renaissance-movie-lens_0
[2024-08-10T00:32:20.031Z] Running test renaissance-movie-lens_0 ...
[2024-08-10T00:32:20.031Z] ===============================================
[2024-08-10T00:32:20.031Z] renaissance-movie-lens_0 Start Time: Sat Aug 10 00:32:19 2024 Epoch Time (ms): 1723249939638
[2024-08-10T00:32:20.031Z] variation: NoOptions
[2024-08-10T00:32:20.031Z] JVM_OPTIONS:
[2024-08-10T00:32:20.031Z] { \
[2024-08-10T00:32:20.031Z] echo ""; echo "TEST SETUP:"; \
[2024-08-10T00:32:20.031Z] echo "Nothing to be done for setup."; \
[2024-08-10T00:32:20.031Z] mkdir -p "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232487606933/renaissance-movie-lens_0"; \
[2024-08-10T00:32:20.031Z] cd "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232487606933/renaissance-movie-lens_0"; \
[2024-08-10T00:32:20.031Z] echo ""; echo "TESTING:"; \
[2024-08-10T00:32:20.031Z] "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/jdkbinary/j2sdk-image/bin/java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../../jvmtest/perf/renaissance/renaissance.jar" --json ""/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232487606933/renaissance-movie-lens_0"/movie-lens.json" movie-lens; \
[2024-08-10T00:32:20.031Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd /home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/..; rm -f -r "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232487606933/renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \
[2024-08-10T00:32:20.031Z] echo ""; echo "TEST TEARDOWN:"; \
[2024-08-10T00:32:20.031Z] echo "Nothing to be done for teardown."; \
[2024-08-10T00:32:20.031Z] } 2>&1 | tee -a "/home/jenkins/workspace/Test_openjdk11_hs_extended.perf_aarch64_linux_testList_0/aqa-tests/TKG/../TKG/output_17232487606933/TestTargetResult";
[2024-08-10T00:32:20.031Z]
[2024-08-10T00:32:20.031Z] TEST SETUP:
[2024-08-10T00:32:20.031Z] Nothing to be done for setup.
[2024-08-10T00:32:20.031Z]
[2024-08-10T00:32:20.031Z] TESTING:
[2024-08-10T00:32:25.372Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
[2024-08-10T00:32:29.498Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 8 (out of 8) threads.
[2024-08-10T00:32:36.868Z] Got 100004 ratings from 671 users on 9066 movies.
[2024-08-10T00:32:36.868Z] Training: 60056, validation: 20285, test: 19854
[2024-08-10T00:32:36.868Z] ====== movie-lens (apache-spark) [default], iteration 0 started ======
[2024-08-10T00:32:36.868Z] GC before operation: completed in 106.016 ms, heap usage 52.340 MB -> 37.176 MB.
[2024-08-10T00:32:48.540Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:32:53.901Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:32:59.269Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:33:03.405Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:33:06.426Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:33:09.430Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:33:11.377Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:33:14.378Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:33:14.378Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:33:14.378Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:33:14.378Z] Movies recommended for you:
[2024-08-10T00:33:14.378Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:33:14.378Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:33:14.378Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (37899.348 ms) ======
[2024-08-10T00:33:14.378Z] ====== movie-lens (apache-spark) [default], iteration 1 started ======
[2024-08-10T00:33:15.332Z] GC before operation: completed in 228.097 ms, heap usage 104.034 MB -> 53.584 MB.
[2024-08-10T00:33:19.467Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:33:23.602Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:33:27.742Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:33:30.747Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:33:32.733Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:33:35.735Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:33:38.378Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:33:40.337Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:33:41.284Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:33:41.284Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:33:41.284Z] Movies recommended for you:
[2024-08-10T00:33:41.284Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:33:41.284Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:33:41.284Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (26063.151 ms) ======
[2024-08-10T00:33:41.284Z] ====== movie-lens (apache-spark) [default], iteration 2 started ======
[2024-08-10T00:33:41.284Z] GC before operation: completed in 213.725 ms, heap usage 365.657 MB -> 51.004 MB.
[2024-08-10T00:33:45.418Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:33:48.420Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:33:52.560Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:33:55.569Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:33:57.692Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:33:59.639Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:34:01.593Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:34:04.596Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:34:04.596Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:34:04.596Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:34:04.596Z] Movies recommended for you:
[2024-08-10T00:34:04.596Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:34:04.596Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:34:04.596Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (23359.045 ms) ======
[2024-08-10T00:34:04.596Z] ====== movie-lens (apache-spark) [default], iteration 3 started ======
[2024-08-10T00:34:04.596Z] GC before operation: completed in 180.330 ms, heap usage 341.270 MB -> 51.414 MB.
[2024-08-10T00:34:08.774Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:34:11.780Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:34:14.784Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:34:17.799Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:34:20.932Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:34:21.885Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:34:24.889Z] RMSE (validation) = 0.927571739133814 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:34:25.836Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:34:26.784Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:34:26.784Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:34:26.784Z] Movies recommended for you:
[2024-08-10T00:34:26.784Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:34:26.784Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:34:26.784Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (21728.407 ms) ======
[2024-08-10T00:34:26.784Z] ====== movie-lens (apache-spark) [default], iteration 4 started ======
[2024-08-10T00:34:26.784Z] GC before operation: completed in 191.787 ms, heap usage 557.097 MB -> 55.157 MB.
[2024-08-10T00:34:29.790Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:34:33.926Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:34:36.573Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:34:39.580Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:34:41.528Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:34:43.471Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:34:45.421Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:34:48.464Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:34:48.464Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:34:48.464Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:34:48.464Z] Movies recommended for you:
[2024-08-10T00:34:48.464Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:34:48.464Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:34:48.464Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (21708.966 ms) ======
[2024-08-10T00:34:48.465Z] ====== movie-lens (apache-spark) [default], iteration 5 started ======
[2024-08-10T00:34:48.465Z] GC before operation: completed in 220.445 ms, heap usage 262.904 MB -> 51.890 MB.
[2024-08-10T00:34:52.601Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:34:55.609Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:34:58.615Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:35:01.622Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:35:03.567Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:35:05.512Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:35:08.518Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:35:09.466Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:35:10.414Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:35:10.414Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:35:10.414Z] Movies recommended for you:
[2024-08-10T00:35:10.414Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:35:10.414Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:35:10.414Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (21760.513 ms) ======
[2024-08-10T00:35:10.414Z] ====== movie-lens (apache-spark) [default], iteration 6 started ======
[2024-08-10T00:35:10.414Z] GC before operation: completed in 185.992 ms, heap usage 180.687 MB -> 54.917 MB.
[2024-08-10T00:35:14.554Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:35:17.555Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:35:20.724Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:35:23.730Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:35:25.690Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:35:27.633Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:35:29.579Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:35:31.524Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:35:32.474Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:35:32.474Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:35:32.474Z] Movies recommended for you:
[2024-08-10T00:35:32.474Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:35:32.474Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:35:32.474Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (21683.523 ms) ======
[2024-08-10T00:35:32.474Z] ====== movie-lens (apache-spark) [default], iteration 7 started ======
[2024-08-10T00:35:32.474Z] GC before operation: completed in 184.815 ms, heap usage 254.736 MB -> 51.893 MB.
[2024-08-10T00:35:35.484Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:35:39.219Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:35:42.240Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:35:45.252Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:35:47.201Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:35:49.151Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:35:52.169Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:35:54.121Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:35:54.121Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:35:54.121Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:35:54.121Z] Movies recommended for you:
[2024-08-10T00:35:54.121Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:35:54.121Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:35:54.121Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (21786.044 ms) ======
[2024-08-10T00:35:54.121Z] ====== movie-lens (apache-spark) [default], iteration 8 started ======
[2024-08-10T00:35:54.121Z] GC before operation: completed in 203.596 ms, heap usage 259.782 MB -> 52.180 MB.
[2024-08-10T00:35:58.267Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:36:01.281Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:36:04.296Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:36:07.308Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:36:10.321Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:36:12.276Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:36:14.229Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:36:16.196Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:36:16.196Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:36:16.196Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:36:16.196Z] Movies recommended for you:
[2024-08-10T00:36:16.196Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:36:16.196Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:36:16.196Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (21958.613 ms) ======
[2024-08-10T00:36:16.196Z] ====== movie-lens (apache-spark) [default], iteration 9 started ======
[2024-08-10T00:36:16.196Z] GC before operation: completed in 202.718 ms, heap usage 251.244 MB -> 52.054 MB.
[2024-08-10T00:36:20.343Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:36:23.359Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:36:26.371Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:36:29.380Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:36:31.328Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:36:33.279Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:36:35.231Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:36:38.591Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:36:38.592Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:36:38.592Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:36:38.592Z] Movies recommended for you:
[2024-08-10T00:36:38.592Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:36:38.592Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:36:38.592Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (21668.354 ms) ======
[2024-08-10T00:36:38.592Z] ====== movie-lens (apache-spark) [default], iteration 10 started ======
[2024-08-10T00:36:38.592Z] GC before operation: completed in 230.472 ms, heap usage 204.048 MB -> 52.195 MB.
[2024-08-10T00:36:41.606Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:36:45.751Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:36:48.760Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:36:51.767Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:36:53.717Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:36:55.667Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:36:57.616Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:36:59.564Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:37:00.514Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:37:00.514Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:37:00.514Z] Movies recommended for you:
[2024-08-10T00:37:00.514Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:37:00.514Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:37:00.514Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (21756.014 ms) ======
[2024-08-10T00:37:00.514Z] ====== movie-lens (apache-spark) [default], iteration 11 started ======
[2024-08-10T00:37:00.515Z] GC before operation: completed in 193.034 ms, heap usage 606.036 MB -> 55.313 MB.
[2024-08-10T00:37:03.524Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:37:06.534Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:37:10.679Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:37:13.697Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:37:14.648Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:37:16.779Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:37:18.731Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:37:20.697Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:37:21.647Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:37:21.647Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:37:21.647Z] Movies recommended for you:
[2024-08-10T00:37:21.647Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:37:21.647Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:37:21.647Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (20950.581 ms) ======
[2024-08-10T00:37:21.647Z] ====== movie-lens (apache-spark) [default], iteration 12 started ======
[2024-08-10T00:37:21.647Z] GC before operation: completed in 202.311 ms, heap usage 75.857 MB -> 55.443 MB.
[2024-08-10T00:37:24.656Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:37:27.667Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:37:30.690Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:37:34.835Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:37:35.785Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:37:38.436Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:37:40.384Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:37:42.509Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:37:42.509Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:37:42.509Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:37:42.509Z] Movies recommended for you:
[2024-08-10T00:37:42.509Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:37:42.509Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:37:42.509Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (20796.950 ms) ======
[2024-08-10T00:37:42.509Z] ====== movie-lens (apache-spark) [default], iteration 13 started ======
[2024-08-10T00:37:42.509Z] GC before operation: completed in 200.602 ms, heap usage 579.429 MB -> 55.712 MB.
[2024-08-10T00:37:45.517Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:37:49.649Z] RMSE (validation) = 2.1340923217118064 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:37:52.658Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:37:55.667Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:37:57.632Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:37:59.584Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:38:01.531Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:38:03.480Z] RMSE (validation) = 0.9001440981626694 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:38:03.480Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:38:03.480Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:38:03.480Z] Movies recommended for you:
[2024-08-10T00:38:03.480Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:38:03.480Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:38:03.480Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (21186.446 ms) ======
[2024-08-10T00:38:03.480Z] ====== movie-lens (apache-spark) [default], iteration 14 started ======
[2024-08-10T00:38:04.428Z] GC before operation: completed in 212.989 ms, heap usage 295.307 MB -> 51.987 MB.
[2024-08-10T00:38:07.437Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:38:10.445Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:38:13.458Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:38:16.473Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:38:19.482Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:38:21.430Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:38:23.383Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:38:25.331Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:38:25.331Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:38:25.331Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:38:25.331Z] Movies recommended for you:
[2024-08-10T00:38:25.331Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:38:25.331Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:38:25.332Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (21587.075 ms) ======
[2024-08-10T00:38:25.332Z] ====== movie-lens (apache-spark) [default], iteration 15 started ======
[2024-08-10T00:38:26.281Z] GC before operation: completed in 247.362 ms, heap usage 297.393 MB -> 52.248 MB.
[2024-08-10T00:38:29.309Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:38:32.314Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:38:35.325Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:38:38.754Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:38:40.706Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:38:42.662Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:38:45.673Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:38:46.623Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:38:47.574Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:38:47.574Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:38:47.574Z] Movies recommended for you:
[2024-08-10T00:38:47.574Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:38:47.574Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:38:47.574Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (21772.033 ms) ======
[2024-08-10T00:38:47.574Z] ====== movie-lens (apache-spark) [default], iteration 16 started ======
[2024-08-10T00:38:47.574Z] GC before operation: completed in 200.408 ms, heap usage 235.157 MB -> 52.268 MB.
[2024-08-10T00:38:51.717Z] RMSE (validation) = 3.6219689545487506 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:38:54.728Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:38:57.744Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:39:00.756Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:39:02.706Z] RMSE (validation) = 1.2218330581874073 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:39:04.655Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:39:06.605Z] RMSE (validation) = 0.9275717391338142 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:39:08.555Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:39:09.504Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:39:09.504Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:39:09.504Z] Movies recommended for you:
[2024-08-10T00:39:09.504Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:39:09.504Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:39:09.504Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (21684.613 ms) ======
[2024-08-10T00:39:09.504Z] ====== movie-lens (apache-spark) [default], iteration 17 started ======
[2024-08-10T00:39:09.504Z] GC before operation: completed in 194.766 ms, heap usage 303.204 MB -> 52.128 MB.
[2024-08-10T00:39:13.650Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:39:16.674Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:39:19.875Z] RMSE (validation) = 1.3105189674610933 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:39:22.446Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:39:24.392Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:39:26.344Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:39:28.299Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:39:30.248Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:39:31.197Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:39:31.197Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:39:31.197Z] Movies recommended for you:
[2024-08-10T00:39:31.197Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:39:31.197Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:39:31.197Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (21373.789 ms) ======
[2024-08-10T00:39:31.197Z] ====== movie-lens (apache-spark) [default], iteration 18 started ======
[2024-08-10T00:39:31.197Z] GC before operation: completed in 212.701 ms, heap usage 96.961 MB -> 53.963 MB.
[2024-08-10T00:39:34.206Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:39:38.347Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:39:41.379Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:39:44.383Z] RMSE (validation) = 1.0045407748005193 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:39:46.332Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:39:48.280Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:39:50.232Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:39:52.184Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:39:52.184Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:39:52.184Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:39:53.133Z] Movies recommended for you:
[2024-08-10T00:39:53.133Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:39:53.133Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:39:53.133Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (21446.549 ms) ======
[2024-08-10T00:39:53.133Z] ====== movie-lens (apache-spark) [default], iteration 19 started ======
[2024-08-10T00:39:53.133Z] GC before operation: completed in 207.178 ms, heap usage 165.221 MB -> 52.268 MB.
[2024-08-10T00:39:56.144Z] RMSE (validation) = 3.621968954548751 for the model trained with rank = 8, lambda = 5.0, and numIter = 20.
[2024-08-10T00:40:00.324Z] RMSE (validation) = 2.134092321711807 for the model trained with rank = 10, lambda = 2.0, and numIter = 20.
[2024-08-10T00:40:03.339Z] RMSE (validation) = 1.3105189674610935 for the model trained with rank = 12, lambda = 1.0, and numIter = 20.
[2024-08-10T00:40:06.351Z] RMSE (validation) = 1.004540774800519 for the model trained with rank = 8, lambda = 0.05, and numIter = 20.
[2024-08-10T00:40:08.301Z] RMSE (validation) = 1.2218330581874075 for the model trained with rank = 10, lambda = 0.01, and numIter = 10.
[2024-08-10T00:40:10.250Z] RMSE (validation) = 1.1174953766371012 for the model trained with rank = 8, lambda = 0.02, and numIter = 10.
[2024-08-10T00:40:11.200Z] RMSE (validation) = 0.9275717391338141 for the model trained with rank = 12, lambda = 0.1, and numIter = 10.
[2024-08-10T00:40:13.149Z] RMSE (validation) = 0.9001440981626695 for the model trained with rank = 8, lambda = 0.2, and numIter = 10.
[2024-08-10T00:40:14.097Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9073522634082535.
[2024-08-10T00:40:14.097Z] The best model improves the baseline by 14.43%.
[2024-08-10T00:40:14.097Z] Movies recommended for you:
[2024-08-10T00:40:14.098Z] WARNING: This benchmark provides no result that can be validated.
[2024-08-10T00:40:14.098Z] There is no way to check that no silent failure occurred.
[2024-08-10T00:40:14.098Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (20937.993 ms) ======
[2024-08-10T00:40:16.048Z] -----------------------------------
[2024-08-10T00:40:16.048Z] renaissance-movie-lens_0_PASSED
[2024-08-10T00:40:16.048Z] -----------------------------------
[2024-08-10T00:40:16.048Z]
[2024-08-10T00:40:16.048Z] TEST TEARDOWN:
[2024-08-10T00:40:16.048Z] Nothing to be done for teardown.
[2024-08-10T00:40:16.048Z] renaissance-movie-lens_0 Finish Time: Sat Aug 10 00:40:15 2024 Epoch Time (ms): 1723250415696