renaissance-movie-lens_0
[2024-08-23T21:01:19.886Z] Running test renaissance-movie-lens_0 ...
[2024-08-23T21:01:19.886Z] ===============================================
[2024-08-23T21:01:19.886Z] renaissance-movie-lens_0 Start Time: Fri Aug 23 17:01:19 2024 Epoch Time (ms): 1724446879484
[2024-08-23T21:01:19.886Z] variation: NoOptions
[2024-08-23T21:01:19.886Z] JVM_OPTIONS:
[2024-08-23T21:01:19.886Z] { \
[2024-08-23T21:01:19.886Z] echo ""; echo "TEST SETUP:"; \
[2024-08-23T21:01:19.886Z] echo "Nothing to be done for setup."; \
[2024-08-23T21:01:19.886Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17244464473992/renaissance-movie-lens_0"; \
[2024-08-23T21:01:19.886Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17244464473992/renaissance-movie-lens_0"; \
[2024-08-23T21:01:19.886Z] echo ""; echo "TESTING:"; \
[2024-08-23T21:01:19.886Z] "/Users/admin/workspace/workspace/Test_openjdk11_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_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17244464473992/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-23T21:01:19.886Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17244464473992/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-23T21:01:19.886Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-23T21:01:19.886Z] echo "Nothing to be done for teardown."; \
[2024-08-23T21:01:19.886Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17244464473992/TestTargetResult";
[2024-08-23T21:01:19.886Z]
[2024-08-23T21:01:19.886Z] TEST SETUP:
[2024-08-23T21:01:19.886Z] Nothing to be done for setup.
[2024-08-23T21:01:19.886Z]
[2024-08-23T21:01:19.886Z] TESTING:
[2024-08-23T21:01:21.755Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-23T21:01:23.000Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-23T21:01:24.849Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-23T21:01:25.222Z] Training: 60056, validation: 20285, test: 19854
[2024-08-23T21:01:25.222Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-23T21:01:25.222Z] GC before operation: completed in 49.862 ms, heap usage 72.588 MB -> 36.579 MB.
[2024-08-23T21:01:29.347Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:31.169Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:33.632Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:01:34.900Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:01:36.154Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:01:37.455Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:01:38.240Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:01:39.549Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:01:39.549Z] 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.
[2024-08-23T21:01:39.549Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:01:39.549Z] Movies recommended for you:
[2024-08-23T21:01:39.549Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:01:39.549Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:01:39.549Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (14524.038 ms) ======
[2024-08-23T21:01:39.549Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-23T21:01:39.549Z] GC before operation: completed in 70.170 ms, heap usage 249.712 MB -> 49.328 MB.
[2024-08-23T21:01:41.355Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:43.139Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:44.938Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:01:46.808Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:01:47.577Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:01:48.354Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:01:49.610Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:01:50.391Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:01:50.391Z] 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.
[2024-08-23T21:01:50.391Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:01:50.391Z] Movies recommended for you:
[2024-08-23T21:01:50.391Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:01:50.391Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:01:50.391Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (10818.668 ms) ======
[2024-08-23T21:01:50.391Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-23T21:01:50.391Z] GC before operation: completed in 49.603 ms, heap usage 65.066 MB -> 49.041 MB.
[2024-08-23T21:01:52.193Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:01:54.020Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:01:55.828Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:01:57.630Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:01:58.415Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:01:59.672Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:00.451Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:01.716Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:01.716Z] 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.
[2024-08-23T21:02:01.716Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:01.716Z] Movies recommended for you:
[2024-08-23T21:02:01.716Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:01.716Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:01.716Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (11249.550 ms) ======
[2024-08-23T21:02:01.716Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-23T21:02:01.716Z] GC before operation: completed in 59.491 ms, heap usage 136.402 MB -> 49.147 MB.
[2024-08-23T21:02:03.526Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:05.322Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:07.161Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:08.484Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:09.268Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:10.516Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:11.286Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:12.545Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:12.545Z] 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.
[2024-08-23T21:02:12.545Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:12.545Z] Movies recommended for you:
[2024-08-23T21:02:12.545Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:12.545Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:12.545Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (10650.015 ms) ======
[2024-08-23T21:02:12.545Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-23T21:02:12.545Z] GC before operation: completed in 59.491 ms, heap usage 251.610 MB -> 49.606 MB.
[2024-08-23T21:02:14.328Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:16.139Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:18.041Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:19.288Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:20.534Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:21.340Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:22.114Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:23.356Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:23.356Z] 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.
[2024-08-23T21:02:23.356Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:23.356Z] Movies recommended for you:
[2024-08-23T21:02:23.356Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:23.356Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:23.356Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (10845.605 ms) ======
[2024-08-23T21:02:23.356Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-23T21:02:23.356Z] GC before operation: completed in 54.605 ms, heap usage 161.127 MB -> 49.743 MB.
[2024-08-23T21:02:25.138Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:26.398Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:28.183Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:29.965Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:30.750Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:31.527Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:32.816Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:33.610Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:33.610Z] 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.
[2024-08-23T21:02:33.965Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:33.965Z] Movies recommended for you:
[2024-08-23T21:02:33.965Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:33.965Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:33.965Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (10377.818 ms) ======
[2024-08-23T21:02:33.965Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-23T21:02:33.965Z] GC before operation: completed in 63.238 ms, heap usage 297.532 MB -> 49.810 MB.
[2024-08-23T21:02:35.770Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:37.006Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:38.788Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:40.593Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:41.381Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:42.157Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:42.933Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:44.203Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:44.203Z] 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.
[2024-08-23T21:02:44.203Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:44.203Z] Movies recommended for you:
[2024-08-23T21:02:44.203Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:44.203Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:44.203Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (10222.405 ms) ======
[2024-08-23T21:02:44.203Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-23T21:02:44.203Z] GC before operation: completed in 49.365 ms, heap usage 64.697 MB -> 49.850 MB.
[2024-08-23T21:02:46.003Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:47.259Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:48.553Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:02:50.338Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:02:51.120Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:02:52.353Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:02:53.130Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:02:53.917Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:02:54.273Z] 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.
[2024-08-23T21:02:54.273Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:02:54.273Z] Movies recommended for you:
[2024-08-23T21:02:54.273Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:02:54.273Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:02:54.273Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9985.093 ms) ======
[2024-08-23T21:02:54.273Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-23T21:02:54.273Z] GC before operation: completed in 50.170 ms, heap usage 198.158 MB -> 50.131 MB.
[2024-08-23T21:02:56.152Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:02:57.394Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:02:59.185Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:00.989Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:01.776Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:03.043Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:03.848Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:04.619Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:04.619Z] 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.
[2024-08-23T21:03:04.619Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:04.978Z] Movies recommended for you:
[2024-08-23T21:03:04.978Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:04.978Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:04.978Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (10601.890 ms) ======
[2024-08-23T21:03:04.978Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-23T21:03:04.978Z] GC before operation: completed in 56.340 ms, heap usage 97.959 MB -> 49.890 MB.
[2024-08-23T21:03:06.779Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:08.042Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:10.019Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:11.269Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:12.512Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:13.289Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:14.557Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:15.329Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:15.329Z] 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.
[2024-08-23T21:03:15.329Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:15.329Z] Movies recommended for you:
[2024-08-23T21:03:15.329Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:15.329Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:15.329Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (10474.957 ms) ======
[2024-08-23T21:03:15.329Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-23T21:03:15.329Z] GC before operation: completed in 51.553 ms, heap usage 206.789 MB -> 50.070 MB.
[2024-08-23T21:03:17.128Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:18.385Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:20.191Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:21.450Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:22.240Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:22.624Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:23.902Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:24.260Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:24.623Z] 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.
[2024-08-23T21:03:24.623Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:24.623Z] Movies recommended for you:
[2024-08-23T21:03:24.623Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:24.623Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:24.623Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (9161.920 ms) ======
[2024-08-23T21:03:24.623Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-23T21:03:24.623Z] GC before operation: completed in 53.716 ms, heap usage 121.090 MB -> 49.735 MB.
[2024-08-23T21:03:26.451Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:27.715Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:29.516Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:30.785Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:31.557Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:32.330Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:33.098Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:34.386Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:34.386Z] 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.
[2024-08-23T21:03:34.386Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:34.386Z] Movies recommended for you:
[2024-08-23T21:03:34.386Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:34.386Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:34.386Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (9720.292 ms) ======
[2024-08-23T21:03:34.386Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-23T21:03:34.386Z] GC before operation: completed in 51.315 ms, heap usage 62.899 MB -> 50.058 MB.
[2024-08-23T21:03:36.199Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:37.467Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:39.262Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:40.529Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:41.308Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:42.575Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:43.349Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:44.135Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:44.498Z] 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.
[2024-08-23T21:03:44.498Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:44.498Z] Movies recommended for you:
[2024-08-23T21:03:44.498Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:44.498Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:44.498Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (10054.575 ms) ======
[2024-08-23T21:03:44.498Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-23T21:03:44.498Z] GC before operation: completed in 52.520 ms, heap usage 281.294 MB -> 50.265 MB.
[2024-08-23T21:03:46.294Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:48.108Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:49.342Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:03:51.128Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:03:51.900Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:03:52.665Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:03:53.444Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:03:54.328Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:03:54.692Z] 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.
[2024-08-23T21:03:54.692Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:03:54.692Z] Movies recommended for you:
[2024-08-23T21:03:54.692Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:03:54.692Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:03:54.692Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (10177.892 ms) ======
[2024-08-23T21:03:54.692Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-23T21:03:54.692Z] GC before operation: completed in 57.324 ms, heap usage 133.279 MB -> 49.836 MB.
[2024-08-23T21:03:56.471Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:03:57.708Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:03:59.526Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:00.921Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:01.283Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:02.558Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:03.348Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:04.142Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:04.142Z] 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.
[2024-08-23T21:04:04.510Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:04.510Z] Movies recommended for you:
[2024-08-23T21:04:04.510Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:04.510Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:04.510Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (9629.037 ms) ======
[2024-08-23T21:04:04.510Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-23T21:04:04.510Z] GC before operation: completed in 54.133 ms, heap usage 297.087 MB -> 50.212 MB.
[2024-08-23T21:04:05.753Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:07.550Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:09.409Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:10.655Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:11.438Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:12.215Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:13.464Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:14.290Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:14.290Z] 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.
[2024-08-23T21:04:14.290Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:14.290Z] Movies recommended for you:
[2024-08-23T21:04:14.290Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:14.290Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:14.290Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (9865.430 ms) ======
[2024-08-23T21:04:14.290Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-23T21:04:14.290Z] GC before operation: completed in 48.498 ms, heap usage 71.561 MB -> 50.003 MB.
[2024-08-23T21:04:16.094Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:17.349Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:19.131Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:20.386Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:21.169Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:22.440Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:23.239Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:24.026Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:24.026Z] 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.
[2024-08-23T21:04:24.027Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:24.027Z] Movies recommended for you:
[2024-08-23T21:04:24.027Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:24.027Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:24.027Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (9790.663 ms) ======
[2024-08-23T21:04:24.027Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-23T21:04:24.027Z] GC before operation: completed in 58.019 ms, heap usage 117.054 MB -> 49.914 MB.
[2024-08-23T21:04:25.816Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:27.604Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:28.848Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:30.644Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:31.412Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:32.178Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:32.956Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:33.745Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:34.113Z] 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.
[2024-08-23T21:04:34.113Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:34.113Z] Movies recommended for you:
[2024-08-23T21:04:34.113Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:34.113Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:34.113Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (9825.643 ms) ======
[2024-08-23T21:04:34.113Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-23T21:04:34.113Z] GC before operation: completed in 50.784 ms, heap usage 293.293 MB -> 50.182 MB.
[2024-08-23T21:04:35.940Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:37.180Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:38.968Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:40.208Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:40.979Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:42.244Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:43.022Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:43.811Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:43.811Z] 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.
[2024-08-23T21:04:43.811Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:43.811Z] Movies recommended for you:
[2024-08-23T21:04:43.811Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:43.811Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:43.811Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (9903.493 ms) ======
[2024-08-23T21:04:43.811Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-23T21:04:44.176Z] GC before operation: completed in 57.702 ms, heap usage 159.902 MB -> 50.233 MB.
[2024-08-23T21:04:45.417Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-23T21:04:47.205Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-23T21:04:48.460Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-23T21:04:50.242Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-23T21:04:51.022Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-23T21:04:51.898Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-23T21:04:52.685Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-23T21:04:53.518Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-23T21:04:53.875Z] 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.
[2024-08-23T21:04:53.875Z] The best model improves the baseline by 14.52%.
[2024-08-23T21:04:53.875Z] Movies recommended for you:
[2024-08-23T21:04:53.875Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-23T21:04:53.875Z] There is no way to check that no silent failure occurred.
[2024-08-23T21:04:53.875Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9827.214 ms) ======
[2024-08-23T21:04:54.235Z] -----------------------------------
[2024-08-23T21:04:54.235Z] renaissance-movie-lens_0_PASSED
[2024-08-23T21:04:54.235Z] -----------------------------------
[2024-08-23T21:04:54.235Z]
[2024-08-23T21:04:54.235Z] TEST TEARDOWN:
[2024-08-23T21:04:54.235Z] Nothing to be done for teardown.
[2024-08-23T21:04:54.235Z] renaissance-movie-lens_0 Finish Time: Fri Aug 23 17:04:53 2024 Epoch Time (ms): 1724447093832