renaissance-movie-lens_0
[2024-08-10T08:54:46.485Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T08:54:46.485Z] ===============================================
[2024-08-10T08:54:46.485Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 08:54:45 2024 Epoch Time (ms): 1723280085488
[2024-08-10T08:54:46.485Z] variation: NoOptions
[2024-08-10T08:54:46.485Z] JVM_OPTIONS:
[2024-08-10T08:54:46.485Z] { \
[2024-08-10T08:54:46.485Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T08:54:46.485Z] echo "Nothing to be done for setup."; \
[2024-08-10T08:54:46.485Z] mkdir -p "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17232792367671/renaissance-movie-lens_0"; \
[2024-08-10T08:54:46.485Z] cd "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17232792367671/renaissance-movie-lens_0"; \
[2024-08-10T08:54:46.485Z] echo ""; echo "TESTING:"; \
[2024-08-10T08:54:46.485Z] "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/jdkbinary/j2sdk-image/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 "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17232792367671/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T08:54:46.485Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17232792367671/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T08:54:46.485Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T08:54:46.485Z] echo "Nothing to be done for teardown."; \
[2024-08-10T08:54:46.485Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk17_hs_extended.perf_ppc64_aix_testList_0/aqa-tests/TKG/../TKG/output_17232792367671/TestTargetResult";
[2024-08-10T08:54:46.485Z]
[2024-08-10T08:54:46.485Z] TEST SETUP:
[2024-08-10T08:54:46.485Z] Nothing to be done for setup.
[2024-08-10T08:54:46.485Z]
[2024-08-10T08:54:46.485Z] TESTING:
[2024-08-10T08:54:49.931Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T08:54:52.398Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 24) threads.
[2024-08-10T08:54:55.822Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T08:54:55.822Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T08:54:55.822Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T08:54:55.822Z] GC before operation: completed in 47.828 ms, heap usage 248.457 MB -> 37.650 MB.
[2024-08-10T08:55:01.432Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:55:03.892Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:55:07.314Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:55:09.785Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:55:11.369Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:55:12.955Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:55:14.541Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:55:16.126Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:55:16.894Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:55:16.894Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:55:16.894Z] Movies recommended for you:
[2024-08-10T08:55:16.894Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:55:16.894Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:55:16.894Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (20792.455 ms) ======
[2024-08-10T08:55:16.894Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T08:55:16.894Z] GC before operation: completed in 83.886 ms, heap usage 237.328 MB -> 50.392 MB.
[2024-08-10T08:55:19.367Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:55:22.781Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:55:25.250Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:55:27.723Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:55:29.320Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:55:30.908Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:55:32.491Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:55:34.074Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:55:34.075Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:55:34.075Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:55:34.840Z] Movies recommended for you:
[2024-08-10T08:55:34.840Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:55:34.840Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:55:34.841Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (17595.096 ms) ======
[2024-08-10T08:55:34.841Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T08:55:34.841Z] GC before operation: completed in 92.405 ms, heap usage 2.571 GB -> 56.166 MB.
[2024-08-10T08:55:37.312Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:55:39.962Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:55:42.432Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:55:44.979Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:55:46.576Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:55:48.169Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:55:49.757Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:55:51.348Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:55:52.120Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:55:52.120Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:55:52.120Z] Movies recommended for you:
[2024-08-10T08:55:52.120Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:55:52.120Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:55:52.120Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (17262.273 ms) ======
[2024-08-10T08:55:52.120Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T08:55:52.120Z] GC before operation: completed in 80.203 ms, heap usage 2.249 GB -> 56.501 MB.
[2024-08-10T08:55:54.945Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:55:57.409Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:55:59.872Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:56:02.342Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:56:03.927Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:56:05.525Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:56:07.117Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:56:08.722Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:56:08.722Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:56:08.722Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:56:08.722Z] Movies recommended for you:
[2024-08-10T08:56:08.722Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:56:08.722Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:56:08.722Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (17000.696 ms) ======
[2024-08-10T08:56:08.722Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T08:56:08.722Z] GC before operation: completed in 89.820 ms, heap usage 4.242 GB -> 61.941 MB.
[2024-08-10T08:56:11.200Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:56:13.672Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:56:17.097Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:56:19.714Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:56:20.481Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:56:22.070Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:56:23.658Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:56:25.248Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:56:26.017Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:56:26.017Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:56:26.017Z] Movies recommended for you:
[2024-08-10T08:56:26.017Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:56:26.017Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:56:26.017Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (16809.917 ms) ======
[2024-08-10T08:56:26.017Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T08:56:26.017Z] GC before operation: completed in 79.622 ms, heap usage 165.221 MB -> 52.046 MB.
[2024-08-10T08:56:28.485Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:56:30.950Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:56:33.434Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:56:35.900Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:56:37.489Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:56:39.075Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:56:40.676Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:56:42.259Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:56:42.259Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:56:42.259Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:56:43.233Z] Movies recommended for you:
[2024-08-10T08:56:43.233Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:56:43.233Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:56:43.233Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (16766.374 ms) ======
[2024-08-10T08:56:43.233Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T08:56:43.233Z] GC before operation: completed in 77.465 ms, heap usage 97.916 MB -> 55.818 MB.
[2024-08-10T08:56:45.724Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:56:48.205Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:56:50.666Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:56:53.137Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:56:54.726Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:56:56.310Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:56:57.909Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:56:59.070Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:56:59.850Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:56:59.850Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:56:59.850Z] Movies recommended for you:
[2024-08-10T08:56:59.850Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:56:59.850Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:56:59.850Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (16834.320 ms) ======
[2024-08-10T08:56:59.850Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T08:56:59.850Z] GC before operation: completed in 84.045 ms, heap usage 206.315 MB -> 52.210 MB.
[2024-08-10T08:57:02.336Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:57:04.800Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:57:07.267Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:57:09.737Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:57:11.334Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:57:12.923Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:57:14.512Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:57:16.111Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:57:16.879Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:57:16.879Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:57:16.879Z] Movies recommended for you:
[2024-08-10T08:57:16.879Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:57:16.879Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:57:16.879Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (17155.208 ms) ======
[2024-08-10T08:57:16.879Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T08:57:16.879Z] GC before operation: completed in 91.364 ms, heap usage 1.779 GB -> 57.375 MB.
[2024-08-10T08:57:19.348Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:57:21.822Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:57:25.268Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:57:27.754Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:57:28.522Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:57:30.118Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:57:31.710Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:57:33.300Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:57:34.066Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:57:34.066Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:57:34.066Z] Movies recommended for you:
[2024-08-10T08:57:34.066Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:57:34.066Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:57:34.066Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (17004.527 ms) ======
[2024-08-10T08:57:34.066Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T08:57:34.066Z] GC before operation: completed in 83.913 ms, heap usage 1.457 GB -> 56.991 MB.
[2024-08-10T08:57:36.534Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:57:39.009Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:57:42.425Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:57:44.061Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:57:45.652Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:57:47.237Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:57:48.834Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:57:50.429Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:57:51.216Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:57:51.216Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:57:51.216Z] Movies recommended for you:
[2024-08-10T08:57:51.216Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:57:51.216Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:57:51.216Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (16946.028 ms) ======
[2024-08-10T08:57:51.216Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T08:57:51.216Z] GC before operation: completed in 81.127 ms, heap usage 861.217 MB -> 56.143 MB.
[2024-08-10T08:57:53.688Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:57:56.159Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:57:58.630Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:58:01.100Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:58:02.682Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:58:04.450Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:58:06.099Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:58:07.701Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:58:07.701Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:58:07.701Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:58:07.701Z] Movies recommended for you:
[2024-08-10T08:58:07.701Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:58:07.701Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:58:07.701Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (16643.466 ms) ======
[2024-08-10T08:58:07.701Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T08:58:07.701Z] GC before operation: completed in 83.997 ms, heap usage 985.428 MB -> 56.235 MB.
[2024-08-10T08:58:10.169Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:58:12.673Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:58:16.097Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:58:17.693Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:58:19.285Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:58:20.881Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:58:22.465Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:58:24.061Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:58:24.829Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:58:24.829Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:58:24.829Z] Movies recommended for you:
[2024-08-10T08:58:24.829Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:58:24.829Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:58:24.829Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (16867.234 ms) ======
[2024-08-10T08:58:24.829Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T08:58:24.829Z] GC before operation: completed in 87.909 ms, heap usage 1.948 GB -> 57.335 MB.
[2024-08-10T08:58:27.291Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:58:29.765Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:58:32.233Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:58:34.697Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:58:36.283Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:58:37.877Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:58:39.470Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:58:41.055Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:58:41.055Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:58:41.055Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:58:41.055Z] Movies recommended for you:
[2024-08-10T08:58:41.055Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:58:41.055Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:58:41.055Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (16592.022 ms) ======
[2024-08-10T08:58:41.055Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T08:58:41.055Z] GC before operation: completed in 87.691 ms, heap usage 800.329 MB -> 56.092 MB.
[2024-08-10T08:58:44.465Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:58:46.061Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:58:49.489Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:58:51.956Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:58:52.728Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:58:54.321Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:58:55.923Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:58:57.513Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:58:58.280Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:58:58.280Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:58:58.280Z] Movies recommended for you:
[2024-08-10T08:58:58.280Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:58:58.281Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:58:58.281Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (16619.053 ms) ======
[2024-08-10T08:58:58.281Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T08:58:58.281Z] GC before operation: completed in 95.139 ms, heap usage 1.514 GB -> 56.989 MB.
[2024-08-10T08:59:00.760Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:59:03.227Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:59:05.696Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:59:08.170Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:59:09.978Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:59:11.564Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:59:13.157Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:59:14.755Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:59:14.755Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:59:14.755Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:59:14.755Z] Movies recommended for you:
[2024-08-10T08:59:14.755Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:59:14.755Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:59:14.755Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (16940.864 ms) ======
[2024-08-10T08:59:14.755Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T08:59:15.525Z] GC before operation: completed in 78.547 ms, heap usage 189.387 MB -> 52.373 MB.
[2024-08-10T08:59:17.986Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:59:20.454Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:59:22.920Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:59:25.380Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:59:26.967Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:59:28.559Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:59:30.146Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:59:31.747Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:59:31.747Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:59:31.747Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:59:32.514Z] Movies recommended for you:
[2024-08-10T08:59:32.514Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:59:32.514Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:59:32.514Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (17060.054 ms) ======
[2024-08-10T08:59:32.514Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T08:59:32.514Z] GC before operation: completed in 91.129 ms, heap usage 2.011 GB -> 57.411 MB.
[2024-08-10T08:59:34.980Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:59:37.465Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:59:39.933Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:59:42.433Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T08:59:44.055Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T08:59:45.648Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T08:59:47.250Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T08:59:48.847Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T08:59:48.847Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T08:59:48.847Z] The best model improves the baseline by 14.43%.
[2024-08-10T08:59:48.847Z] Movies recommended for you:
[2024-08-10T08:59:48.847Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T08:59:48.847Z] There is no way to check that no silent failure occurred.
[2024-08-10T08:59:48.847Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (16760.049 ms) ======
[2024-08-10T08:59:48.847Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T08:59:48.847Z] GC before operation: completed in 83.929 ms, heap usage 1.517 GB -> 57.105 MB.
[2024-08-10T08:59:51.329Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T08:59:53.799Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T08:59:57.218Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T08:59:58.803Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T09:00:00.400Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T09:00:02.000Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T09:00:03.581Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T09:00:05.162Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T09:00:05.163Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T09:00:05.163Z] The best model improves the baseline by 14.43%.
[2024-08-10T09:00:05.932Z] Movies recommended for you:
[2024-08-10T09:00:05.932Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T09:00:05.932Z] There is no way to check that no silent failure occurred.
[2024-08-10T09:00:05.932Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (16430.219 ms) ======
[2024-08-10T09:00:05.932Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T09:00:05.932Z] GC before operation: completed in 81.758 ms, heap usage 1.002 GB -> 56.471 MB.
[2024-08-10T09:00:08.402Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T09:00:10.878Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T09:00:13.340Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T09:00:16.189Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T09:00:17.777Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T09:00:18.557Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T09:00:20.139Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T09:00:21.722Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T09:00:22.491Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T09:00:22.491Z] The best model improves the baseline by 14.43%.
[2024-08-10T09:00:22.491Z] Movies recommended for you:
[2024-08-10T09:00:22.491Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T09:00:22.491Z] There is no way to check that no silent failure occurred.
[2024-08-10T09:00:22.491Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (16611.569 ms) ======
[2024-08-10T09:00:22.491Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T09:00:22.491Z] GC before operation: completed in 88.112 ms, heap usage 3.442 GB -> 61.766 MB.
[2024-08-10T09:00:24.955Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T09:00:27.419Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T09:00:29.897Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T09:00:32.361Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T09:00:33.949Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T09:00:35.538Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T09:00:37.137Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T09:00:38.889Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T09:00:38.889Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T09:00:38.889Z] The best model improves the baseline by 14.43%.
[2024-08-10T09:00:38.889Z] Movies recommended for you:
[2024-08-10T09:00:38.889Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T09:00:38.889Z] There is no way to check that no silent failure occurred.
[2024-08-10T09:00:38.889Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (16624.777 ms) ======
[2024-08-10T09:00:39.659Z] -----------------------------------
[2024-08-10T09:00:39.659Z] renaissance-movie-lens_0_PASSED
[2024-08-10T09:00:39.659Z] -----------------------------------
[2024-08-10T09:00:39.659Z]
[2024-08-10T09:00:39.659Z] TEST TEARDOWN:
[2024-08-10T09:00:39.659Z] Nothing to be done for teardown.
[2024-08-10T09:00:39.659Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 09:00:39 2024 Epoch Time (ms): 1723280439316