Result table

This table was generated on 2023-10-11 at 05:26. See more results here. See last results here.

results

project_name group_name hostname status Time RMSE Accuracy error_msg deeprec Master-IASD boldeagle Success 36.27 0.861 0.0 None goat Master-IASD boldeagle Success 106.95 0.863 0.1 None bot Master-IASD boldeagle Success 32.49 0.878 0.2 None prestige-worldwide Master-IASD boldeagle Success 24.73 0.886 25.64 None matrix-brigade Master-IASD boldeagle Success 104.87 0.89 24.86 None a-m-y-group Master-IASD boldeagle Success 55.06 0.903 0.0 None descente-optimale Master-IASD boldeagle Success 18.58 0.923 21.83 None la-grosse-descente Master-IASD boldeagle Success 124.96 0.929 0.0 None forecastors Master-IASD boldeagle Success 20.94 0.971 29.86 None deepdeepmf Master-IASD boldeagle Success 0.57 1.037 0.0 None average profs boldeagle Success 0.58 1.037 0.0 None random profs boldeagle Success 0.56 1.833 14.08 None claraliorarafael Master-IASD boldeagle Success 180.57 2.983 0.0 None equipe-404 Master-IASD boldeagle Error 0 100 0 bytes: b' File "/home/lamsade/testplatform/test-platform-a1/repos/Master-IASD/equipe-404/generate.py", line 75\n return R_pred\n ^^^^^^^^^^^^^\nSyntaxError: \'return\' outside function\n' lecun-team Master-IASD boldeagle Error 0 100 0 bytes: b'Traceback (most recent call last):\n File "/home/lamsade/testplatform/test-platform-a1/repos/Master-IASD/lecun-team/generate.py", line 39, in \n model.make_output(batch_size = 65536, tqdm_on = False)\n File "/home/lamsade/testplatform/test-platform-a1/repos/Master-IASD/lecun-team/algorithms/folded_deep_matrix_factorization_imprv.py", line 318, in make_output\n test_users_features_batch = test_users_explicit_ds / 5\n ~~~~~~~~~~~~~~~~~~~~~~~^~~\ntorch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.22 GiB (GPU 0; 10.91 GiB total capacity; 3.26 GiB already allocated; 110.12 MiB free; 4.26 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF\n' the-boring-group Master-IASD boldeagle Success 144.07 nan 0.0 None

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