renaissance-movie-lens_0
[2024-08-01T01:26:45.148Z] Running test renaissance-movie-lens_0 ...
[2024-08-01T01:26:45.148Z] ===============================================
[2024-08-01T01:26:45.969Z] renaissance-movie-lens_0 Start Time: Thu Aug 1 01:26:45 2024 Epoch Time (ms): 1722475605075
[2024-08-01T01:26:45.969Z] variation: NoOptions
[2024-08-01T01:26:45.969Z] JVM_OPTIONS:
[2024-08-01T01:26:45.969Z] { \
[2024-08-01T01:26:45.969Z] echo ""; echo "TEST SETUP:"; \
[2024-08-01T01:26:45.969Z] echo "Nothing to be done for setup."; \
[2024-08-01T01:26:45.969Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17224704683843/renaissance-movie-lens_0"; \
[2024-08-01T01:26:45.969Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17224704683843/renaissance-movie-lens_0"; \
[2024-08-01T01:26:45.969Z] echo ""; echo "TESTING:"; \
[2024-08-01T01:26:45.969Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_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_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17224704683843/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-01T01:26:45.969Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17224704683843/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-01T01:26:45.969Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-01T01:26:45.969Z] echo "Nothing to be done for teardown."; \
[2024-08-01T01:26:45.969Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_alpine-linux_testList_0/aqa-tests/TKG/../TKG/output_17224704683843/TestTargetResult";
[2024-08-01T01:26:45.969Z]
[2024-08-01T01:26:45.969Z] TEST SETUP:
[2024-08-01T01:26:45.969Z] Nothing to be done for setup.
[2024-08-01T01:26:45.969Z]
[2024-08-01T01:26:45.969Z] TESTING:
[2024-08-01T01:26:58.297Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-01T01:27:11.215Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads.
[2024-08-01T01:27:34.157Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-01T01:27:34.157Z] Training: 60056, validation: 20285, test: 19854
[2024-08-01T01:27:34.157Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-01T01:27:34.157Z] GC before operation: completed in 443.156 ms, heap usage 57.519 MB -> 36.490 MB.
[2024-08-01T01:28:23.954Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:29:00.285Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:29:23.619Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:29:46.811Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:30:01.635Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:30:14.092Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:30:27.248Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:30:39.528Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:30:42.240Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:30:42.240Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:30:43.106Z] Movies recommended for you:
[2024-08-01T01:30:43.106Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:30:43.106Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:30:43.106Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (188800.956 ms) ======
[2024-08-01T01:30:43.106Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-01T01:30:44.030Z] GC before operation: completed in 851.734 ms, heap usage 259.035 MB -> 49.984 MB.
[2024-08-01T01:31:07.127Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:31:26.102Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:31:44.836Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:32:01.316Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:32:12.852Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:32:24.470Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:32:34.178Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:32:43.882Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:32:45.434Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:32:45.434Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:32:46.178Z] Movies recommended for you:
[2024-08-01T01:32:46.178Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:32:46.178Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:32:46.178Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (122180.634 ms) ======
[2024-08-01T01:32:46.178Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-01T01:32:46.926Z] GC before operation: completed in 763.814 ms, heap usage 262.350 MB -> 49.097 MB.
[2024-08-01T01:33:06.234Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:33:22.208Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:33:40.923Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:33:57.070Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:34:07.478Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:34:17.254Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:34:28.834Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:34:38.500Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:34:40.114Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:34:40.114Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:34:40.863Z] Movies recommended for you:
[2024-08-01T01:34:40.863Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:34:40.863Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:34:40.863Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (113741.836 ms) ======
[2024-08-01T01:34:40.863Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-01T01:34:40.863Z] GC before operation: completed in 594.819 ms, heap usage 63.279 MB -> 49.261 MB.
[2024-08-01T01:34:59.565Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:35:15.886Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:35:31.938Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:35:45.458Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:35:55.326Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:36:03.414Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:36:13.081Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:36:21.719Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:36:23.277Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:36:23.277Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:36:24.030Z] Movies recommended for you:
[2024-08-01T01:36:24.030Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:36:24.030Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:36:24.030Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (102671.253 ms) ======
[2024-08-01T01:36:24.030Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-01T01:36:24.030Z] GC before operation: completed in 472.200 ms, heap usage 128.511 MB -> 49.577 MB.
[2024-08-01T01:36:42.760Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:36:58.785Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:37:17.440Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:37:31.120Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:37:41.560Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:37:51.478Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:37:59.790Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:38:09.558Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:38:10.301Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:38:10.301Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:38:11.048Z] Movies recommended for you:
[2024-08-01T01:38:11.048Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:38:11.048Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:38:11.048Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (106989.051 ms) ======
[2024-08-01T01:38:11.048Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-01T01:38:11.824Z] GC before operation: completed in 501.452 ms, heap usage 103.609 MB -> 49.738 MB.
[2024-08-01T01:38:27.868Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:38:41.507Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:38:58.021Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:39:11.646Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:39:21.518Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:39:29.628Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:39:39.404Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:39:48.068Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:39:48.852Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:39:48.852Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:39:49.618Z] Movies recommended for you:
[2024-08-01T01:39:49.618Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:39:49.618Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:39:49.618Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (97916.033 ms) ======
[2024-08-01T01:39:49.618Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-01T01:39:50.369Z] GC before operation: completed in 636.352 ms, heap usage 312.071 MB -> 49.900 MB.
[2024-08-01T01:40:06.401Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:40:22.287Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:40:35.829Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:40:51.946Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:41:00.699Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:41:08.817Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:41:18.590Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:41:26.735Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:41:27.489Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:41:27.489Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:41:28.296Z] Movies recommended for you:
[2024-08-01T01:41:28.296Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:41:28.296Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:41:28.296Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (97778.966 ms) ======
[2024-08-01T01:41:28.296Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-01T01:41:28.296Z] GC before operation: completed in 526.093 ms, heap usage 323.197 MB -> 50.066 MB.
[2024-08-01T01:41:44.462Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:42:00.421Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:42:12.490Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:42:26.078Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:42:35.895Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:42:45.629Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:42:53.811Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:43:03.514Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:43:04.263Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:43:05.007Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:43:05.761Z] Movies recommended for you:
[2024-08-01T01:43:05.761Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:43:05.761Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:43:05.761Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (96923.730 ms) ======
[2024-08-01T01:43:05.761Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-01T01:43:06.608Z] GC before operation: completed in 624.297 ms, heap usage 114.789 MB -> 50.130 MB.
[2024-08-01T01:43:20.685Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:43:36.666Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:43:50.310Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:44:03.913Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:44:12.038Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:44:20.151Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:44:28.285Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:44:38.030Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:44:38.810Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:44:38.810Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:44:39.558Z] Movies recommended for you:
[2024-08-01T01:44:39.558Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:44:39.558Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:44:39.558Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (93397.338 ms) ======
[2024-08-01T01:44:39.558Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-01T01:44:40.318Z] GC before operation: completed in 573.509 ms, heap usage 122.954 MB -> 49.956 MB.
[2024-08-01T01:44:56.290Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:45:09.956Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:45:24.403Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:45:37.952Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:45:46.194Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:45:54.491Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:46:04.153Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:46:10.890Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:46:12.425Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:46:13.169Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:46:13.169Z] Movies recommended for you:
[2024-08-01T01:46:13.169Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:46:13.169Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:46:13.169Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (93165.121 ms) ======
[2024-08-01T01:46:13.169Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-01T01:46:13.910Z] GC before operation: completed in 586.106 ms, heap usage 206.038 MB -> 50.149 MB.
[2024-08-01T01:46:28.076Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:46:41.648Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:46:55.269Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:47:08.703Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:47:16.769Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:47:26.437Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:47:34.902Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:47:42.874Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:47:43.602Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:47:44.414Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:47:44.415Z] Movies recommended for you:
[2024-08-01T01:47:44.415Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:47:44.415Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:47:44.415Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (90636.716 ms) ======
[2024-08-01T01:47:44.415Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-01T01:47:45.146Z] GC before operation: completed in 725.408 ms, heap usage 202.755 MB -> 49.890 MB.
[2024-08-01T01:48:00.798Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:48:14.129Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:48:27.426Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:48:38.931Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:48:48.448Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:48:56.544Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:49:04.552Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:49:12.775Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:49:13.518Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:49:13.518Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:49:14.489Z] Movies recommended for you:
[2024-08-01T01:49:14.489Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:49:14.489Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:49:14.489Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (88970.363 ms) ======
[2024-08-01T01:49:14.489Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-01T01:49:14.489Z] GC before operation: completed in 574.622 ms, heap usage 332.129 MB -> 50.204 MB.
[2024-08-01T01:49:30.363Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:49:44.389Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:50:00.260Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:50:11.669Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:50:19.724Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:50:27.765Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:50:37.640Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:50:46.033Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:50:47.585Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:50:47.585Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:50:47.585Z] Movies recommended for you:
[2024-08-01T01:50:47.585Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:50:47.585Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:50:47.585Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (93037.516 ms) ======
[2024-08-01T01:50:47.585Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-01T01:50:48.377Z] GC before operation: completed in 655.816 ms, heap usage 322.070 MB -> 50.349 MB.
[2024-08-01T01:51:04.481Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:51:18.180Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:51:34.060Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:51:45.717Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:51:54.418Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:52:02.509Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:52:10.657Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:52:18.780Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:52:20.381Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:52:20.381Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:52:21.123Z] Movies recommended for you:
[2024-08-01T01:52:21.123Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:52:21.123Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:52:21.123Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (92307.099 ms) ======
[2024-08-01T01:52:21.123Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-01T01:52:21.123Z] GC before operation: completed in 699.002 ms, heap usage 193.216 MB -> 47.614 MB.
[2024-08-01T01:52:36.868Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:52:50.822Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:53:06.633Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:53:22.441Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:53:30.677Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:53:40.309Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:53:48.447Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:53:56.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:53:57.427Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:53:57.427Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:53:58.532Z] Movies recommended for you:
[2024-08-01T01:53:58.532Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:53:58.532Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:53:58.532Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (96318.606 ms) ======
[2024-08-01T01:53:58.532Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-01T01:53:58.532Z] GC before operation: completed in 586.785 ms, heap usage 126.818 MB -> 47.639 MB.
[2024-08-01T01:54:14.365Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:54:27.830Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:54:41.329Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:54:54.955Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:55:04.717Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:55:11.928Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:55:21.605Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:55:29.653Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:55:30.394Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:55:31.141Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:55:31.141Z] Movies recommended for you:
[2024-08-01T01:55:31.141Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:55:31.141Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:55:31.141Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (92855.443 ms) ======
[2024-08-01T01:55:31.141Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-01T01:55:31.885Z] GC before operation: completed in 508.989 ms, heap usage 184.556 MB -> 47.669 MB.
[2024-08-01T01:55:45.317Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:55:58.892Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:56:12.910Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:56:24.313Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:56:32.417Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:56:39.332Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:56:48.989Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:56:57.105Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:56:58.638Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:56:58.638Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:56:59.385Z] Movies recommended for you:
[2024-08-01T01:56:59.385Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:56:59.385Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:56:59.385Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (87617.800 ms) ======
[2024-08-01T01:56:59.385Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-01T01:57:00.125Z] GC before operation: completed in 596.742 ms, heap usage 96.250 MB -> 47.984 MB.
[2024-08-01T01:57:14.077Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:57:28.170Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:57:42.196Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:57:56.196Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:58:06.267Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:58:14.770Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:58:23.946Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T01:58:32.422Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T01:58:33.223Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T01:58:34.014Z] The best model improves the baseline by 14.52%.
[2024-08-01T01:58:34.014Z] Movies recommended for you:
[2024-08-01T01:58:34.014Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T01:58:34.014Z] There is no way to check that no silent failure occurred.
[2024-08-01T01:58:34.014Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (94176.477 ms) ======
[2024-08-01T01:58:34.014Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-01T01:58:34.814Z] GC before operation: completed in 522.251 ms, heap usage 71.414 MB -> 47.958 MB.
[2024-08-01T01:58:48.791Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T01:59:02.970Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T01:59:17.102Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T01:59:29.182Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T01:59:36.562Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T01:59:43.663Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T01:59:52.290Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T02:00:00.815Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T02:00:02.528Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T02:00:02.528Z] The best model improves the baseline by 14.52%.
[2024-08-01T02:00:02.528Z] Movies recommended for you:
[2024-08-01T02:00:02.528Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T02:00:02.528Z] There is no way to check that no silent failure occurred.
[2024-08-01T02:00:02.528Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (88113.732 ms) ======
[2024-08-01T02:00:02.528Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-01T02:00:03.322Z] GC before operation: completed in 624.044 ms, heap usage 81.028 MB -> 47.593 MB.
[2024-08-01T02:00:17.434Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-01T02:00:29.436Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-01T02:00:44.122Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-01T02:00:54.367Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-01T02:01:01.431Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-01T02:01:08.509Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-01T02:01:18.706Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-01T02:01:24.553Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-01T02:01:26.247Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611.
[2024-08-01T02:01:26.247Z] The best model improves the baseline by 14.52%.
[2024-08-01T02:01:27.039Z] Movies recommended for you:
[2024-08-01T02:01:27.039Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-01T02:01:27.039Z] There is no way to check that no silent failure occurred.
[2024-08-01T02:01:27.039Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (83449.666 ms) ======
[2024-08-01T02:01:28.676Z] -----------------------------------
[2024-08-01T02:01:28.676Z] renaissance-movie-lens_0_PASSED
[2024-08-01T02:01:28.676Z] -----------------------------------
[2024-08-01T02:01:29.476Z]
[2024-08-01T02:01:29.476Z] TEST TEARDOWN:
[2024-08-01T02:01:29.476Z] Nothing to be done for teardown.
[2024-08-01T02:01:29.476Z] renaissance-movie-lens_0 Finish Time: Thu Aug 1 02:01:28 2024 Epoch Time (ms): 1722477688649