renaissance-movie-lens_0
[2024-08-21T21:46:11.257Z] Running test renaissance-movie-lens_0 ...
[2024-08-21T21:46:11.257Z] ===============================================
[2024-08-21T21:46:11.257Z] renaissance-movie-lens_0 Start Time: Wed Aug 21 17:46:10 2024 Epoch Time (ms): 1724276770732
[2024-08-21T21:46:11.257Z] variation: NoOptions
[2024-08-21T21:46:11.257Z] JVM_OPTIONS:
[2024-08-21T21:46:11.257Z] { \
[2024-08-21T21:46:11.257Z] echo ""; echo "TEST SETUP:"; \
[2024-08-21T21:46:11.257Z] echo "Nothing to be done for setup."; \
[2024-08-21T21:46:11.257Z] mkdir -p "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17242763514565/renaissance-movie-lens_0"; \
[2024-08-21T21:46:11.257Z] cd "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17242763514565/renaissance-movie-lens_0"; \
[2024-08-21T21:46:11.257Z] echo ""; echo "TESTING:"; \
[2024-08-21T21:46:11.257Z] "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/jdkbinary/j2sdk-image/Contents/Home/bin/..//bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17242763514565/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-21T21:46:11.257Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/..; rm -f -r "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17242763514565/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-21T21:46:11.257Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-21T21:46:11.257Z] echo "Nothing to be done for teardown."; \
[2024-08-21T21:46:11.257Z] } 2>&1 | tee -a "/Users/admin/workspace/workspace/Test_openjdk11_hs_extended.perf_aarch64_mac/aqa-tests/TKG/../TKG/output_17242763514565/TestTargetResult";
[2024-08-21T21:46:11.257Z]
[2024-08-21T21:46:11.257Z] TEST SETUP:
[2024-08-21T21:46:11.257Z] Nothing to be done for setup.
[2024-08-21T21:46:11.257Z]
[2024-08-21T21:46:11.257Z] TESTING:
[2024-08-21T21:46:13.028Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-21T21:46:13.796Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 3 (out of 3) threads.
[2024-08-21T21:46:15.593Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-21T21:46:15.593Z] Training: 60056, validation: 20285, test: 19854
[2024-08-21T21:46:15.593Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-21T21:46:15.593Z] GC before operation: completed in 26.485 ms, heap usage 68.106 MB -> 36.568 MB.
[2024-08-21T21:46:18.748Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:46:20.557Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:46:21.803Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:46:23.598Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:46:24.508Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:46:25.269Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:46:26.054Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:46:26.837Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:46:27.198Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:46:27.198Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:46:27.198Z] Movies recommended for you:
[2024-08-21T21:46:27.198Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:46:27.198Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:46:27.198Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (11673.407 ms) ======
[2024-08-21T21:46:27.198Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-21T21:46:27.198Z] GC before operation: completed in 68.946 ms, heap usage 224.295 MB -> 49.329 MB.
[2024-08-21T21:46:28.980Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:46:30.244Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:46:31.483Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:46:33.290Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:46:33.646Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:46:34.417Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:46:35.184Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:46:36.412Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:46:36.412Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:46:36.412Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:46:36.412Z] Movies recommended for you:
[2024-08-21T21:46:36.412Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:46:36.412Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:46:36.412Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (9109.494 ms) ======
[2024-08-21T21:46:36.412Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-21T21:46:36.412Z] GC before operation: completed in 41.323 ms, heap usage 257.808 MB -> 48.938 MB.
[2024-08-21T21:46:37.755Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:46:39.542Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:46:40.802Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:46:42.049Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:46:42.830Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:46:44.066Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:46:44.854Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:46:45.634Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:46:45.634Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:46:45.634Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:46:45.634Z] Movies recommended for you:
[2024-08-21T21:46:45.634Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:46:45.634Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:46:45.634Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (9350.929 ms) ======
[2024-08-21T21:46:45.634Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-21T21:46:45.634Z] GC before operation: completed in 46.151 ms, heap usage 159.467 MB -> 49.263 MB.
[2024-08-21T21:46:47.412Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:46:48.673Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:46:49.935Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:46:51.699Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:46:52.480Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:46:53.262Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:46:54.047Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:46:54.955Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:46:54.955Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:46:54.955Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:46:54.955Z] Movies recommended for you:
[2024-08-21T21:46:54.955Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:46:54.955Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:46:54.955Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (9101.245 ms) ======
[2024-08-21T21:46:54.955Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-21T21:46:54.955Z] GC before operation: completed in 56.916 ms, heap usage 197.536 MB -> 49.593 MB.
[2024-08-21T21:46:56.730Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:46:57.968Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:46:59.230Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:00.472Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:01.243Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:02.021Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:02.818Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:03.592Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:03.954Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:03.954Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:03.954Z] Movies recommended for you:
[2024-08-21T21:47:03.954Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:03.954Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:03.954Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (8980.598 ms) ======
[2024-08-21T21:47:03.954Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-21T21:47:03.954Z] GC before operation: completed in 51.891 ms, heap usage 89.962 MB -> 51.662 MB.
[2024-08-21T21:47:05.789Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:47:07.040Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:47:08.310Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:09.097Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:10.347Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:10.708Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:11.947Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:12.755Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:12.755Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:12.755Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:12.755Z] Movies recommended for you:
[2024-08-21T21:47:12.755Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:12.755Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:12.755Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (8807.712 ms) ======
[2024-08-21T21:47:12.755Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-21T21:47:12.755Z] GC before operation: completed in 41.408 ms, heap usage 224.368 MB -> 49.754 MB.
[2024-08-21T21:47:14.559Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:47:15.796Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:47:17.039Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:18.290Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:19.532Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:20.304Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:21.088Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:21.872Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:21.872Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:21.872Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:22.233Z] Movies recommended for you:
[2024-08-21T21:47:22.233Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:22.233Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:22.233Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (9248.281 ms) ======
[2024-08-21T21:47:22.233Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-21T21:47:22.233Z] GC before operation: completed in 57.542 ms, heap usage 203.192 MB -> 49.854 MB.
[2024-08-21T21:47:23.509Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:47:24.760Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:47:26.174Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:27.436Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:28.708Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:29.079Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:30.333Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:31.102Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:31.102Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:31.102Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:31.102Z] Movies recommended for you:
[2024-08-21T21:47:31.102Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:31.102Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:31.102Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (9137.873 ms) ======
[2024-08-21T21:47:31.102Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-21T21:47:31.468Z] GC before operation: completed in 52.422 ms, heap usage 289.128 MB -> 50.228 MB.
[2024-08-21T21:47:32.739Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:47:33.975Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:47:35.224Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:37.016Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:37.801Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:38.574Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:39.352Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:40.119Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:40.119Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:40.119Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:40.119Z] Movies recommended for you:
[2024-08-21T21:47:40.119Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:40.119Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:40.119Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (8884.609 ms) ======
[2024-08-21T21:47:40.119Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-21T21:47:40.119Z] GC before operation: completed in 51.335 ms, heap usage 168.993 MB -> 49.946 MB.
[2024-08-21T21:47:41.925Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:47:43.184Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:47:44.457Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:45.699Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:46.946Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:47.712Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:48.481Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:49.289Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:49.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:49.647Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:49.647Z] Movies recommended for you:
[2024-08-21T21:47:49.647Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:49.647Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:49.647Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (9289.180 ms) ======
[2024-08-21T21:47:49.647Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-21T21:47:49.647Z] GC before operation: completed in 50.299 ms, heap usage 194.389 MB -> 50.029 MB.
[2024-08-21T21:47:50.889Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:47:52.671Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:47:53.929Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:47:55.196Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:47:56.435Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:47:57.210Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:47:57.989Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:47:58.767Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:47:58.767Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:47:59.124Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:47:59.124Z] Movies recommended for you:
[2024-08-21T21:47:59.124Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:47:59.124Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:47:59.124Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (9387.468 ms) ======
[2024-08-21T21:47:59.124Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-21T21:47:59.124Z] GC before operation: completed in 39.882 ms, heap usage 191.407 MB -> 49.772 MB.
[2024-08-21T21:48:00.386Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:01.634Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:02.897Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:04.140Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:04.934Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:05.722Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:06.490Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:07.266Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:07.266Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:07.266Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:07.266Z] Movies recommended for you:
[2024-08-21T21:48:07.266Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:07.266Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:07.266Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (8303.393 ms) ======
[2024-08-21T21:48:07.266Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-21T21:48:07.266Z] GC before operation: completed in 43.702 ms, heap usage 282.106 MB -> 50.051 MB.
[2024-08-21T21:48:08.512Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:10.304Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:11.560Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:12.831Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:13.602Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:14.379Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:15.161Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:15.942Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:15.942Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:15.942Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:15.942Z] Movies recommended for you:
[2024-08-21T21:48:15.942Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:15.942Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:15.942Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (8603.633 ms) ======
[2024-08-21T21:48:15.942Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-21T21:48:15.942Z] GC before operation: completed in 41.713 ms, heap usage 131.789 MB -> 50.014 MB.
[2024-08-21T21:48:17.755Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:18.519Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:20.333Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:21.103Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:21.888Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:22.666Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:23.461Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:24.242Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:24.242Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:24.242Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:24.242Z] Movies recommended for you:
[2024-08-21T21:48:24.242Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:24.242Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:24.242Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (8284.174 ms) ======
[2024-08-21T21:48:24.242Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-21T21:48:24.242Z] GC before operation: completed in 51.888 ms, heap usage 74.891 MB -> 49.792 MB.
[2024-08-21T21:48:25.485Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:26.862Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:28.102Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:29.905Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:30.263Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:31.036Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:32.282Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:32.644Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:33.001Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:33.001Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:33.001Z] Movies recommended for you:
[2024-08-21T21:48:33.001Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:33.001Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:33.001Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (8606.679 ms) ======
[2024-08-21T21:48:33.001Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-21T21:48:33.001Z] GC before operation: completed in 51.619 ms, heap usage 234.221 MB -> 50.149 MB.
[2024-08-21T21:48:34.258Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:36.094Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:37.342Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:38.598Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:39.384Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:40.156Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:40.924Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:42.183Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:42.183Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:42.183Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:42.183Z] Movies recommended for you:
[2024-08-21T21:48:42.183Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:42.183Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:42.183Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (9088.947 ms) ======
[2024-08-21T21:48:42.183Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-21T21:48:42.183Z] GC before operation: completed in 50.022 ms, heap usage 164.350 MB -> 50.156 MB.
[2024-08-21T21:48:43.430Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:44.682Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:46.478Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:47.292Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:48.066Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:48.838Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:49.624Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:50.415Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:50.415Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:50.415Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:50.775Z] Movies recommended for you:
[2024-08-21T21:48:50.775Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:50.775Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:50.775Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (8471.882 ms) ======
[2024-08-21T21:48:50.775Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-21T21:48:50.775Z] GC before operation: completed in 49.798 ms, heap usage 120.662 MB -> 49.905 MB.
[2024-08-21T21:48:52.038Z] RMSE (validation) = 3.6219689545487603 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:48:53.286Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:48:55.089Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:48:56.330Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:48:57.099Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:48:57.884Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:48:58.669Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:48:59.470Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:48:59.470Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:48:59.470Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:48:59.470Z] Movies recommended for you:
[2024-08-21T21:48:59.470Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:48:59.470Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:48:59.470Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (8800.218 ms) ======
[2024-08-21T21:48:59.470Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-21T21:48:59.470Z] GC before operation: completed in 49.122 ms, heap usage 118.428 MB -> 49.953 MB.
[2024-08-21T21:49:01.282Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:49:02.551Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:49:03.816Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:49:05.078Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:49:05.855Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:49:06.632Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:49:07.420Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:49:08.189Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:49:08.561Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:49:08.561Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:49:08.561Z] Movies recommended for you:
[2024-08-21T21:49:08.561Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:49:08.561Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:49:08.561Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (8966.613 ms) ======
[2024-08-21T21:49:08.561Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-21T21:49:08.561Z] GC before operation: completed in 66.148 ms, heap usage 301.637 MB -> 50.339 MB.
[2024-08-21T21:49:09.818Z] RMSE (validation) = 3.62196895454876 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-21T21:49:11.675Z] RMSE (validation) = 2.1340923221100736 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-21T21:49:12.942Z] RMSE (validation) = 1.3105190428502682 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-21T21:49:14.189Z] RMSE (validation) = 0.9920028100571827 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-21T21:49:14.961Z] RMSE (validation) = 1.212631715629696 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-21T21:49:15.734Z] RMSE (validation) = 1.1025694034386657 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-21T21:49:16.983Z] RMSE (validation) = 0.9259652469249674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-21T21:49:17.761Z] RMSE (validation) = 0.8982232214592321 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-21T21:49:17.761Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063003101263983.
[2024-08-21T21:49:17.761Z] The best model improves the baseline by 14.52%.
[2024-08-21T21:49:17.761Z] Movies recommended for you:
[2024-08-21T21:49:17.761Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-21T21:49:17.761Z] There is no way to check that no silent failure occurred.
[2024-08-21T21:49:17.761Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (9116.114 ms) ======
[2024-08-21T21:49:17.761Z] -----------------------------------
[2024-08-21T21:49:17.761Z] renaissance-movie-lens_0_PASSED
[2024-08-21T21:49:17.761Z] -----------------------------------
[2024-08-21T21:49:17.761Z]
[2024-08-21T21:49:17.761Z] TEST TEARDOWN:
[2024-08-21T21:49:17.761Z] Nothing to be done for teardown.
[2024-08-21T21:49:17.761Z] renaissance-movie-lens_0 Finish Time: Wed Aug 21 17:49:17 2024 Epoch Time (ms): 1724276957681