renaissance-movie-lens_0
[2024-11-16T03:33:21.291Z] Running test renaissance-movie-lens_0 ...
[2024-11-16T03:33:21.291Z] ===============================================
[2024-11-16T03:33:21.291Z] renaissance-movie-lens_0 Start Time: Fri Nov 15 22:33:20 2024 Epoch Time (ms): 1731728000943
[2024-11-16T03:33:21.291Z] variation: NoOptions
[2024-11-16T03:33:21.291Z] JVM_OPTIONS:
[2024-11-16T03:33:21.291Z] { \
[2024-11-16T03:33:21.291Z] echo ""; echo "TEST SETUP:"; \
[2024-11-16T03:33:21.291Z] echo "Nothing to be done for setup."; \
[2024-11-16T03:33:21.291Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17317268621572/renaissance-movie-lens_0"; \
[2024-11-16T03:33:21.291Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17317268621572/renaissance-movie-lens_0"; \
[2024-11-16T03:33:21.291Z] echo ""; echo "TESTING:"; \
[2024-11-16T03:33:21.291Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/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_s390x_linux/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17317268621572/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-11-16T03:33:21.291Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17317268621572/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-11-16T03:33:21.291Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-11-16T03:33:21.291Z] echo "Nothing to be done for teardown."; \
[2024-11-16T03:33:21.291Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_s390x_linux/aqa-tests/TKG/../TKG/output_17317268621572/TestTargetResult";
[2024-11-16T03:33:21.291Z]
[2024-11-16T03:33:21.291Z] TEST SETUP:
[2024-11-16T03:33:21.291Z] Nothing to be done for setup.
[2024-11-16T03:33:21.291Z]
[2024-11-16T03:33:21.291Z] TESTING:
[2024-11-16T03:33:24.666Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-11-16T03:33:26.065Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 2 (out of 2) threads.
[2024-11-16T03:33:30.203Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-11-16T03:33:30.204Z] Training: 60056, validation: 20285, test: 19854
[2024-11-16T03:33:30.204Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-11-16T03:33:30.204Z] GC before operation: completed in 170.789 ms, heap usage 69.864 MB -> 36.409 MB.
[2024-11-16T03:33:37.710Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:33:42.680Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:33:46.590Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:33:50.481Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:33:52.673Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:33:54.110Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:33:56.253Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:33:58.407Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:33:58.407Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:33:59.055Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:33:59.055Z] Movies recommended for you:
[2024-11-16T03:33:59.055Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:33:59.055Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:33:59.055Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (28633.678 ms) ======
[2024-11-16T03:33:59.055Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-11-16T03:33:59.055Z] GC before operation: completed in 126.244 ms, heap usage 148.119 MB -> 50.361 MB.
[2024-11-16T03:34:03.050Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:34:06.021Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:34:09.981Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:34:12.932Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:34:14.344Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:34:16.459Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:34:17.842Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:34:20.785Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:34:20.785Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:34:20.785Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:34:20.785Z] Movies recommended for you:
[2024-11-16T03:34:20.785Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:34:20.785Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:34:20.785Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (21658.610 ms) ======
[2024-11-16T03:34:20.785Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-11-16T03:34:20.785Z] GC before operation: completed in 142.519 ms, heap usage 221.496 MB -> 48.533 MB.
[2024-11-16T03:34:23.841Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:34:26.934Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:34:30.018Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:34:32.956Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:34:34.351Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:34:35.705Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:34:37.871Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:34:39.215Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:34:39.935Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:34:39.935Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:34:39.935Z] Movies recommended for you:
[2024-11-16T03:34:39.935Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:34:39.935Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:34:39.935Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (18881.962 ms) ======
[2024-11-16T03:34:39.935Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-11-16T03:34:39.935Z] GC before operation: completed in 132.625 ms, heap usage 220.764 MB -> 48.782 MB.
[2024-11-16T03:34:42.873Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:34:45.543Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:34:48.585Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:34:51.556Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:34:53.672Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:34:55.058Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:34:57.161Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:34:58.556Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:34:59.229Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:34:59.229Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:34:59.229Z] Movies recommended for you:
[2024-11-16T03:34:59.229Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:34:59.229Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:34:59.229Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (19276.484 ms) ======
[2024-11-16T03:34:59.229Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-11-16T03:34:59.229Z] GC before operation: completed in 153.994 ms, heap usage 139.786 MB -> 49.001 MB.
[2024-11-16T03:35:02.273Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:35:05.201Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:35:08.189Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:35:11.189Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:35:12.556Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:35:13.891Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:35:16.020Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:35:17.391Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:35:17.391Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:35:17.391Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:35:17.391Z] Movies recommended for you:
[2024-11-16T03:35:17.391Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:35:17.391Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:35:17.391Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (18316.432 ms) ======
[2024-11-16T03:35:17.391Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-11-16T03:35:18.046Z] GC before operation: completed in 153.803 ms, heap usage 274.749 MB -> 49.349 MB.
[2024-11-16T03:35:21.021Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:35:24.009Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:35:27.036Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:35:30.036Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:35:31.466Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:35:33.595Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:35:35.760Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:35:37.149Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:35:37.149Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:35:37.149Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:35:37.149Z] Movies recommended for you:
[2024-11-16T03:35:37.149Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:35:37.149Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:35:37.149Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (19443.633 ms) ======
[2024-11-16T03:35:37.149Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-11-16T03:35:37.149Z] GC before operation: completed in 136.239 ms, heap usage 62.583 MB -> 49.010 MB.
[2024-11-16T03:35:41.091Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:35:44.067Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:35:47.203Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:35:50.188Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:35:52.395Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:35:53.787Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:35:55.987Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:35:57.434Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:35:58.110Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:35:58.110Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:35:58.110Z] Movies recommended for you:
[2024-11-16T03:35:58.110Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:35:58.110Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:35:58.110Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (20549.161 ms) ======
[2024-11-16T03:35:58.110Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-11-16T03:35:58.110Z] GC before operation: completed in 170.054 ms, heap usage 137.573 MB -> 49.305 MB.
[2024-11-16T03:36:02.577Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:36:04.792Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:36:07.752Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:36:10.792Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:36:12.188Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:36:14.303Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:36:16.394Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:36:17.800Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:36:18.550Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:36:18.550Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:36:18.550Z] Movies recommended for you:
[2024-11-16T03:36:18.550Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:36:18.550Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:36:18.550Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (20438.725 ms) ======
[2024-11-16T03:36:18.550Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-11-16T03:36:18.550Z] GC before operation: completed in 180.121 ms, heap usage 62.287 MB -> 49.753 MB.
[2024-11-16T03:36:22.572Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:36:25.603Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:36:29.601Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:36:32.602Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:36:33.944Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:36:36.073Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:36:37.445Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:36:39.604Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:36:39.604Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:36:39.604Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:36:39.604Z] Movies recommended for you:
[2024-11-16T03:36:39.604Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:36:39.604Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:36:39.604Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21081.504 ms) ======
[2024-11-16T03:36:39.604Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-11-16T03:36:40.248Z] GC before operation: completed in 160.685 ms, heap usage 144.129 MB -> 49.439 MB.
[2024-11-16T03:36:43.187Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:36:46.163Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:36:50.107Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:36:53.086Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:36:54.453Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:36:55.853Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:36:57.994Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:37:00.147Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:37:00.147Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:37:00.147Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:37:00.147Z] Movies recommended for you:
[2024-11-16T03:37:00.147Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:37:00.147Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:37:00.147Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (20360.831 ms) ======
[2024-11-16T03:37:00.147Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-11-16T03:37:00.776Z] GC before operation: completed in 178.339 ms, heap usage 113.724 MB -> 49.485 MB.
[2024-11-16T03:37:03.786Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:37:07.777Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:37:10.795Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:37:14.660Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:37:16.063Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:37:18.191Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:37:20.827Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:37:22.193Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:37:22.847Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:37:22.847Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:37:22.848Z] Movies recommended for you:
[2024-11-16T03:37:22.848Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:37:22.848Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:37:22.848Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (22241.523 ms) ======
[2024-11-16T03:37:22.848Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-11-16T03:37:22.848Z] GC before operation: completed in 205.877 ms, heap usage 235.007 MB -> 49.425 MB.
[2024-11-16T03:37:26.746Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:37:30.870Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:37:33.920Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:37:36.491Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:37:38.674Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:37:40.967Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:37:42.413Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:37:43.811Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:37:44.480Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:37:44.480Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:37:44.480Z] Movies recommended for you:
[2024-11-16T03:37:44.480Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:37:44.480Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:37:44.480Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (21468.479 ms) ======
[2024-11-16T03:37:44.480Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-11-16T03:37:44.480Z] GC before operation: completed in 196.526 ms, heap usage 181.711 MB -> 49.446 MB.
[2024-11-16T03:37:48.427Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:37:52.562Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:37:55.610Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:37:58.636Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:38:00.851Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:38:02.290Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:38:04.544Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:38:05.945Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:38:06.618Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:38:06.618Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:38:06.618Z] Movies recommended for you:
[2024-11-16T03:38:06.618Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:38:06.618Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:38:06.618Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (21783.783 ms) ======
[2024-11-16T03:38:06.618Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-11-16T03:38:06.618Z] GC before operation: completed in 180.162 ms, heap usage 117.117 MB -> 49.542 MB.
[2024-11-16T03:38:09.651Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:38:12.705Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:38:15.717Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:38:18.767Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:38:20.958Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:38:23.142Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:38:24.553Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:38:25.968Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:38:26.679Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:38:26.679Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:38:26.679Z] Movies recommended for you:
[2024-11-16T03:38:26.679Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:38:26.679Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:38:26.680Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (20183.741 ms) ======
[2024-11-16T03:38:26.680Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-11-16T03:38:27.358Z] GC before operation: completed in 209.387 ms, heap usage 172.543 MB -> 49.377 MB.
[2024-11-16T03:38:30.384Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:38:33.402Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:38:36.439Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:38:39.505Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:38:41.358Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:38:42.789Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:38:44.990Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:38:47.226Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:38:47.226Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:38:47.226Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:38:47.226Z] Movies recommended for you:
[2024-11-16T03:38:47.226Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:38:47.226Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:38:47.226Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (20338.855 ms) ======
[2024-11-16T03:38:47.226Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-11-16T03:38:47.877Z] GC before operation: completed in 190.274 ms, heap usage 241.538 MB -> 49.597 MB.
[2024-11-16T03:38:51.895Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:38:55.044Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:38:58.053Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:39:01.078Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:39:03.282Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:39:04.637Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:39:06.853Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:39:08.285Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:39:08.979Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:39:08.979Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:39:08.979Z] Movies recommended for you:
[2024-11-16T03:39:08.979Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:39:08.979Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:39:08.979Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21371.582 ms) ======
[2024-11-16T03:39:08.979Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-11-16T03:39:08.979Z] GC before operation: completed in 161.984 ms, heap usage 196.454 MB -> 49.633 MB.
[2024-11-16T03:39:12.973Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:39:15.189Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:39:19.252Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:39:22.364Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:39:23.875Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:39:26.037Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:39:28.264Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:39:29.662Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:39:29.662Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:39:29.662Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:39:30.351Z] Movies recommended for you:
[2024-11-16T03:39:30.351Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:39:30.351Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:39:30.351Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (20917.829 ms) ======
[2024-11-16T03:39:30.351Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-11-16T03:39:30.351Z] GC before operation: completed in 157.961 ms, heap usage 148.971 MB -> 49.445 MB.
[2024-11-16T03:39:33.413Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:39:36.520Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:39:39.568Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:39:42.607Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:39:44.002Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:39:46.158Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:39:47.530Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:39:49.660Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:39:49.660Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:39:49.660Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:39:49.660Z] Movies recommended for you:
[2024-11-16T03:39:49.660Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:39:49.660Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:39:49.660Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (19543.359 ms) ======
[2024-11-16T03:39:49.660Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-11-16T03:39:49.660Z] GC before operation: completed in 170.483 ms, heap usage 146.986 MB -> 49.518 MB.
[2024-11-16T03:39:53.653Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:39:55.651Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:39:58.617Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:40:01.636Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:40:03.790Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:40:05.163Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:40:07.340Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:40:08.740Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:40:08.741Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:40:08.741Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:40:09.415Z] Movies recommended for you:
[2024-11-16T03:40:09.415Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:40:09.415Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:40:09.415Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (19270.103 ms) ======
[2024-11-16T03:40:09.415Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-11-16T03:40:09.415Z] GC before operation: completed in 164.028 ms, heap usage 148.885 MB -> 49.687 MB.
[2024-11-16T03:40:12.487Z] RMSE (validation) = 3.621968954548762 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-11-16T03:40:15.522Z] RMSE (validation) = 2.134092321459638 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-11-16T03:40:18.490Z] RMSE (validation) = 1.3105186097961345 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-11-16T03:40:21.528Z] RMSE (validation) = 1.0039112263869625 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-11-16T03:40:22.922Z] RMSE (validation) = 1.2279489569306759 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-11-16T03:40:24.311Z] RMSE (validation) = 1.1317743270958185 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-11-16T03:40:26.444Z] RMSE (validation) = 0.9270299248067019 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-11-16T03:40:27.818Z] RMSE (validation) = 0.8979370339906045 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-11-16T03:40:28.487Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9082701964919572.
[2024-11-16T03:40:28.487Z] The best model improves the baseline by 14.34%.
[2024-11-16T03:40:28.487Z] Movies recommended for you:
[2024-11-16T03:40:28.487Z] WARNING: This benchmark provides no result that can be validated.
[2024-11-16T03:40:28.487Z] There is no way to check that no silent failure occurred.
[2024-11-16T03:40:28.487Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (19161.879 ms) ======
[2024-11-16T03:40:29.180Z] -----------------------------------
[2024-11-16T03:40:29.180Z] renaissance-movie-lens_0_PASSED
[2024-11-16T03:40:29.180Z] -----------------------------------
[2024-11-16T03:40:29.180Z]
[2024-11-16T03:40:29.180Z] TEST TEARDOWN:
[2024-11-16T03:40:29.180Z] Nothing to be done for teardown.
[2024-11-16T03:40:29.180Z] renaissance-movie-lens_0 Finish Time: Fri Nov 15 22:40:28 2024 Epoch Time (ms): 1731728428613