renaissance-movie-lens_0
[2024-09-26T21:29:28.447Z] Running test renaissance-movie-lens_0 ...
[2024-09-26T21:29:28.447Z] ===============================================
[2024-09-26T21:29:28.447Z] renaissance-movie-lens_0 Start Time: Thu Sep 26 22:29:28 2024 Epoch Time (ms): 1727386168035
[2024-09-26T21:29:28.447Z] variation: NoOptions
[2024-09-26T21:29:28.447Z] JVM_OPTIONS:
[2024-09-26T21:29:28.447Z] { \
[2024-09-26T21:29:28.447Z] echo ""; echo "TEST SETUP:"; \
[2024-09-26T21:29:28.447Z] echo "Nothing to be done for setup."; \
[2024-09-26T21:29:28.447Z] mkdir -p "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17273848222894/renaissance-movie-lens_0"; \
[2024-09-26T21:29:28.447Z] cd "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17273848222894/renaissance-movie-lens_0"; \
[2024-09-26T21:29:28.447Z] echo ""; echo "TESTING:"; \
[2024-09-26T21:29:28.447Z] "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/jdkbinary/j2sdk-image/bin/java" -jar "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17273848222894/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-09-26T21:29:28.447Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/..; rm -f -r "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17273848222894/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-09-26T21:29:28.447Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-09-26T21:29:28.447Z] echo "Nothing to be done for teardown."; \
[2024-09-26T21:29:28.448Z] } 2>&1 | tee -a "/export/home/jenkins/workspace/Test_openjdk8_hs_extended.perf_x86-64_solaris/aqa-tests/TKG/../TKG/output_17273848222894/TestTargetResult";
[2024-09-26T21:29:28.448Z]
[2024-09-26T21:29:28.448Z] TEST SETUP:
[2024-09-26T21:29:28.448Z] Nothing to be done for setup.
[2024-09-26T21:29:28.448Z]
[2024-09-26T21:29:28.448Z] TESTING:
[2024-09-26T21:29:34.444Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-09-26T21:29:38.205Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 1 (out of 1) threads.
[2024-09-26T21:29:45.563Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-09-26T21:29:46.215Z] Training: 60056, validation: 20285, test: 19854
[2024-09-26T21:29:46.215Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-09-26T21:29:46.215Z] GC before operation: completed in 108.521 ms, heap usage 49.453 MB -> 26.106 MB.
[2024-09-26T21:29:57.101Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:30:03.159Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:30:08.071Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:30:11.898Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:30:14.755Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:30:16.830Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:30:19.747Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:30:21.923Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:30:22.561Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:30:23.188Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:30:23.189Z] Movies recommended for you:
[2024-09-26T21:30:23.189Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:30:23.189Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:30:23.189Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (36958.448 ms) ======
[2024-09-26T21:30:23.189Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-09-26T21:30:23.189Z] GC before operation: completed in 120.110 ms, heap usage 75.371 MB -> 49.222 MB.
[2024-09-26T21:30:26.978Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:30:30.075Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:30:33.834Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:30:36.725Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:30:39.002Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:30:41.136Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:30:42.439Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:30:44.494Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:30:44.494Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:30:44.494Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:30:45.124Z] Movies recommended for you:
[2024-09-26T21:30:45.124Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:30:45.124Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:30:45.124Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21817.466 ms) ======
[2024-09-26T21:30:45.124Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-09-26T21:30:45.125Z] GC before operation: completed in 178.607 ms, heap usage 100.385 MB -> 72.576 MB.
[2024-09-26T21:30:49.046Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:30:52.005Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:30:55.804Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:31:00.693Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:31:02.030Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:31:04.132Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:31:06.668Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:31:08.929Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:31:08.929Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:31:08.929Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:31:08.929Z] Movies recommended for you:
[2024-09-26T21:31:08.929Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:31:08.929Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:31:08.929Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23982.773 ms) ======
[2024-09-26T21:31:08.929Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-09-26T21:31:09.593Z] GC before operation: completed in 154.438 ms, heap usage 134.394 MB -> 61.167 MB.
[2024-09-26T21:31:12.643Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:31:15.529Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:31:18.396Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:31:21.311Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:31:23.418Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:31:25.528Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:31:27.597Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:31:29.905Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:31:29.905Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:31:29.905Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:31:29.905Z] Movies recommended for you:
[2024-09-26T21:31:29.905Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:31:29.905Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:31:29.905Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (20917.871 ms) ======
[2024-09-26T21:31:29.905Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-09-26T21:31:30.556Z] GC before operation: completed in 142.774 ms, heap usage 127.538 MB -> 69.782 MB.
[2024-09-26T21:31:33.438Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:31:36.291Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:31:40.149Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:31:42.228Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:31:44.399Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:31:45.704Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:31:47.738Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:31:49.299Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:31:50.138Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:31:50.138Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:31:50.138Z] Movies recommended for you:
[2024-09-26T21:31:50.138Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:31:50.138Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:31:50.138Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (19560.194 ms) ======
[2024-09-26T21:31:50.138Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-09-26T21:31:50.138Z] GC before operation: completed in 146.170 ms, heap usage 131.165 MB -> 67.992 MB.
[2024-09-26T21:31:53.026Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:31:55.889Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:31:58.851Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:32:01.843Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:32:04.020Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:32:05.452Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:32:07.539Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:32:09.631Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:32:09.631Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:32:09.631Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:32:09.631Z] Movies recommended for you:
[2024-09-26T21:32:09.631Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:32:09.631Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:32:09.631Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19792.503 ms) ======
[2024-09-26T21:32:09.631Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-09-26T21:32:10.255Z] GC before operation: completed in 208.242 ms, heap usage 116.858 MB -> 70.240 MB.
[2024-09-26T21:32:13.188Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:32:16.194Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:32:19.143Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:32:22.047Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:32:24.127Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:32:26.183Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:32:27.528Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:32:29.637Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:32:29.637Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:32:29.637Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:32:29.637Z] Movies recommended for you:
[2024-09-26T21:32:29.637Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:32:29.637Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:32:29.637Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (19970.654 ms) ======
[2024-09-26T21:32:29.637Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-09-26T21:32:30.286Z] GC before operation: completed in 168.705 ms, heap usage 118.940 MB -> 63.100 MB.
[2024-09-26T21:32:33.719Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:32:36.730Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:32:39.582Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:32:42.482Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:32:44.549Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:32:45.847Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:32:47.953Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:32:49.408Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:32:50.152Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:32:50.153Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:32:50.153Z] Movies recommended for you:
[2024-09-26T21:32:50.153Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:32:50.153Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:32:50.153Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20117.574 ms) ======
[2024-09-26T21:32:50.153Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-09-26T21:32:50.153Z] GC before operation: completed in 145.034 ms, heap usage 127.522 MB -> 69.476 MB.
[2024-09-26T21:32:53.014Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:32:56.773Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:32:59.626Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:33:02.535Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:33:03.863Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:33:05.978Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:33:08.069Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:33:10.148Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:33:10.148Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:33:10.148Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:33:10.148Z] Movies recommended for you:
[2024-09-26T21:33:10.148Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:33:10.148Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:33:10.148Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (19996.515 ms) ======
[2024-09-26T21:33:10.148Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-09-26T21:33:10.778Z] GC before operation: completed in 185.644 ms, heap usage 123.314 MB -> 71.214 MB.
[2024-09-26T21:33:13.653Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:33:16.611Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:33:19.323Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:33:22.375Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:33:24.476Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:33:25.785Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:33:27.830Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:33:29.348Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:33:29.973Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:33:29.973Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:33:29.973Z] Movies recommended for you:
[2024-09-26T21:33:29.973Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:33:29.973Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:33:29.973Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (19639.829 ms) ======
[2024-09-26T21:33:29.973Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-09-26T21:33:30.609Z] GC before operation: completed in 260.818 ms, heap usage 127.896 MB -> 74.917 MB.
[2024-09-26T21:33:33.484Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:33:36.445Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:33:39.293Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:33:42.261Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:33:43.570Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:33:45.785Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:33:47.113Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:33:49.197Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:33:49.197Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:33:49.824Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:33:49.824Z] Movies recommended for you:
[2024-09-26T21:33:49.824Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:33:49.824Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:33:49.824Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (19280.389 ms) ======
[2024-09-26T21:33:49.824Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-09-26T21:33:49.824Z] GC before operation: completed in 178.052 ms, heap usage 132.486 MB -> 61.869 MB.
[2024-09-26T21:33:52.873Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:33:55.775Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:33:58.688Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:34:01.565Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:34:03.554Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:34:05.700Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:34:07.098Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:34:09.164Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:34:09.164Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:34:09.164Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:34:09.789Z] Movies recommended for you:
[2024-09-26T21:34:09.789Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:34:09.789Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:34:09.789Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (19799.309 ms) ======
[2024-09-26T21:34:09.789Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-09-26T21:34:09.789Z] GC before operation: completed in 332.389 ms, heap usage 114.899 MB -> 70.993 MB.
[2024-09-26T21:34:12.698Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:34:16.489Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:34:20.272Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:34:23.146Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:34:25.228Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:34:26.539Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:34:28.643Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:34:30.915Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:34:30.915Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:34:30.915Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:34:31.556Z] Movies recommended for you:
[2024-09-26T21:34:31.556Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:34:31.556Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:34:31.556Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21418.371 ms) ======
[2024-09-26T21:34:31.556Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-09-26T21:34:31.556Z] GC before operation: completed in 343.588 ms, heap usage 117.935 MB -> 75.857 MB.
[2024-09-26T21:34:34.474Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:34:37.495Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:34:41.270Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:34:44.199Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:34:45.524Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:34:47.610Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:34:49.409Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:34:51.642Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:34:51.642Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:34:51.642Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:34:51.642Z] Movies recommended for you:
[2024-09-26T21:34:51.642Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:34:51.642Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:34:51.642Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20129.146 ms) ======
[2024-09-26T21:34:51.642Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-09-26T21:34:52.302Z] GC before operation: completed in 305.324 ms, heap usage 116.871 MB -> 73.243 MB.
[2024-09-26T21:34:55.256Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:34:58.121Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:35:01.359Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:35:03.408Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:35:05.471Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:35:06.850Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:35:08.920Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:35:11.004Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:35:11.004Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:35:11.004Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:35:11.629Z] Movies recommended for you:
[2024-09-26T21:35:11.629Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:35:11.629Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:35:11.629Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (19286.699 ms) ======
[2024-09-26T21:35:11.629Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-09-26T21:35:11.629Z] GC before operation: completed in 156.687 ms, heap usage 138.918 MB -> 66.409 MB.
[2024-09-26T21:35:14.528Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:35:17.400Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:35:21.343Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:35:23.429Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:35:24.877Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:35:27.009Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:35:28.304Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:35:30.547Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:35:30.547Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:35:30.547Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:35:30.547Z] Movies recommended for you:
[2024-09-26T21:35:30.547Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:35:30.547Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:35:30.547Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (19238.696 ms) ======
[2024-09-26T21:35:30.547Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-09-26T21:35:31.171Z] GC before operation: completed in 196.139 ms, heap usage 155.763 MB -> 72.951 MB.
[2024-09-26T21:35:33.782Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:35:36.785Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:35:40.211Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:35:43.171Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:35:45.260Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:35:46.609Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:35:48.769Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:35:50.074Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:35:50.698Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:35:50.698Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:35:50.698Z] Movies recommended for you:
[2024-09-26T21:35:50.698Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:35:50.698Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:35:50.698Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (19928.017 ms) ======
[2024-09-26T21:35:50.698Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-09-26T21:35:51.337Z] GC before operation: completed in 287.593 ms, heap usage 142.247 MB -> 76.029 MB.
[2024-09-26T21:35:54.201Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:35:57.143Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:36:00.039Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:36:03.001Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:36:04.347Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:36:05.766Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:36:07.801Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:36:09.161Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:36:09.807Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:36:09.807Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:36:09.807Z] Movies recommended for you:
[2024-09-26T21:36:09.807Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:36:09.807Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:36:09.807Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (18955.087 ms) ======
[2024-09-26T21:36:09.807Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-09-26T21:36:10.445Z] GC before operation: completed in 292.324 ms, heap usage 126.182 MB -> 73.770 MB.
[2024-09-26T21:36:13.351Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:36:16.269Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:36:19.207Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:36:22.163Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:36:23.520Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:36:24.885Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:36:27.120Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:36:28.418Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:36:29.134Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:36:29.134Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:36:29.134Z] Movies recommended for you:
[2024-09-26T21:36:29.134Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:36:29.134Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:36:29.134Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (18725.337 ms) ======
[2024-09-26T21:36:29.134Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-09-26T21:36:29.134Z] GC before operation: completed in 149.624 ms, heap usage 126.399 MB -> 66.672 MB.
[2024-09-26T21:36:32.009Z] RMSE (validation) = 3.6219689545487626 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-09-26T21:36:34.886Z] RMSE (validation) = 2.1340923188651915 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-09-26T21:36:37.809Z] RMSE (validation) = 1.3105186849113732 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-09-26T21:36:40.794Z] RMSE (validation) = 1.0067105965077905 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-09-26T21:36:42.131Z] RMSE (validation) = 1.2280678781652192 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-09-26T21:36:43.429Z] RMSE (validation) = 1.1218153401857944 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-09-26T21:36:45.485Z] RMSE (validation) = 0.9269352310919159 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-09-26T21:36:46.803Z] RMSE (validation) = 0.9005755986883522 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-09-26T21:36:46.803Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9083924152149858.
[2024-09-26T21:36:46.803Z] The best model improves the baseline by 14.33%.
[2024-09-26T21:36:47.444Z] Movies recommended for you:
[2024-09-26T21:36:47.444Z] WARNING: This benchmark provides no result that can be validated.
[2024-09-26T21:36:47.444Z] There is no way to check that no silent failure occurred.
[2024-09-26T21:36:47.444Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (18037.020 ms) ======
[2024-09-26T21:36:48.071Z] -----------------------------------
[2024-09-26T21:36:48.071Z] renaissance-movie-lens_0_PASSED
[2024-09-26T21:36:48.071Z] -----------------------------------
[2024-09-26T21:36:48.071Z]
[2024-09-26T21:36:48.071Z] TEST TEARDOWN:
[2024-09-26T21:36:48.071Z] Nothing to be done for teardown.
[2024-09-26T21:36:48.071Z] renaissance-movie-lens_0 Finish Time: Thu Sep 26 22:36:47 2024 Epoch Time (ms): 1727386607552