Result table

This table was generated on 2023-10-10 at 05:22. See more results here. See last results here.

results

project_name group_name hostname status Time RMSE Accuracy error_msg goat Master-IASD boldeagle Success 107.58 0.863 0.1 None deeprec Master-IASD boldeagle Success 33.4 0.87 25.71 None bot Master-IASD boldeagle Success 32.48 0.878 0.2 None the-boring-group Master-IASD boldeagle Success 107.76 0.879 29.14 None matrix-brigade Master-IASD boldeagle Success 105.87 0.889 24.81 None equipe-404 Master-IASD boldeagle Success 26.62 0.922 32.75 None descente-optimale Master-IASD boldeagle Success 19.67 0.93 21.16 None a-m-y-group Master-IASD boldeagle Success 0.79 0.958 1.92 None forecastors Master-IASD boldeagle Success 21.42 0.971 29.86 None prestige-worldwide Master-IASD boldeagle Success 32.15 0.98 26.01 None deepdeepmf Master-IASD boldeagle Success 0.56 1.037 0.0 None average profs boldeagle Success 0.61 1.037 0.0 None random profs boldeagle Success 0.58 1.833 13.85 None claraliorarafael 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/claraliorarafael/generate.py", line 40, in \n np.save("output.npy", predicted) ## DO NOT CHANGE THIS LINE\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File "/home/lamsade/testplatform/test-platform-a1/venv/lib/python3.11/site-packages/numpy/lib/npyio.py", line 545, in save\n arr = np.asanyarray(arr)\n ^^^^^^^^^^^^^^^^^^\n File "/home/lamsade/testplatform/test-platform-a1/venv/lib/python3.11/site-packages/torch/_tensor.py", line 970, in __array__\n return self.numpy()\n ^^^^^^^^^^^^\nRuntimeError: Can\'t call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead.\n' la-grosse-descente Master-IASD boldeagle Error 0 100 0 IndexError: index 610 is out of bounds for axis 1 with size 610 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 308, in make_output\n test_users_explicit_ds = self.R[test_users_idx].float()\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; 1.18 GiB free; 3.29 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'

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