renaissance-movie-lens_0
[2024-10-02T21:08:22.128Z] Running test renaissance-movie-lens_0 ...
[2024-10-02T21:08:22.128Z] ===============================================
[2024-10-02T21:08:22.128Z] renaissance-movie-lens_0 Start Time: Wed Oct 2 17:08:21 2024 Epoch Time (ms): 1727903301681
[2024-10-02T21:08:22.128Z] variation: NoOptions
[2024-10-02T21:08:22.128Z] JVM_OPTIONS:
[2024-10-02T21:08:22.128Z] { \
[2024-10-02T21:08:22.128Z] echo ""; echo "TEST SETUP:"; \
[2024-10-02T21:08:22.128Z] echo "Nothing to be done for setup."; \
[2024-10-02T21:08:22.128Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17279028409517/renaissance-movie-lens_0"; \
[2024-10-02T21:08:22.128Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17279028409517/renaissance-movie-lens_0"; \
[2024-10-02T21:08:22.128Z] echo ""; echo "TESTING:"; \
[2024-10-02T21:08:22.128Z] "/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_17279028409517/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-10-02T21:08:22.128Z] 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_17279028409517/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-10-02T21:08:22.128Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-10-02T21:08:22.128Z] echo "Nothing to be done for teardown."; \
[2024-10-02T21:08:22.128Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17279028409517/TestTargetResult";
[2024-10-02T21:08:22.128Z]
[2024-10-02T21:08:22.128Z] TEST SETUP:
[2024-10-02T21:08:22.128Z] Nothing to be done for setup.
[2024-10-02T21:08:22.128Z]
[2024-10-02T21:08:22.128Z] TESTING:
[2024-10-02T21:08:24.518Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-10-02T21:08:25.308Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-10-02T21:08:27.716Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-10-02T21:08:27.716Z] Training: 60056, validation: 20285, test: 19854
[2024-10-02T21:08:27.716Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-10-02T21:08:27.716Z] GC before operation: completed in 45.324 ms, heap usage 79.641 MB -> 36.580 MB.
[2024-10-02T21:08:31.732Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:08:33.513Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:08:35.308Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:08:37.098Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:08:38.328Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:08:39.095Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:08:40.319Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:08:41.567Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:08:41.567Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:08:41.567Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:08:41.567Z] Movies recommended for you:
[2024-10-02T21:08:41.567Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:08:41.567Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:08:41.567Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (14131.223 ms) ======
[2024-10-02T21:08:41.567Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-10-02T21:08:41.918Z] GC before operation: completed in 64.980 ms, heap usage 77.260 MB -> 47.944 MB.
[2024-10-02T21:08:43.717Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:08:45.488Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:08:47.255Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:08:48.477Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:08:49.703Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:08:50.462Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:08:51.698Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:08:52.922Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:08:52.922Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:08:52.922Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:08:52.922Z] Movies recommended for you:
[2024-10-02T21:08:52.922Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:08:52.922Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:08:52.922Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (11134.945 ms) ======
[2024-10-02T21:08:52.922Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-10-02T21:08:52.922Z] GC before operation: completed in 49.436 ms, heap usage 235.017 MB -> 48.966 MB.
[2024-10-02T21:08:54.695Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:08:56.471Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:08:58.358Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:08:59.599Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:09:00.840Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:09:02.129Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:09:02.905Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:09:04.140Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:09:04.140Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:09:04.140Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:09:04.140Z] Movies recommended for you:
[2024-10-02T21:09:04.140Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:09:04.140Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:09:04.140Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (11222.975 ms) ======
[2024-10-02T21:09:04.140Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-10-02T21:09:04.140Z] GC before operation: completed in 55.882 ms, heap usage 168.335 MB -> 49.180 MB.
[2024-10-02T21:09:05.922Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:09:07.715Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:09:09.500Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:09:10.730Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:09:11.950Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:09:12.766Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:09:14.004Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:09:14.888Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:09:15.239Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:09:15.239Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:09:15.239Z] Movies recommended for you:
[2024-10-02T21:09:15.239Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:09:15.239Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:09:15.239Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (10903.589 ms) ======
[2024-10-02T21:09:15.239Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-10-02T21:09:15.239Z] GC before operation: completed in 61.824 ms, heap usage 262.937 MB -> 49.586 MB.
[2024-10-02T21:09:17.043Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:09:18.854Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:09:20.095Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:09:21.851Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:09:22.640Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:09:23.866Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:09:24.671Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:09:25.940Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:09:25.940Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:09:25.940Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:09:25.940Z] Movies recommended for you:
[2024-10-02T21:09:25.940Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:09:25.940Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:09:25.940Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (10834.255 ms) ======
[2024-10-02T21:09:25.940Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-10-02T21:09:25.940Z] GC before operation: completed in 59.045 ms, heap usage 145.403 MB -> 49.666 MB.
[2024-10-02T21:09:27.727Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:09:29.509Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:09:31.265Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:09:32.512Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:09:33.749Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:09:34.507Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:09:35.272Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:09:36.568Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:09:36.568Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:09:36.568Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:09:36.568Z] Movies recommended for you:
[2024-10-02T21:09:36.568Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:09:36.568Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:09:36.568Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (10434.784 ms) ======
[2024-10-02T21:09:36.568Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-10-02T21:09:36.568Z] GC before operation: completed in 55.486 ms, heap usage 145.351 MB -> 49.631 MB.
[2024-10-02T21:09:38.377Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:09:40.139Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:09:41.396Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:09:43.164Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:09:43.927Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:09:44.703Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:09:45.933Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:09:46.700Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:09:47.063Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:09:47.063Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:09:47.064Z] Movies recommended for you:
[2024-10-02T21:09:47.064Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:09:47.064Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:09:47.064Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (10407.609 ms) ======
[2024-10-02T21:09:47.064Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-10-02T21:09:47.064Z] GC before operation: completed in 57.015 ms, heap usage 238.052 MB -> 49.908 MB.
[2024-10-02T21:09:48.822Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:09:50.137Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:09:51.923Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:09:53.186Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:09:54.420Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:09:55.186Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:09:55.946Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:09:56.715Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:09:57.075Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:09:57.075Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:09:57.075Z] Movies recommended for you:
[2024-10-02T21:09:57.075Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:09:57.075Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:09:57.075Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9930.818 ms) ======
[2024-10-02T21:09:57.075Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-10-02T21:09:57.075Z] GC before operation: completed in 57.109 ms, heap usage 166.977 MB -> 50.112 MB.
[2024-10-02T21:09:58.341Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:10:00.104Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:10:01.950Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:10:03.195Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:10:03.988Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:10:04.771Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:10:06.013Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:10:06.773Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:10:06.773Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:10:06.773Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:10:06.773Z] Movies recommended for you:
[2024-10-02T21:10:06.773Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:10:06.773Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:10:06.773Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (9865.675 ms) ======
[2024-10-02T21:10:06.773Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-10-02T21:10:07.136Z] GC before operation: completed in 58.989 ms, heap usage 76.202 MB -> 49.840 MB.
[2024-10-02T21:10:08.915Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:10:10.141Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:10:11.906Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:10:13.688Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:10:14.465Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:10:15.225Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:10:16.014Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:10:17.229Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:10:17.229Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:10:17.229Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:10:17.229Z] Movies recommended for you:
[2024-10-02T21:10:17.229Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:10:17.229Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:10:17.229Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (10306.361 ms) ======
[2024-10-02T21:10:17.229Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-10-02T21:10:17.229Z] GC before operation: completed in 57.937 ms, heap usage 143.346 MB -> 50.007 MB.
[2024-10-02T21:10:19.003Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:10:20.282Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:10:22.201Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:10:23.426Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:10:24.185Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:10:25.409Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:10:26.172Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:10:27.401Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:10:27.401Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:10:27.401Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:10:27.401Z] Movies recommended for you:
[2024-10-02T21:10:27.401Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:10:27.401Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:10:27.401Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (10016.844 ms) ======
[2024-10-02T21:10:27.401Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-10-02T21:10:27.401Z] GC before operation: completed in 55.306 ms, heap usage 323.040 MB -> 49.955 MB.
[2024-10-02T21:10:29.170Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:10:31.035Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:10:32.284Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:10:33.522Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:10:34.740Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:10:35.504Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:10:36.273Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:10:37.514Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:10:37.514Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:10:37.514Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:10:37.514Z] Movies recommended for you:
[2024-10-02T21:10:37.514Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:10:37.514Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:10:37.514Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (10032.983 ms) ======
[2024-10-02T21:10:37.514Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-10-02T21:10:37.514Z] GC before operation: completed in 58.480 ms, heap usage 155.486 MB -> 49.952 MB.
[2024-10-02T21:10:39.320Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:10:40.549Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:10:42.335Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:10:43.566Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:10:44.785Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:10:45.548Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:10:46.785Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:10:47.595Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:10:47.595Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:10:47.595Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:10:47.996Z] Movies recommended for you:
[2024-10-02T21:10:47.996Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:10:47.996Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:10:47.996Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (10237.724 ms) ======
[2024-10-02T21:10:47.996Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-10-02T21:10:47.996Z] GC before operation: completed in 62.145 ms, heap usage 154.708 MB -> 50.115 MB.
[2024-10-02T21:10:49.256Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:10:51.021Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:10:52.265Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:10:54.037Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:10:54.819Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:10:55.588Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:10:56.833Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:10:57.597Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:10:57.597Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:10:57.597Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:10:57.597Z] Movies recommended for you:
[2024-10-02T21:10:57.597Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:10:57.597Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:10:57.597Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (9944.352 ms) ======
[2024-10-02T21:10:57.597Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-10-02T21:10:57.947Z] GC before operation: completed in 60.850 ms, heap usage 312.728 MB -> 50.026 MB.
[2024-10-02T21:10:59.718Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:11:00.969Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:11:02.775Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:11:04.597Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:11:05.395Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:11:06.167Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:11:06.939Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:11:08.201Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:11:08.201Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:11:08.201Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:11:08.201Z] Movies recommended for you:
[2024-10-02T21:11:08.201Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:11:08.201Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:11:08.201Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (10368.618 ms) ======
[2024-10-02T21:11:08.201Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-10-02T21:11:08.201Z] GC before operation: completed in 52.876 ms, heap usage 69.710 MB -> 50.015 MB.
[2024-10-02T21:11:09.967Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:11:11.199Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:11:12.968Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:11:14.230Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:11:15.519Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:11:16.309Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:11:17.080Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:11:17.848Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:11:17.848Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:11:17.848Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:11:18.202Z] Movies recommended for you:
[2024-10-02T21:11:18.202Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:11:18.202Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:11:18.202Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (9834.790 ms) ======
[2024-10-02T21:11:18.202Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-10-02T21:11:18.202Z] GC before operation: completed in 50.978 ms, heap usage 75.464 MB -> 50.011 MB.
[2024-10-02T21:11:19.980Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:11:21.200Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:11:22.986Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:11:24.786Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:11:25.540Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:11:26.303Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:11:27.113Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:11:28.337Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:11:28.337Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:11:28.337Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:11:28.337Z] Movies recommended for you:
[2024-10-02T21:11:28.337Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:11:28.337Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:11:28.337Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (10304.100 ms) ======
[2024-10-02T21:11:28.337Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-10-02T21:11:28.337Z] GC before operation: completed in 58.702 ms, heap usage 187.198 MB -> 50.001 MB.
[2024-10-02T21:11:30.110Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:11:31.887Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:11:33.663Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:11:34.888Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:11:35.653Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:11:36.877Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:11:37.636Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:11:38.867Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:11:38.867Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:11:38.867Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:11:38.867Z] Movies recommended for you:
[2024-10-02T21:11:38.867Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:11:38.867Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:11:38.867Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (10368.816 ms) ======
[2024-10-02T21:11:38.867Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-10-02T21:11:38.867Z] GC before operation: completed in 61.541 ms, heap usage 145.470 MB -> 50.040 MB.
[2024-10-02T21:11:40.625Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:11:42.383Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:11:44.163Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:11:45.377Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:11:46.139Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:11:46.901Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:11:48.181Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:11:48.945Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:11:48.945Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:11:48.945Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:11:48.945Z] Movies recommended for you:
[2024-10-02T21:11:48.945Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:11:48.945Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:11:48.945Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (10164.897 ms) ======
[2024-10-02T21:11:48.945Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-10-02T21:11:49.302Z] GC before operation: completed in 58.951 ms, heap usage 154.533 MB -> 50.220 MB.
[2024-10-02T21:11:51.091Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-10-02T21:11:52.322Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-10-02T21:11:54.093Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-10-02T21:11:55.321Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-10-02T21:11:56.563Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-10-02T21:11:57.352Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-10-02T21:11:58.135Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-10-02T21:11:58.893Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-10-02T21:11:59.252Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-10-02T21:11:59.252Z] The best model improves the baseline by 14.52%.
[2024-10-02T21:11:59.252Z] Movies recommended for you:
[2024-10-02T21:11:59.252Z] WARNING: This benchmark provides no result that can be validated.
[2024-10-02T21:11:59.252Z] There is no way to check that no silent failure occurred.
[2024-10-02T21:11:59.252Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (10098.765 ms) ======
[2024-10-02T21:11:59.607Z] -----------------------------------
[2024-10-02T21:11:59.607Z] renaissance-movie-lens_0_PASSED
[2024-10-02T21:11:59.607Z] -----------------------------------
[2024-10-02T21:11:59.607Z]
[2024-10-02T21:11:59.607Z] TEST TEARDOWN:
[2024-10-02T21:11:59.607Z] Nothing to be done for teardown.
[2024-10-02T21:11:59.607Z] renaissance-movie-lens_0 Finish Time: Wed Oct 2 17:11:59 2024 Epoch Time (ms): 1727903519395