renaissance-movie-lens_0
[2024-09-25T21:05:35.964Z] Running test renaissance-movie-lens_0 ...
[2024-09-25T21:05:35.964Z] ===============================================
[2024-09-25T21:05:35.964Z] renaissance-movie-lens_0 Start Time: Wed Sep 25 14:05:35 2024 Epoch Time (ms): 1727298335544
[2024-09-25T21:05:35.964Z] variation: NoOptions
[2024-09-25T21:05:35.964Z] JVM_OPTIONS:
[2024-09-25T21:05:35.964Z] { \
[2024-09-25T21:05:35.964Z] echo ""; echo "TEST SETUP:"; \
[2024-09-25T21:05:35.964Z] echo "Nothing to be done for setup."; \
[2024-09-25T21:05:35.964Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17272965253443/renaissance-movie-lens_0"; \
[2024-09-25T21:05:35.964Z] cd "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17272965253443/renaissance-movie-lens_0"; \
[2024-09-25T21:05:35.964Z] echo ""; echo "TESTING:"; \
[2024-09-25T21:05:35.964Z] "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17272965253443/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-25T21:05:35.964Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17272965253443/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-25T21:05:35.964Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-25T21:05:35.964Z] echo "Nothing to be done for teardown."; \
[2024-09-25T21:05:35.964Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk17_hs_extended.perf_x86-64_mac_testList_0/aqa-tests/TKG/../TKG/output_17272965253443/TestTargetResult";
[2024-09-25T21:05:35.964Z]
[2024-09-25T21:05:35.964Z] TEST SETUP:
[2024-09-25T21:05:35.964Z] Nothing to be done for setup.
[2024-09-25T21:05:36.413Z]
[2024-09-25T21:05:36.413Z] TESTING:
[2024-09-25T21:05:55.719Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-25T21:06:12.051Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-09-25T21:06:26.251Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-25T21:06:26.251Z] Training: 60056, validation: 20285, test: 19854
[2024-09-25T21:06:26.251Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-25T21:06:26.251Z] GC before operation: completed in 189.411 ms, heap usage 113.802 MB -> 37.674 MB.
[2024-09-25T21:07:04.414Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:07:29.279Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:07:52.913Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:08:11.880Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:08:21.544Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:08:35.072Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:08:45.013Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:08:55.043Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:08:56.313Z] 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.
[2024-09-25T21:08:56.822Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:08:56.822Z] Movies recommended for you:
[2024-09-25T21:08:57.442Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:08:57.442Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:08:57.442Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (150767.051 ms) ======
[2024-09-25T21:08:57.442Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-25T21:08:57.442Z] GC before operation: completed in 273.176 ms, heap usage 224.382 MB -> 53.385 MB.
[2024-09-25T21:09:19.982Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:09:35.287Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:09:53.107Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:10:11.621Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:10:20.896Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:10:30.217Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:10:43.262Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:10:53.136Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:10:53.136Z] 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.
[2024-09-25T21:10:53.885Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:10:53.885Z] Movies recommended for you:
[2024-09-25T21:10:53.885Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:10:53.885Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:10:53.885Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (116355.649 ms) ======
[2024-09-25T21:10:53.885Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-25T21:10:55.603Z] GC before operation: completed in 1169.434 ms, heap usage 328.023 MB -> 50.080 MB.
[2024-09-25T21:11:14.990Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:11:33.151Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:11:55.904Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:12:11.628Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:12:23.527Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:12:35.868Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:12:45.820Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:12:55.571Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:12:57.725Z] 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.
[2024-09-25T21:12:57.725Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:12:58.254Z] Movies recommended for you:
[2024-09-25T21:12:58.254Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:12:58.254Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:12:58.254Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (123116.579 ms) ======
[2024-09-25T21:12:58.254Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-25T21:12:58.254Z] GC before operation: completed in 221.294 ms, heap usage 249.645 MB -> 50.235 MB.
[2024-09-25T21:13:14.144Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:13:33.160Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:13:48.674Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:14:07.438Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:14:15.594Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:14:25.150Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:14:38.713Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:14:43.590Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:14:45.906Z] 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.
[2024-09-25T21:14:45.906Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:14:45.906Z] Movies recommended for you:
[2024-09-25T21:14:45.906Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:14:45.906Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:14:45.906Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (107774.687 ms) ======
[2024-09-25T21:14:45.906Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-25T21:14:46.314Z] GC before operation: completed in 233.984 ms, heap usage 308.426 MB -> 50.725 MB.
[2024-09-25T21:15:02.003Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:15:17.321Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:15:28.461Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:15:41.623Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:15:47.258Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:15:55.061Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:16:04.068Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:16:11.783Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:16:11.783Z] 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.
[2024-09-25T21:16:11.783Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:16:11.783Z] Movies recommended for you:
[2024-09-25T21:16:11.783Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:16:11.783Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:16:11.783Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (85775.754 ms) ======
[2024-09-25T21:16:11.783Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-25T21:16:12.429Z] GC before operation: completed in 204.145 ms, heap usage 616.374 MB -> 54.429 MB.
[2024-09-25T21:16:27.744Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:16:40.428Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:16:53.352Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:17:19.189Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:17:20.991Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:17:28.825Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:17:36.410Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:17:45.846Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:17:47.828Z] 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.
[2024-09-25T21:17:47.828Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:17:48.271Z] Movies recommended for you:
[2024-09-25T21:17:48.271Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:17:48.271Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:17:48.271Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (96008.420 ms) ======
[2024-09-25T21:17:48.271Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-25T21:17:48.688Z] GC before operation: completed in 289.283 ms, heap usage 270.642 MB -> 50.728 MB.
[2024-09-25T21:18:04.788Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:18:24.908Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:18:43.646Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:19:06.000Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:19:10.041Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:19:21.621Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:19:32.809Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:19:42.543Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:19:44.975Z] 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.
[2024-09-25T21:19:44.975Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:19:45.408Z] Movies recommended for you:
[2024-09-25T21:19:45.408Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:19:45.408Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:19:45.408Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (116960.749 ms) ======
[2024-09-25T21:19:45.408Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-25T21:19:45.804Z] GC before operation: completed in 212.969 ms, heap usage 349.193 MB -> 50.999 MB.
[2024-09-25T21:20:04.808Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:20:20.628Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:20:39.228Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:20:55.270Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:21:04.567Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:21:12.285Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:21:23.322Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:21:34.466Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:21:34.466Z] 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.
[2024-09-25T21:21:34.466Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:21:34.466Z] Movies recommended for you:
[2024-09-25T21:21:34.466Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:21:34.466Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:21:34.466Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (108760.639 ms) ======
[2024-09-25T21:21:34.466Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-25T21:21:34.466Z] GC before operation: completed in 203.853 ms, heap usage 266.192 MB -> 51.162 MB.
[2024-09-25T21:21:53.195Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:22:12.146Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:22:31.668Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:22:46.605Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:22:56.790Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:23:08.451Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:23:17.770Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:23:27.288Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:23:27.893Z] 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.
[2024-09-25T21:23:28.405Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:23:28.405Z] Movies recommended for you:
[2024-09-25T21:23:28.405Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:23:28.405Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:23:28.405Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (113738.773 ms) ======
[2024-09-25T21:23:28.405Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-25T21:23:28.893Z] GC before operation: completed in 272.043 ms, heap usage 198.073 MB -> 50.956 MB.
[2024-09-25T21:23:48.049Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:24:06.808Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:24:25.175Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:24:44.173Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:24:55.034Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:25:05.800Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:25:15.498Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:25:23.471Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:25:24.536Z] 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.
[2024-09-25T21:25:24.536Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:25:24.536Z] Movies recommended for you:
[2024-09-25T21:25:24.536Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:25:24.536Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:25:24.536Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (115903.326 ms) ======
[2024-09-25T21:25:24.536Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-25T21:25:24.536Z] GC before operation: completed in 93.972 ms, heap usage 71.991 MB -> 53.978 MB.
[2024-09-25T21:25:47.707Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:26:04.402Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:26:18.417Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:26:32.434Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:26:39.938Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:26:47.899Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:26:55.355Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:27:04.498Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:27:05.120Z] 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.
[2024-09-25T21:27:05.121Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:27:05.121Z] Movies recommended for you:
[2024-09-25T21:27:05.121Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:27:05.121Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:27:05.121Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (100590.526 ms) ======
[2024-09-25T21:27:05.121Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-25T21:27:05.573Z] GC before operation: completed in 186.994 ms, heap usage 438.497 MB -> 54.180 MB.
[2024-09-25T21:27:24.262Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:27:33.200Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:27:44.442Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:27:55.652Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:28:03.435Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:28:08.300Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:28:15.545Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:28:20.767Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:28:21.210Z] 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.
[2024-09-25T21:28:21.210Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:28:21.210Z] Movies recommended for you:
[2024-09-25T21:28:21.210Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:28:21.210Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:28:21.210Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (75945.112 ms) ======
[2024-09-25T21:28:21.210Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-25T21:28:21.712Z] GC before operation: completed in 173.076 ms, heap usage 81.435 MB -> 54.381 MB.
[2024-09-25T21:28:37.766Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:28:45.361Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:29:01.734Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:29:10.697Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:29:17.842Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:29:25.450Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:29:39.144Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:29:52.414Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:29:52.414Z] 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.
[2024-09-25T21:29:52.414Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:29:52.881Z] Movies recommended for you:
[2024-09-25T21:29:52.881Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:29:52.881Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:29:52.881Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (91170.528 ms) ======
[2024-09-25T21:29:52.881Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-25T21:29:52.881Z] GC before operation: completed in 271.914 ms, heap usage 402.771 MB -> 54.530 MB.
[2024-09-25T21:30:11.938Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:30:27.886Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:30:46.745Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:30:59.758Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:31:13.146Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:31:23.335Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:31:33.301Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:31:41.994Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:31:42.655Z] 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.
[2024-09-25T21:31:42.655Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:31:43.245Z] Movies recommended for you:
[2024-09-25T21:31:43.245Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:31:43.245Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:31:43.245Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (110084.725 ms) ======
[2024-09-25T21:31:43.245Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-25T21:31:43.245Z] GC before operation: completed in 238.094 ms, heap usage 256.569 MB -> 50.926 MB.
[2024-09-25T21:32:01.622Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:32:17.782Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:32:36.438Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:32:53.084Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:33:04.313Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:33:13.090Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:33:22.384Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:33:35.653Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:33:35.653Z] 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.
[2024-09-25T21:33:35.653Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:33:35.653Z] Movies recommended for you:
[2024-09-25T21:33:35.653Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:33:35.653Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:33:35.653Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (111348.728 ms) ======
[2024-09-25T21:33:35.653Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-25T21:33:35.653Z] GC before operation: completed in 225.481 ms, heap usage 80.856 MB -> 54.472 MB.
[2024-09-25T21:33:50.931Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:34:04.294Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:34:20.115Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:34:33.220Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:34:39.855Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:34:47.284Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:34:56.749Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:35:06.316Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:35:08.367Z] 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.
[2024-09-25T21:35:08.367Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:35:08.781Z] Movies recommended for you:
[2024-09-25T21:35:08.781Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:35:08.781Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:35:08.781Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (93727.996 ms) ======
[2024-09-25T21:35:08.781Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-25T21:35:08.781Z] GC before operation: completed in 177.542 ms, heap usage 337.871 MB -> 51.300 MB.
[2024-09-25T21:35:27.421Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:35:43.330Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:35:57.107Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:36:16.007Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:36:20.876Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:36:27.574Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:36:34.053Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:36:41.973Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:36:43.265Z] 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.
[2024-09-25T21:36:43.693Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:36:43.693Z] Movies recommended for you:
[2024-09-25T21:36:43.693Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:36:43.693Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:36:43.693Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (94971.291 ms) ======
[2024-09-25T21:36:43.693Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-25T21:36:44.157Z] GC before operation: completed in 214.076 ms, heap usage 123.713 MB -> 53.197 MB.
[2024-09-25T21:37:03.366Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:37:19.015Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:37:34.814Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:37:54.221Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:38:03.181Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:38:10.206Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:38:19.652Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:38:25.633Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:38:26.031Z] 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.
[2024-09-25T21:38:26.031Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:38:26.449Z] Movies recommended for you:
[2024-09-25T21:38:26.449Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:38:26.449Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:38:26.449Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (102358.491 ms) ======
[2024-09-25T21:38:26.449Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-25T21:38:26.449Z] GC before operation: completed in 206.301 ms, heap usage 316.572 MB -> 51.191 MB.
[2024-09-25T21:38:42.847Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:38:54.067Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:39:05.252Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:39:16.170Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:39:23.882Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:39:30.143Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:39:37.620Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:39:43.715Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:39:44.162Z] 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.
[2024-09-25T21:39:44.162Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:39:44.162Z] Movies recommended for you:
[2024-09-25T21:39:44.162Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:39:44.163Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:39:44.163Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (77745.132 ms) ======
[2024-09-25T21:39:44.163Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-25T21:39:44.649Z] GC before operation: completed in 221.976 ms, heap usage 345.576 MB -> 51.384 MB.
[2024-09-25T21:39:55.947Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-25T21:40:14.834Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-25T21:40:33.627Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-25T21:40:47.407Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-25T21:40:57.770Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-25T21:41:06.771Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-25T21:41:15.902Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-25T21:41:24.101Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-25T21:41:26.441Z] 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.
[2024-09-25T21:41:26.441Z] The best model improves the baseline by 14.52%.
[2024-09-25T21:41:26.441Z] Movies recommended for you:
[2024-09-25T21:41:26.441Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-25T21:41:26.441Z] There is no way to check that no silent failure occurred.
[2024-09-25T21:41:26.441Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (102069.055 ms) ======
[2024-09-25T21:41:29.686Z] -----------------------------------
[2024-09-25T21:41:29.686Z] renaissance-movie-lens_0_PASSED
[2024-09-25T21:41:29.686Z] -----------------------------------
[2024-09-25T21:41:29.686Z]
[2024-09-25T21:41:29.686Z] TEST TEARDOWN:
[2024-09-25T21:41:29.686Z] Nothing to be done for teardown.
[2024-09-25T21:41:29.686Z] renaissance-movie-lens_0 Finish Time: Wed Sep 25 14:41:29 2024 Epoch Time (ms): 1727300489171