Result table

This table was generated on 2024-09-26 at 16:05. See more results here. See last results here.

results

project_name group_name hostname status Time RMSE Accuracy error_msg freshtomatoes Master-IASD boldeagle Success 1.89 0.872 0.28 None code-brain-fuel Master-IASD boldeagle Success 32.7 0.885 0.0 None closeai Master-IASD boldeagle Success 0.56 1.037 0.0 None elcoma Master-IASD boldeagle Success 0.57 1.037 0.0 None elon Master-IASD boldeagle Success 0.54 1.037 0.0 None esi Master-IASD boldeagle Success 0.61 1.037 0.0 None just-do-it Master-IASD boldeagle Success 0.64 1.037 0.0 None matrixe Master-IASD boldeagle Success 0.64 1.037 0.0 None palm Master-IASD boldeagle Success 0.57 1.037 0.0 None anxisa Master-IASD boldeagle Success 0.66 5.004 0.0 None alexandre-verinotableandefficientmodel 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/alexandre-verinotableandefficientmodel/generate.py", line 39, in \n P, Q = torch_matrix_factorization_gradient_descent(sum_tensor, k, alpha, lambda_, mu, ratio)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/home/lamsade/testplatform/test-platform-a1/repos/Master-IASD/alexandre-verinotableandefficientmodel/tmf.py", line 28, in torch_matrix_factorization_gradient_descent\n R_t, R_val = utils.train_val(R_tensor, ratio)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/home/lamsade/testplatform/test-platform-a1/repos/Master-IASD/alexandre-verinotableandefficientmodel/utils.py", line 10, in train_val\n R_t = torch.where(mask, R, torch.full_like(R, float(\'nan\')))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nRuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!\n'

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