie-lens_0"; \
[2024-11-27T22:13:42.655Z] echo ""; echo "TESTING:"; \
[2024-11-27T22:13:42.655Z] "/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_17327452733710/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-27T22:13:42.655Z] 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_17327452733710/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-27T22:13:42.655Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-27T22:13:42.655Z] echo "Nothing to be done for teardown."; \
[2024-11-27T22:13:42.655Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17327452733710/TestTargetResult";
[2024-11-27T22:13:42.655Z]
[2024-11-27T22:13:42.655Z] TEST SETUP:
[2024-11-27T22:13:42.655Z] Nothing to be done for setup.
[2024-11-27T22:13:42.655Z]
[2024-11-27T22:13:42.655Z] TESTING:
[2024-11-27T22:13:44.512Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-27T22:13:46.345Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-11-27T22:13:48.193Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-27T22:13:48.193Z] Training: 60056, validation: 20285, test: 19854
[2024-11-27T22:13:48.193Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-27T22:13:48.193Z] GC before operation: completed in 41.649 ms, heap usage 159.302 MB -> 37.291 MB.
[2024-11-27T22:13:52.341Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:13:54.177Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:13:56.060Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:13:57.377Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:13:58.196Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:13:59.003Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:13:59.825Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:00.647Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:00.647Z] 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.
[2024-11-27T22:14:00.647Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:00.647Z] Movies recommended for you:
[2024-11-27T22:14:00.647Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:00.647Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:00.647Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (12402.597 ms) ======
[2024-11-27T22:14:00.647Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-27T22:14:00.647Z] GC before operation: completed in 42.675 ms, heap usage 359.833 MB -> 53.402 MB.
[2024-11-27T22:14:01.972Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:03.277Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:04.169Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:05.484Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:06.272Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:07.065Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:07.913Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:08.727Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:09.102Z] 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.
[2024-11-27T22:14:09.103Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:09.103Z] Movies recommended for you:
[2024-11-27T22:14:09.103Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:09.103Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:09.103Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (8415.247 ms) ======
[2024-11-27T22:14:09.103Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-27T22:14:09.103Z] GC before operation: completed in 37.838 ms, heap usage 271.014 MB -> 50.862 MB.
[2024-11-27T22:14:10.388Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:11.680Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:12.980Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:14.264Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:15.053Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:16.336Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:16.725Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:18.048Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:18.048Z] 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.
[2024-11-27T22:14:18.048Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:18.048Z] Movies recommended for you:
[2024-11-27T22:14:18.048Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:18.048Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:18.048Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (8901.655 ms) ======
[2024-11-27T22:14:18.048Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-27T22:14:18.048Z] GC before operation: completed in 41.145 ms, heap usage 252.688 MB -> 49.915 MB.
[2024-11-27T22:14:19.349Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:20.642Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:21.944Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:32.688Z] 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.
[2024-11-27T22:14:32.688Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:32.688Z] Movies recommended for you:
[2024-11-27T22:14:32.688Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:32.688Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:32.688Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (8597.947 ms) ======
[2024-11-27T22:14:32.688Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-27T22:14:32.688Z] GC before operation: completed in 34.414 ms, heap usage 238.614 MB -> 50.190 MB.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:32.688Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:33.056Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:33.423Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:34.241Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:34.241Z] 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.
[2024-11-27T22:14:34.241Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:34.612Z] Movies recommended for you:
[2024-11-27T22:14:34.612Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:34.612Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:34.612Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (7732.349 ms) ======
[2024-11-27T22:14:34.612Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-27T22:14:34.612Z] GC before operation: completed in 29.085 ms, heap usage 168.179 MB -> 50.472 MB.
[2024-11-27T22:14:35.899Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:37.746Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:39.019Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:40.341Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:41.130Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:41.949Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:42.741Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:43.545Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:43.545Z] 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.
[2024-11-27T22:14:43.545Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:43.545Z] Movies recommended for you:
[2024-11-27T22:14:43.545Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:43.545Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:43.545Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (9157.190 ms) ======
[2024-11-27T22:14:43.545Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-27T22:14:43.545Z] GC before operation: completed in 51.350 ms, heap usage 297.088 MB -> 52.689 MB.
[2024-11-27T22:14:44.849Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:46.131Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:47.414Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:48.692Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:49.068Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:49.864Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:50.668Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:51.123Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:51.491Z] 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.
[2024-11-27T22:14:51.491Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:51.491Z] Movies recommended for you:
[2024-11-27T22:14:51.491Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:51.491Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:51.491Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (7694.402 ms) ======
[2024-11-27T22:14:51.491Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-27T22:14:51.491Z] GC before operation: completed in 33.523 ms, heap usage 356.440 MB -> 50.779 MB.
[2024-11-27T22:14:52.776Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:14:53.581Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:14:54.980Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:14:56.280Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:14:56.651Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:14:57.446Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:14:58.243Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:14:59.074Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:14:59.074Z] 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.
[2024-11-27T22:14:59.074Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:14:59.443Z] Movies recommended for you:
[2024-11-27T22:14:59.443Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:14:59.443Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:14:59.443Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (7865.563 ms) ======
[2024-11-27T22:14:59.443Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-27T22:14:59.443Z] GC before operation: completed in 42.363 ms, heap usage 377.630 MB -> 54.180 MB.
[2024-11-27T22:15:00.822Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:01.633Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:02.926Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:04.223Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:04.600Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:05.413Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:06.213Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:07.008Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:07.008Z] 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.
[2024-11-27T22:15:07.008Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:07.008Z] Movies recommended for you:
[2024-11-27T22:15:07.008Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:07.008Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:07.008Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (7756.525 ms) ======
[2024-11-27T22:15:07.008Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-27T22:15:07.008Z] GC before operation: completed in 36.609 ms, heap usage 257.106 MB -> 52.956 MB.
[2024-11-27T22:15:08.308Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:09.596Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:10.877Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:11.679Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:12.472Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:13.277Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:13.654Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:14.462Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:14.462Z] 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.
[2024-11-27T22:15:14.462Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:14.837Z] Movies recommended for you:
[2024-11-27T22:15:14.837Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:14.837Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:14.837Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (7583.400 ms) ======
[2024-11-27T22:15:14.837Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-27T22:15:14.837Z] GC before operation: completed in 33.175 ms, heap usage 344.748 MB -> 50.999 MB.
[2024-11-27T22:15:15.637Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:16.926Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:18.210Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:19.492Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:19.867Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:20.691Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:21.521Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:21.920Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:22.302Z] 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.
[2024-11-27T22:15:22.302Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:22.302Z] Movies recommended for you:
[2024-11-27T22:15:22.302Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:22.302Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:22.302Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (7527.252 ms) ======
[2024-11-27T22:15:22.302Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-27T22:15:22.302Z] GC before operation: completed in 37.018 ms, heap usage 232.551 MB -> 50.541 MB.
[2024-11-27T22:15:23.595Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:24.882Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:26.162Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:26.957Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:27.754Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:28.564Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:29.377Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:30.168Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:30.168Z] 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.
[2024-11-27T22:15:30.168Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:30.168Z] Movies recommended for you:
[2024-11-27T22:15:30.168Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:30.168Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:30.168Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (7892.391 ms) ======
[2024-11-27T22:15:30.168Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-27T22:15:30.168Z] GC before operation: completed in 33.703 ms, heap usage 304.517 MB -> 50.769 MB.
[2024-11-27T22:15:31.446Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:32.722Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:34.002Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:35.269Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:36.087Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:36.456Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:37.259Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:38.060Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:38.060Z] 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.
[2024-11-27T22:15:38.060Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:38.060Z] Movies recommended for you:
[2024-11-27T22:15:38.060Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:38.060Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:38.060Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (7769.331 ms) ======
[2024-11-27T22:15:38.060Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-27T22:15:38.060Z] GC before operation: completed in 38.953 ms, heap usage 326.643 MB -> 50.896 MB.
[2024-11-27T22:15:39.352Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:40.144Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:41.424Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:42.702Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:43.081Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:43.875Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:44.676Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:45.047Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:45.416Z] 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.
[2024-11-27T22:15:45.416Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:45.416Z] Movies recommended for you:
[2024-11-27T22:15:45.416Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:45.416Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:45.416Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (7327.992 ms) ======
[2024-11-27T22:15:45.416Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-27T22:15:45.416Z] GC before operation: completed in 34.611 ms, heap usage 290.849 MB -> 50.791 MB.
[2024-11-27T22:15:46.736Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:47.531Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:48.847Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:50.126Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:50.926Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:51.314Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:52.111Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:15:52.905Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:15:52.905Z] 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.
[2024-11-27T22:15:52.905Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:15:52.905Z] Movies recommended for you:
[2024-11-27T22:15:52.905Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:15:52.905Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:15:52.905Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (7653.942 ms) ======
[2024-11-27T22:15:52.905Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-27T22:15:52.905Z] GC before operation: completed in 34.030 ms, heap usage 63.409 MB -> 53.494 MB.
[2024-11-27T22:15:54.195Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:15:55.461Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:15:56.273Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:15:57.557Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:15:58.355Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:15:59.146Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:15:59.529Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:16:00.335Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:16:00.336Z] 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.
[2024-11-27T22:16:00.336Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:16:00.336Z] Movies recommended for you:
[2024-11-27T22:16:00.336Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:16:00.336Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:16:00.336Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (7381.988 ms) ======
[2024-11-27T22:16:00.336Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-27T22:16:00.336Z] GC before operation: completed in 31.146 ms, heap usage 204.186 MB -> 50.869 MB.
[2024-11-27T22:16:01.642Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:16:02.962Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:16:04.353Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:16:05.141Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:16:05.940Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:16:06.730Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:16:07.516Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:16:08.310Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:16:08.310Z] 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.
[2024-11-27T22:16:08.310Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:16:08.310Z] Movies recommended for you:
[2024-11-27T22:16:08.310Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:16:08.310Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:16:08.310Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (7777.131 ms) ======
[2024-11-27T22:16:08.310Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-27T22:16:08.310Z] GC before operation: completed in 34.348 ms, heap usage 377.751 MB -> 53.992 MB.
[2024-11-27T22:16:09.602Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:16:10.399Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:16:11.682Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:16:12.951Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:16:13.735Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:16:14.537Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:16:15.359Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:16:16.173Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:16:16.173Z] 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.
[2024-11-27T22:16:16.173Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:16:16.173Z] Movies recommended for you:
[2024-11-27T22:16:16.173Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:16:16.173Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:16:16.173Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (7882.281 ms) ======
[2024-11-27T22:16:16.173Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-27T22:16:16.173Z] GC before operation: completed in 33.492 ms, heap usage 380.636 MB -> 54.089 MB.
[2024-11-27T22:16:17.446Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:16:18.743Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:16:19.531Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:16:20.811Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:16:21.675Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:16:22.066Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:16:22.855Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:16:23.667Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:16:23.667Z] 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.
[2024-11-27T22:16:23.667Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:16:23.667Z] Movies recommended for you:
[2024-11-27T22:16:23.667Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:16:23.667Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:16:23.667Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (7573.866 ms) ======
[2024-11-27T22:16:23.667Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-27T22:16:23.667Z] GC before operation: completed in 32.856 ms, heap usage 192.152 MB -> 51.033 MB.
[2024-11-27T22:16:24.948Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-27T22:16:26.227Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-27T22:16:27.045Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-27T22:16:28.342Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-27T22:16:29.133Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-27T22:16:29.929Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-27T22:16:30.732Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-27T22:16:31.121Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-27T22:16:31.494Z] 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.
[2024-11-27T22:16:31.494Z] The best model improves the baseline by 14.52%.
[2024-11-27T22:16:31.494Z] Movies recommended for you:
[2024-11-27T22:16:31.494Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-27T22:16:31.494Z] There is no way to check that no silent failure occurred.
[2024-11-27T22:16:31.494Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (7594.212 ms) ======
[2024-11-27T22:16:31.494Z] -----------------------------------
[2024-11-27T22:16:31.494Z] renaissance-movie-lens_0_PASSED
[2024-11-27T22:16:31.494Z] -----------------------------------
[2024-11-27T22:16:31.494Z]
[2024-11-27T22:16:31.494Z] TEST TEARDOWN:
[2024-11-27T22:16:31.494Z] Nothing to be done for teardown.
[2024-11-27T22:16:31.863Z] renaissance-movie-lens_0 Finish Time: Wed Nov 27 17:16:31 2024 Epoch Time (ms): 1732745791462