jd7h/dreamcraft3d 🔢🖼️📝✓ → 🖼️
About
DreamCraft3D is a text and image to 3D model. Dreamcraft3D uses DeepFloyd IF and Stable Zero123, non-commercial research-only models. Please make sure you read and abide to the relevant licenses before using it.
Example Output
Prompt:
"A green leafy plant in a striped terracotta pot"
Output
Performance Metrics
1345.15s
Prediction Time
1684.60s
Total Time
All Input Parameters
{
"image": "https://replicate.delivery/pbxt/KRr0hkRklSX0x5Uw8OFen0HWdAo7A4HMe2CYDt7isiDhw4jV/potted-plant.webp",
"prompt": "A green leafy plant in a striped terracotta pot",
"num_steps": 800,
"guidance_scale": 5,
"use_fast_configs": true
}
Input Parameters
- seed
- The seed to use for the generation. If not specified, a random value will be used.
- image (required)
- Image to generate a 3D object from.
- prompt (required)
- Prompt to generate a 3D object.
- num_steps
- Number of iterations to run the model for.
- guidance_scale
- The scale of the guidance loss. Higher values will result in more accurate meshes but may also result in artifacts.
- use_fast_configs
- Use fast configuration files. This is less precise but much faster than the original configuration.
Output Schema
Output
Example Execution Logs
Using seed 3731177029
Seed set to 3731177029
Preprocessing image...
[INFO] background removal...
[1;31m2024-02-22 13:40:23.104407995 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1831, index: 1, mask: {1, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.104414275 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1830, index: 0, mask: {48, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.104502865 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1832, index: 2, mask: {49, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.104535295 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1833, index: 3, mask: {2, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.104613524 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1834, index: 4, mask: {50, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.107023935 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1841, index: 11, mask: {6, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.107094724 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1842, index: 12, mask: {54, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.107029744 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1908, index: 78, mask: {87, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.107404823 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1844, index: 14, mask: {55, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.119497582 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1843, index: 13, mask: {7, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.107393863 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1914, index: 84, mask: {90, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.123661054 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1911, index: 81, mask: {41, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.123722614 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1909, index: 79, mask: {40, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.123701134 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1910, index: 80, mask: {88, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.127291970 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1916, index: 86, mask: {91, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.127624198 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1915, index: 85, mask: {43, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.130148067 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1912, index: 82, mask: {89, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.131521142 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1835, index: 5, mask: {3, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.135786034 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1902, index: 72, mask: {84, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.142269357 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1836, index: 6, mask: {51, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.147488775 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1919, index: 89, mask: {45, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.151492068 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1920, index: 90, mask: {93, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.151515108 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1845, index: 15, mask: {8, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.152578874 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1921, index: 91, mask: {46, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.155036124 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1922, index: 92, mask: {94, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.159492425 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1923, index: 93, mask: {47, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.159619344 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1847, index: 17, mask: {9, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.163491428 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1924, index: 94, mask: {95, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.167512541 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1848, index: 18, mask: {57, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.175204479 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1918, index: 88, mask: {92, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.175514908 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1849, index: 19, mask: {10, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.183547044 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1850, index: 20, mask: {58, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203673140 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1865, index: 35, mask: {18, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203714850 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1867, index: 37, mask: {19, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203730010 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1868, index: 38, mask: {67, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208804658 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1880, index: 50, mask: {73, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208933648 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1892, index: 62, mask: {79, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.211571717 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1896, index: 66, mask: {81, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.218757077 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1898, index: 68, mask: {82, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.219530623 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1899, index: 69, mask: {35, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.159503775 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1846, index: 16, mask: {56, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208690009 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1872, index: 42, mask: {69, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.135794754 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1903, index: 73, mask: {37, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208878768 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1887, index: 57, mask: {29, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208739099 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1876, index: 46, mask: {71, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.135799404 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1904, index: 74, mask: {85, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208820138 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1882, index: 52, mask: {74, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208661999 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1871, index: 41, mask: {21, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.211522277 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1894, index: 64, mask: {80, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.211549267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1895, index: 65, mask: {33, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208761849 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1877, index: 47, mask: {24, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.135804604 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1905, index: 75, mask: {38, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203705640 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1866, index: 36, mask: {66, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.211499897 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1893, index: 63, mask: {32, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.135809804 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1906, index: 76, mask: {86, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208906798 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1889, index: 59, mask: {30, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208719959 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1874, index: 44, mask: {70, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.135814794 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1907, index: 77, mask: {39, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.208775729 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1879, index: 49, mask: {25, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203510801 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1855, index: 25, mask: {13, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203596991 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1917, index: 87, mask: {44, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.191524490 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1854, index: 24, mask: {60, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.203625340 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1862, index: 32, mask: {64, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.255050885 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1856, index: 26, mask: {61, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.226268595 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1853, index: 23, mask: {12, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.226295085 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1883, index: 53, mask: {27, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.231529973 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1869, index: 39, mask: {20, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.235482157 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1864, index: 34, mask: {65, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.239481860 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1897, index: 67, mask: {34, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.247489267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1913, index: 83, mask: {42, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.231551533 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1878, index: 48, mask: {72, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.235490787 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1888, index: 58, mask: {77, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.235501267 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1891, index: 61, mask: {31, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.231560853 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1884, index: 54, mask: {75, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.235479747 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1885, index: 55, mask: {28, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.226300705 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1873, index: 43, mask: {22, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.226262175 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1863, index: 33, mask: {17, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.231541763 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1875, index: 45, mask: {23, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.231485533 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1886, index: 56, mask: {76, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.231574443 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1890, index: 60, mask: {78, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.226293125 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1870, index: 40, mask: {68, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.255088475 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1881, index: 51, mask: {26, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.255135895 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1837, index: 7, mask: {4, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.287495189 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1901, index: 71, mask: {36, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[1;31m2024-02-22 13:40:23.295484056 [E:onnxruntime:Default, env.cc:254 ThreadMain] pthread_setaffinity_np failed for thread: 1900, index: 70, mask: {83, }, error code: 22 error msg: Invalid argument. Specify the number of threads explicitly so the affinity is not set.[m
[INFO] depth estimation...
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/timm/models/_factory.py:117: UserWarning: Mapping deprecated model name vit_base_resnet50_384 to current vit_base_r50_s16_384.orig_in21k_ft_in1k.
model = create_fn(
[INFO] normal estimation...
Running step 1: NeRF
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': [64, 128], 'width': [64, 128], 'resolution_milestones': [3000], 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': True, 'requires_normal': False, 'random_camera': {'height': [64, 128], 'width': [64, 128], 'batch_size': [1, 1], 'resolution_milestones': [3000], 'eval_height': 128, 'eval_width': 128, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 200, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-coarse-nerf',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-coarse-nerf',
'resume': None,
'seed': 0,
'system': {'stage': 'coarse', 'geometry_type': 'implicit-volume', 'geometry': {'radius': 2.0, 'normal_type': 'finite_difference', 'density_bias': 'blob_magic3d', 'density_activation': 'softplus', 'density_blob_scale': 10.0, 'density_blob_std': 0.5, 'pos_encoding_config': {'otype': 'ProgressiveBandHashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378, 'start_level': 8, 'start_step': 2000, 'update_steps': 500}}, 'material_type': 'no-material', 'material': {'requires_normal': True}, 'background_type': 'solid-color-background', 'renderer_type': 'nerf-volume-renderer', 'renderer': {'radius': 2.0, 'num_samples_per_ray': 512, 'return_normal_perturb': True, 'return_comp_normal': True}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': [0, 0.7, 0.2, 200], 'max_step_percent': [0, 0.85, 0.5, 200]}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': [0, 0.7, 0.2, 200], 'max_step_percent': [0, 0.85, 0.5, 200]}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': 0, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.05, 'lambda_normal': 0.0, 'lambda_normal_smooth': 1.0, 'lambda_3d_normal_smooth': [1000, 5.0, 1.0, 1001], 'lambda_orient': [1000, 1.0, 10.0, 1001], 'lambda_sparsity': [1000, 0.1, 10.0, 1001], 'lambda_opaque': [1000, 0.1, 10.0, 1001], 'lambda_clip': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'lr': 0.01, 'betas': [0.9, 0.99], 'eps': 1e-08}}},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-134035',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': '16-mixed'},
'trial_dir': 'outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035',
'trial_name': 'replicate_user@20240222-134035',
'use_timestamp': True}
Loading Deep Floyd ...
Couldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d74ed3-77c3833b6edb1358569cd2db;c0fe2e5f-e2c0-465b-af4c-23a1c171d42e)
Cannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Repo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..
Will try to load from local cache.
Loading pipeline components...: 0%| | 0/3 [00:00<?, ?it/s]
Loading pipeline components...: 33%|███▎ | 1/3 [00:00<00:00, 3.80it/s]
Loading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 9.15it/s]
Loading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 8.02it/s]
Loaded Deep Floyd!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
0%| | 0.00/890M [00:00<?, ?iB/s]
1%|▍ | 11.0M/890M [00:00<00:07, 116MiB/s]
3%|█▏ | 26.0M/890M [00:00<00:06, 140MiB/s]
5%|█▊ | 42.3M/890M [00:00<00:05, 154MiB/s]
6%|██▍ | 57.0M/890M [00:00<00:06, 145MiB/s]
8%|███ | 70.9M/890M [00:00<00:06, 127MiB/s]
9%|███▌ | 83.3M/890M [00:00<00:12, 68.1MiB/s]
10%|███▉ | 92.5M/890M [00:01<00:13, 59.9MiB/s]
11%|████▍ | 100M/890M [00:01<00:23, 35.8MiB/s]
12%|████▋ | 106M/890M [00:02<00:40, 20.5MiB/s]
12%|████▊ | 110M/890M [00:02<00:40, 20.3MiB/s]
13%|████▉ | 113M/890M [00:02<00:41, 19.8MiB/s]
13%|█████ | 116M/890M [00:03<00:59, 13.7MiB/s]
13%|█████▏ | 118M/890M [00:03<00:56, 14.3MiB/s]
14%|█████▎ | 120M/890M [00:03<01:09, 11.7MiB/s]
14%|█████▎ | 122M/890M [00:04<01:06, 12.1MiB/s]
14%|█████▍ | 124M/890M [00:04<01:04, 12.4MiB/s]
14%|█████▍ | 125M/890M [00:04<01:11, 11.2MiB/s]
14%|█████▌ | 127M/890M [00:04<01:06, 12.1MiB/s]
14%|█████▌ | 128M/890M [00:04<01:10, 11.3MiB/s]
15%|█████▋ | 130M/890M [00:04<01:00, 13.2MiB/s]
15%|█████▊ | 131M/890M [00:04<01:01, 12.9MiB/s]
15%|█████▊ | 133M/890M [00:05<01:18, 10.1MiB/s]
15%|█████▉ | 135M/890M [00:05<00:59, 13.3MiB/s]
15%|██████ | 137M/890M [00:05<00:55, 14.3MiB/s]
16%|██████ | 139M/890M [00:05<01:00, 12.9MiB/s]
16%|██████▏ | 140M/890M [00:05<01:03, 12.4MiB/s]
16%|██████▏ | 142M/890M [00:05<00:59, 13.1MiB/s]
16%|██████▎ | 143M/890M [00:05<01:09, 11.3MiB/s]
16%|██████▎ | 144M/890M [00:06<01:10, 11.1MiB/s]
16%|██████▍ | 147M/890M [00:06<00:54, 14.2MiB/s]
17%|██████▌ | 150M/890M [00:06<00:38, 20.1MiB/s]
17%|██████▊ | 154M/890M [00:06<00:29, 25.9MiB/s]
18%|██████▉ | 157M/890M [00:06<00:31, 24.7MiB/s]
18%|██████▉ | 159M/890M [00:06<00:39, 19.4MiB/s]
18%|███████ | 161M/890M [00:06<00:52, 14.4MiB/s]
18%|███████▏ | 163M/890M [00:07<00:58, 13.1MiB/s]
19%|███████▏ | 165M/890M [00:07<00:55, 13.6MiB/s]
19%|███████▎ | 167M/890M [00:07<00:49, 15.2MiB/s]
19%|███████▍ | 168M/890M [00:07<00:52, 14.5MiB/s]
19%|███████▍ | 170M/890M [00:07<00:51, 14.6MiB/s]
19%|███████▌ | 171M/890M [00:07<00:50, 14.9MiB/s]
20%|███████▋ | 175M/890M [00:07<00:37, 20.0MiB/s]
20%|███████▊ | 178M/890M [00:07<00:30, 24.7MiB/s]
20%|███████▉ | 181M/890M [00:07<00:30, 24.1MiB/s]
21%|████████ | 183M/890M [00:08<00:30, 24.0MiB/s]
21%|████████▏ | 187M/890M [00:08<00:26, 28.0MiB/s]
21%|████████▎ | 190M/890M [00:08<00:29, 25.0MiB/s]
22%|████████▍ | 192M/890M [00:08<00:30, 23.6MiB/s]
22%|████████▌ | 195M/890M [00:08<00:29, 24.5MiB/s]
22%|████████▋ | 197M/890M [00:08<00:29, 24.5MiB/s]
22%|████████▊ | 200M/890M [00:08<00:29, 24.8MiB/s]
23%|████████▊ | 202M/890M [00:08<00:29, 24.5MiB/s]
23%|████████▉ | 204M/890M [00:08<00:29, 24.6MiB/s]
23%|█████████ | 207M/890M [00:09<00:28, 24.7MiB/s]
24%|█████████▏ | 210M/890M [00:09<00:25, 27.4MiB/s]
24%|█████████▍ | 216M/890M [00:09<00:19, 36.1MiB/s]
25%|█████████▌ | 219M/890M [00:09<00:21, 33.0MiB/s]
25%|█████████▊ | 223M/890M [00:09<00:20, 33.8MiB/s]
25%|█████████▉ | 226M/890M [00:09<00:22, 31.1MiB/s]
26%|██████████ | 230M/890M [00:09<00:20, 33.3MiB/s]
27%|██████████▎ | 236M/890M [00:09<00:16, 41.4MiB/s]
27%|██████████▌ | 241M/890M [00:09<00:14, 45.8MiB/s]
28%|██████████▊ | 247M/890M [00:10<00:13, 51.0MiB/s]
28%|███████████ | 252M/890M [00:10<00:15, 43.8MiB/s]
29%|███████████▎ | 257M/890M [00:10<00:14, 44.4MiB/s]
30%|███████████▌ | 264M/890M [00:10<00:12, 51.9MiB/s]
30%|███████████▉ | 271M/890M [00:10<00:11, 58.2MiB/s]
31%|████████████▏ | 279M/890M [00:10<00:09, 65.9MiB/s]
32%|████████████▌ | 287M/890M [00:10<00:08, 71.2MiB/s]
33%|████████████▉ | 295M/890M [00:10<00:08, 75.1MiB/s]
34%|█████████████▎ | 304M/890M [00:10<00:07, 78.0MiB/s]
35%|█████████████▋ | 312M/890M [00:11<00:07, 81.4MiB/s]
36%|██████████████ | 320M/890M [00:11<00:07, 79.5MiB/s]
37%|██████████████▍ | 328M/890M [00:11<00:07, 81.2MiB/s]
38%|██████████████▊ | 338M/890M [00:11<00:06, 85.5MiB/s]
39%|███████████████▏ | 346M/890M [00:11<00:06, 86.8MiB/s]
40%|███████████████▌ | 356M/890M [00:11<00:06, 91.1MiB/s]
41%|████████████████ | 366M/890M [00:11<00:05, 95.6MiB/s]
42%|████████████████▍ | 376M/890M [00:11<00:05, 98.3MiB/s]
43%|████████████████▉ | 385M/890M [00:11<00:05, 96.1MiB/s]
44%|█████████████████▎ | 395M/890M [00:11<00:05, 96.3MiB/s]
45%|█████████████████▋ | 405M/890M [00:12<00:05, 98.8MiB/s]
47%|██████████████████▏ | 414M/890M [00:12<00:05, 97.1MiB/s]
48%|███████████████████ | 425M/890M [00:12<00:04, 102MiB/s]
49%|███████████████████▌ | 435M/890M [00:12<00:04, 104MiB/s]
50%|████████████████████ | 446M/890M [00:12<00:04, 106MiB/s]
51%|████████████████████▌ | 456M/890M [00:12<00:04, 102MiB/s]
52%|████████████████████▍ | 466M/890M [00:12<00:05, 85.4MiB/s]
53%|████████████████████▊ | 475M/890M [00:12<00:05, 87.0MiB/s]
54%|█████████████████████▏ | 483M/890M [00:13<00:07, 55.9MiB/s]
55%|█████████████████████▍ | 490M/890M [00:13<00:07, 54.7MiB/s]
56%|█████████████████████▊ | 496M/890M [00:13<00:07, 57.2MiB/s]
57%|██████████████████████ | 503M/890M [00:13<00:07, 57.5MiB/s]
57%|██████████████████████▎ | 509M/890M [00:13<00:07, 53.4MiB/s]
58%|██████████████████████▌ | 514M/890M [00:13<00:08, 48.0MiB/s]
58%|██████████████████████▊ | 519M/890M [00:13<00:09, 41.7MiB/s]
59%|██████████████████████▉ | 524M/890M [00:14<00:09, 41.5MiB/s]
59%|███████████████████████▏ | 528M/890M [00:14<00:10, 37.8MiB/s]
60%|███████████████████████▎ | 532M/890M [00:14<00:10, 35.2MiB/s]
60%|███████████████████████▍ | 535M/890M [00:14<00:11, 33.6MiB/s]
61%|███████████████████████▋ | 540M/890M [00:14<00:09, 36.8MiB/s]
61%|███████████████████████▊ | 543M/890M [00:14<00:10, 35.8MiB/s]
61%|███████████████████████▉ | 547M/890M [00:14<00:10, 34.0MiB/s]
62%|████████████████████████ | 550M/890M [00:14<00:10, 34.0MiB/s]
62%|████████████████████████▎ | 554M/890M [00:15<00:09, 36.2MiB/s]
63%|████████████████████████▌ | 559M/890M [00:15<00:08, 41.7MiB/s]
64%|████████████████████████▊ | 567M/890M [00:15<00:06, 53.1MiB/s]
64%|█████████████████████████ | 572M/890M [00:15<00:06, 51.1MiB/s]
65%|█████████████████████████▎ | 577M/890M [00:15<00:06, 48.7MiB/s]
65%|█████████████████████████▌ | 582M/890M [00:15<00:06, 49.0MiB/s]
66%|█████████████████████████▉ | 591M/890M [00:15<00:05, 61.3MiB/s]
67%|██████████████████████████▏ | 598M/890M [00:15<00:04, 65.0MiB/s]
68%|██████████████████████████▌ | 605M/890M [00:15<00:04, 62.2MiB/s]
69%|██████████████████████████▊ | 611M/890M [00:16<00:05, 58.1MiB/s]
69%|███████████████████████████ | 617M/890M [00:16<00:04, 59.3MiB/s]
70%|███████████████████████████▎ | 623M/890M [00:16<00:04, 59.8MiB/s]
71%|███████████████████████████▌ | 628M/890M [00:16<00:05, 48.3MiB/s]
71%|███████████████████████████▊ | 634M/890M [00:16<00:05, 49.4MiB/s]
72%|████████████████████████████ | 639M/890M [00:16<00:05, 51.9MiB/s]
73%|████████████████████████████▎ | 645M/890M [00:16<00:04, 55.0MiB/s]
73%|████████████████████████████▌ | 652M/890M [00:16<00:04, 56.8MiB/s]
74%|████████████████████████████▊ | 657M/890M [00:16<00:04, 57.9MiB/s]
75%|█████████████████████████████▏ | 665M/890M [00:17<00:03, 63.7MiB/s]
76%|█████████████████████████████▌ | 675M/890M [00:17<00:03, 74.1MiB/s]
77%|█████████████████████████████▉ | 682M/890M [00:17<00:03, 70.3MiB/s]
77%|██████████████████████████████▏ | 689M/890M [00:17<00:03, 69.8MiB/s]
78%|██████████████████████████████▍ | 695M/890M [00:17<00:03, 63.9MiB/s]
79%|██████████████████████████████▊ | 702M/890M [00:17<00:03, 63.2MiB/s]
80%|███████████████████████████████ | 709M/890M [00:17<00:02, 66.7MiB/s]
80%|███████████████████████████████▍ | 716M/890M [00:17<00:02, 67.9MiB/s]
81%|███████████████████████████████▋ | 722M/890M [00:17<00:02, 64.0MiB/s]
82%|████████████████████████████████ | 731M/890M [00:18<00:02, 72.6MiB/s]
83%|████████████████████████████████▍ | 739M/890M [00:18<00:03, 50.1MiB/s]
84%|████████████████████████████████▋ | 744M/890M [00:18<00:03, 50.1MiB/s]
84%|████████████████████████████████▊ | 750M/890M [00:18<00:02, 51.1MiB/s]
85%|█████████████████████████████████ | 755M/890M [00:18<00:02, 52.7MiB/s]
86%|█████████████████████████████████▎ | 761M/890M [00:18<00:02, 52.1MiB/s]
86%|█████████████████████████████████▌ | 767M/890M [00:18<00:02, 55.3MiB/s]
87%|█████████████████████████████████▊ | 773M/890M [00:18<00:02, 55.0MiB/s]
88%|██████████████████████████████████▏ | 779M/890M [00:19<00:01, 59.5MiB/s]
88%|██████████████████████████████████▍ | 785M/890M [00:19<00:01, 60.8MiB/s]
89%|██████████████████████████████████▋ | 791M/890M [00:19<00:02, 51.3MiB/s]
90%|██████████████████████████████████▉ | 797M/890M [00:19<00:02, 48.5MiB/s]
90%|███████████████████████████████████▎ | 804M/890M [00:19<00:01, 56.5MiB/s]
92%|███████████████████████████████████▋ | 815M/890M [00:19<00:01, 71.6MiB/s]
93%|████████████████████████████████████▎ | 828M/890M [00:19<00:00, 88.1MiB/s]
94%|████████████████████████████████████▋ | 837M/890M [00:19<00:00, 91.4MiB/s]
95%|█████████████████████████████████████▏ | 847M/890M [00:19<00:00, 93.8MiB/s]
96%|█████████████████████████████████████▌ | 856M/890M [00:20<00:00, 93.1MiB/s]
98%|███████████████████████████████████████ | 868M/890M [00:20<00:00, 102MiB/s]
99%|██████████████████████████████████████▍| 878M/890M [00:20<00:00, 94.3MiB/s]
100%|██████████████████████████████████████▉| 888M/890M [00:20<00:00, 98.6MiB/s]
100%|███████████████████████████████████████| 890M/890M [00:20<00:00, 45.8MiB/s]
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
Using 16bit Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
You are using a CUDA device ('NVIDIA A40') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name | Type | Params
----------------------------------------------------
0 | geometry | ImplicitVolume | 12.6 M
1 | material | NoMaterial | 0
2 | background | SolidColorBackground | 0
3 | renderer | NeRFVolumeRenderer | 0
----------------------------------------------------
12.6 M Trainable params
0 Non-trainable params
12.6 M Total params
50.417 Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/save
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
Training: | | 0/? [00:00<?, ?it/s]
Training: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 1/? [00:00<00:00, 5.54it/s]
Epoch 0: | | 1/? [00:00<00:00, 5.51it/s, train/loss=58.90]
Epoch 0: | | 2/? [00:00<00:00, 2.90it/s, train/loss=58.90]
Epoch 0: | | 2/? [00:00<00:00, 2.90it/s, train/loss=40.50]
Epoch 0: | | 3/? [00:00<00:00, 3.98it/s, train/loss=40.50]
Epoch 0: | | 3/? [00:00<00:00, 3.97it/s, train/loss=58.60]
Epoch 0: | | 4/? [00:01<00:00, 3.74it/s, train/loss=58.60]
Epoch 0: | | 4/? [00:01<00:00, 3.74it/s, train/loss=69.90]
Epoch 0: | | 5/? [00:01<00:00, 4.38it/s, train/loss=69.90]
Epoch 0: | | 5/? [00:01<00:00, 4.38it/s, train/loss=57.90]
Epoch 0: | | 6/? [00:01<00:00, 4.11it/s, train/loss=57.90]
Epoch 0: | | 6/? [00:01<00:00, 4.11it/s, train/loss=73.10]
Epoch 0: | | 7/? [00:01<00:00, 4.59it/s, train/loss=73.10]
Epoch 0: | | 7/? [00:01<00:00, 4.59it/s, train/loss=56.60]
Epoch 0: | | 8/? [00:01<00:00, 4.34it/s, train/loss=56.60]
Epoch 0: | | 8/? [00:01<00:00, 4.34it/s, train/loss=41.30]
Epoch 0: | | 9/? [00:01<00:00, 4.72it/s, train/loss=41.30]
Epoch 0: | | 9/? [00:01<00:00, 4.71it/s, train/loss=54.50]
Epoch 0: | | 10/? [00:02<00:00, 4.49it/s, train/loss=54.50]
Epoch 0: | | 10/? [00:02<00:00, 4.49it/s, train/loss=80.40]
Epoch 0: | | 11/? [00:02<00:00, 4.80it/s, train/loss=80.40]
Epoch 0: | | 11/? [00:02<00:00, 4.80it/s, train/loss=51.40]
Epoch 0: | | 12/? [00:02<00:00, 4.61it/s, train/loss=51.40]
Epoch 0: | | 12/? [00:02<00:00, 4.60it/s, train/loss=108.0]
Epoch 0: | | 13/? [00:02<00:00, 4.87it/s, train/loss=108.0]
Epoch 0: | | 13/? [00:02<00:00, 4.87it/s, train/loss=47.50]
Epoch 0: | | 14/? [00:02<00:00, 4.69it/s, train/loss=47.50]
Epoch 0: | | 14/? [00:02<00:00, 4.69it/s, train/loss=52.10]
Epoch 0: | | 15/? [00:03<00:00, 4.92it/s, train/loss=52.10]
Epoch 0: | | 15/? [00:03<00:00, 4.92it/s, train/loss=42.80]
Epoch 0: | | 16/? [00:03<00:00, 4.74it/s, train/loss=42.80]
Epoch 0: | | 16/? [00:03<00:00, 4.74it/s, train/loss=76.90]
Epoch 0: | | 17/? [00:03<00:00, 4.94it/s, train/loss=76.90]
Epoch 0: | | 17/? [00:03<00:00, 4.94it/s, train/loss=37.60]
Epoch 0: | | 18/? [00:03<00:00, 4.79it/s, train/loss=37.60]
Epoch 0: | | 18/? [00:03<00:00, 4.79it/s, train/loss=123.0]
Epoch 0: | | 19/? [00:03<00:00, 4.98it/s, train/loss=123.0]
Epoch 0: | | 19/? [00:03<00:00, 4.97it/s, train/loss=32.60]
Epoch 0: | | 20/? [00:04<00:00, 4.84it/s, train/loss=32.60]
Epoch 0: | | 20/? [00:04<00:00, 4.84it/s, train/loss=62.40]
Epoch 0: | | 21/? [00:04<00:00, 5.01it/s, train/loss=62.40]
Epoch 0: | | 21/? [00:04<00:00, 5.01it/s, train/loss=28.20]
Epoch 0: | | 22/? [00:04<00:00, 4.88it/s, train/loss=28.20]
Epoch 0: | | 22/? [00:04<00:00, 4.88it/s, train/loss=49.50]
Epoch 0: | | 23/? [00:04<00:00, 5.03it/s, train/loss=49.50]
Epoch 0: | | 23/? [00:04<00:00, 5.03it/s, train/loss=24.40]
Epoch 0: | | 24/? [00:04<00:00, 4.92it/s, train/loss=24.40]
Epoch 0: | | 24/? [00:04<00:00, 4.91it/s, train/loss=74.90]
Epoch 0: | | 25/? [00:04<00:00, 5.06it/s, train/loss=74.90]
Epoch 0: | | 25/? [00:04<00:00, 5.06it/s, train/loss=21.10]
Epoch 0: | | 26/? [00:05<00:00, 4.95it/s, train/loss=21.10]
Epoch 0: | | 26/? [00:05<00:00, 4.95it/s, train/loss=66.30]
Epoch 0: | | 27/? [00:05<00:00, 5.09it/s, train/loss=66.30]
Epoch 0: | | 27/? [00:05<00:00, 5.09it/s, train/loss=18.90]
Epoch 0: | | 28/? [00:05<00:00, 4.99it/s, train/loss=18.90]
Epoch 0: | | 28/? [00:05<00:00, 4.98it/s, train/loss=67.70]
Epoch 0: | | 29/? [00:05<00:00, 5.11it/s, train/loss=67.70]
Epoch 0: | | 29/? [00:05<00:00, 5.11it/s, train/loss=17.40]
Epoch 0: | | 30/? [00:05<00:00, 5.02it/s, train/loss=17.40]
Epoch 0: | | 30/? [00:05<00:00, 5.02it/s, train/loss=79.10]
Epoch 0: | | 31/? [00:06<00:00, 5.14it/s, train/loss=79.10]
Epoch 0: | | 31/? [00:06<00:00, 5.14it/s, train/loss=16.20]
Epoch 0: | | 32/? [00:06<00:00, 5.05it/s, train/loss=16.20]
Epoch 0: | | 32/? [00:06<00:00, 5.05it/s, train/loss=41.90]
Epoch 0: | | 33/? [00:06<00:00, 5.17it/s, train/loss=41.90]
Epoch 0: | | 33/? [00:06<00:00, 5.17it/s, train/loss=15.50]
Epoch 0: | | 34/? [00:06<00:00, 5.08it/s, train/loss=15.50]
Epoch 0: | | 34/? [00:06<00:00, 5.08it/s, train/loss=47.50]
Epoch 0: | | 35/? [00:06<00:00, 5.19it/s, train/loss=47.50]
Epoch 0: | | 35/? [00:06<00:00, 5.18it/s, train/loss=14.20]
Epoch 0: | | 36/? [00:07<00:00, 5.08it/s, train/loss=14.20]
Epoch 0: | | 36/? [00:07<00:00, 5.08it/s, train/loss=41.60]
Epoch 0: | | 37/? [00:07<00:00, 5.19it/s, train/loss=41.60]
Epoch 0: | | 37/? [00:07<00:00, 5.19it/s, train/loss=12.90]
Epoch 0: | | 38/? [00:07<00:00, 5.11it/s, train/loss=12.90]
Epoch 0: | | 38/? [00:07<00:00, 5.11it/s, train/loss=50.40]
Epoch 0: | | 39/? [00:07<00:00, 5.21it/s, train/loss=50.40]
Epoch 0: | | 39/? [00:07<00:00, 5.21it/s, train/loss=11.80]
Epoch 0: | | 40/? [00:07<00:00, 5.13it/s, train/loss=11.80]
Epoch 0: | | 40/? [00:07<00:00, 5.13it/s, train/loss=82.60]
Epoch 0: | | 41/? [00:07<00:00, 5.23it/s, train/loss=82.60]
Epoch 0: | | 41/? [00:07<00:00, 5.23it/s, train/loss=10.90]
Epoch 0: | | 42/? [00:08<00:00, 5.15it/s, train/loss=10.90]
Epoch 0: | | 42/? [00:08<00:00, 5.15it/s, train/loss=63.40]
Epoch 0: | | 43/? [00:08<00:00, 5.24it/s, train/loss=63.40]
Epoch 0: | | 43/? [00:08<00:00, 5.24it/s, train/loss=10.30]
Epoch 0: | | 44/? [00:08<00:00, 5.17it/s, train/loss=10.30]
Epoch 0: | | 44/? [00:08<00:00, 5.17it/s, train/loss=70.20]
Epoch 0: | | 45/? [00:08<00:00, 5.26it/s, train/loss=70.20]
Epoch 0: | | 45/? [00:08<00:00, 5.26it/s, train/loss=10.00]
Epoch 0: | | 46/? [00:08<00:00, 5.19it/s, train/loss=10.00]
Epoch 0: | | 46/? [00:08<00:00, 5.19it/s, train/loss=60.70]
Epoch 0: | | 47/? [00:08<00:00, 5.28it/s, train/loss=60.70]
Epoch 0: | | 47/? [00:08<00:00, 5.28it/s, train/loss=9.830]
Epoch 0: | | 48/? [00:09<00:00, 5.21it/s, train/loss=9.830]
Epoch 0: | | 48/? [00:09<00:00, 5.21it/s, train/loss=61.30]
Epoch 0: | | 49/? [00:09<00:00, 5.29it/s, train/loss=61.30]
Epoch 0: | | 49/? [00:09<00:00, 5.29it/s, train/loss=9.610]
Epoch 0: | | 50/? [00:09<00:00, 5.23it/s, train/loss=9.610]
Epoch 0: | | 50/? [00:09<00:00, 5.23it/s, train/loss=61.80]
Epoch 0: | | 51/? [00:09<00:00, 5.30it/s, train/loss=61.80]
Epoch 0: | | 51/? [00:09<00:00, 5.30it/s, train/loss=9.420]
Epoch 0: | | 52/? [00:09<00:00, 5.24it/s, train/loss=9.420]
Epoch 0: | | 52/? [00:09<00:00, 5.24it/s, train/loss=38.50]
Epoch 0: | | 53/? [00:09<00:00, 5.32it/s, train/loss=38.50]
Epoch 0: | | 53/? [00:09<00:00, 5.32it/s, train/loss=9.250]
Epoch 0: | | 54/? [00:10<00:00, 5.26it/s, train/loss=9.250]
Epoch 0: | | 54/? [00:10<00:00, 5.26it/s, train/loss=43.80]
Epoch 0: | | 55/? [00:10<00:00, 5.33it/s, train/loss=43.80]
Epoch 0: | | 55/? [00:10<00:00, 5.33it/s, train/loss=9.020]
Epoch 0: | | 56/? [00:10<00:00, 5.27it/s, train/loss=9.020]
Epoch 0: | | 56/? [00:10<00:00, 5.27it/s, train/loss=88.30]
Epoch 0: | | 57/? [00:10<00:00, 5.34it/s, train/loss=88.30]
Epoch 0: | | 57/? [00:10<00:00, 5.34it/s, train/loss=8.820]
Epoch 0: | | 58/? [00:10<00:00, 5.29it/s, train/loss=8.820]
Epoch 0: | | 58/? [00:10<00:00, 5.29it/s, train/loss=65.20]
Epoch 0: | | 59/? [00:11<00:00, 5.35it/s, train/loss=65.20]
Epoch 0: | | 59/? [00:11<00:00, 5.35it/s, train/loss=8.700]
Epoch 0: | | 60/? [00:11<00:00, 5.30it/s, train/loss=8.700]
Epoch 0: | | 60/? [00:11<00:00, 5.30it/s, train/loss=48.50]
Epoch 0: | | 61/? [00:11<00:00, 5.36it/s, train/loss=48.50]
Epoch 0: | | 61/? [00:11<00:00, 5.36it/s, train/loss=8.640]
Epoch 0: | | 62/? [00:11<00:00, 5.31it/s, train/loss=8.640]
Epoch 0: | | 62/? [00:11<00:00, 5.30it/s, train/loss=63.30]
Epoch 0: | | 63/? [00:11<00:00, 5.37it/s, train/loss=63.30]
Epoch 0: | | 63/? [00:11<00:00, 5.37it/s, train/loss=8.580]
Epoch 0: | | 64/? [00:12<00:00, 5.32it/s, train/loss=8.580]
Epoch 0: | | 64/? [00:12<00:00, 5.31it/s, train/loss=73.00]
Epoch 0: | | 65/? [00:12<00:00, 5.37it/s, train/loss=73.00]
Epoch 0: | | 65/? [00:12<00:00, 5.37it/s, train/loss=8.530]
Epoch 0: | | 66/? [00:12<00:00, 5.32it/s, train/loss=8.530]
Epoch 0: | | 66/? [00:12<00:00, 5.32it/s, train/loss=114.0]
Epoch 0: | | 67/? [00:12<00:00, 5.38it/s, train/loss=114.0]
Epoch 0: | | 67/? [00:12<00:00, 5.38it/s, train/loss=8.480]
Epoch 0: | | 68/? [00:12<00:00, 5.28it/s, train/loss=8.480]
Epoch 0: | | 68/? [00:12<00:00, 5.28it/s, train/loss=47.50]
Epoch 0: | | 69/? [00:12<00:00, 5.34it/s, train/loss=47.50]
Epoch 0: | | 69/? [00:12<00:00, 5.34it/s, train/loss=8.460]
Epoch 0: | | 70/? [00:13<00:00, 5.30it/s, train/loss=8.460]
Epoch 0: | | 70/? [00:13<00:00, 5.30it/s, train/loss=71.40]
Epoch 0: | | 71/? [00:13<00:00, 5.36it/s, train/loss=71.40]
Epoch 0: | | 71/? [00:13<00:00, 5.35it/s, train/loss=8.390]
Epoch 0: | | 72/? [00:13<00:00, 5.31it/s, train/loss=8.390]
Epoch 0: | | 72/? [00:13<00:00, 5.31it/s, train/loss=54.80]
Epoch 0: | | 73/? [00:13<00:00, 5.37it/s, train/loss=54.80]
Epoch 0: | | 73/? [00:13<00:00, 5.37it/s, train/loss=8.210]
Epoch 0: | | 74/? [00:13<00:00, 5.33it/s, train/loss=8.210]
Epoch 0: | | 74/? [00:13<00:00, 5.33it/s, train/loss=46.20]
Epoch 0: | | 75/? [00:13<00:00, 5.38it/s, train/loss=46.20]
Epoch 0: | | 75/? [00:13<00:00, 5.38it/s, train/loss=8.040]
Epoch 0: | | 76/? [00:14<00:00, 5.34it/s, train/loss=8.040]
Epoch 0: | | 76/? [00:14<00:00, 5.34it/s, train/loss=79.50]
Epoch 0: | | 77/? [00:14<00:00, 5.39it/s, train/loss=79.50]
Epoch 0: | | 77/? [00:14<00:00, 5.39it/s, train/loss=7.990]
Epoch 0: | | 78/? [00:14<00:00, 5.35it/s, train/loss=7.990]
Epoch 0: | | 78/? [00:14<00:00, 5.35it/s, train/loss=41.70]
Epoch 0: | | 79/? [00:14<00:00, 5.40it/s, train/loss=41.70]
Epoch 0: | | 79/? [00:14<00:00, 5.40it/s, train/loss=8.030]
Epoch 0: | | 80/? [00:14<00:00, 5.36it/s, train/loss=8.030]
Epoch 0: | | 80/? [00:14<00:00, 5.36it/s, train/loss=64.90]
Epoch 0: | | 81/? [00:14<00:00, 5.41it/s, train/loss=64.90]
Epoch 0: | | 81/? [00:14<00:00, 5.41it/s, train/loss=8.050]
Epoch 0: | | 82/? [00:15<00:00, 5.37it/s, train/loss=8.050]
Epoch 0: | | 82/? [00:15<00:00, 5.37it/s, train/loss=62.00]
Epoch 0: | | 83/? [00:15<00:00, 5.42it/s, train/loss=62.00]
Epoch 0: | | 83/? [00:15<00:00, 5.42it/s, train/loss=8.020]
Epoch 0: | | 84/? [00:15<00:00, 5.38it/s, train/loss=8.020]
Epoch 0: | | 84/? [00:15<00:00, 5.38it/s, train/loss=45.70]
Epoch 0: | | 85/? [00:15<00:00, 5.43it/s, train/loss=45.70]
Epoch 0: | | 85/? [00:15<00:00, 5.43it/s, train/loss=7.980]
Epoch 0: | | 86/? [00:15<00:00, 5.39it/s, train/loss=7.980]
Epoch 0: | | 86/? [00:15<00:00, 5.39it/s, train/loss=61.90]
Epoch 0: | | 87/? [00:16<00:00, 5.44it/s, train/loss=61.90]
Epoch 0: | | 87/? [00:16<00:00, 5.44it/s, train/loss=7.940]
Epoch 0: | | 88/? [00:16<00:00, 5.40it/s, train/loss=7.940]
Epoch 0: | | 88/? [00:16<00:00, 5.40it/s, train/loss=72.20]
Epoch 0: | | 89/? [00:16<00:00, 5.45it/s, train/loss=72.20]
Epoch 0: | | 89/? [00:16<00:00, 5.45it/s, train/loss=7.930]
Epoch 0: | | 90/? [00:16<00:00, 5.41it/s, train/loss=7.930]
Epoch 0: | | 90/? [00:16<00:00, 5.41it/s, train/loss=70.50]
Epoch 0: | | 91/? [00:16<00:00, 5.45it/s, train/loss=70.50]
Epoch 0: | | 91/? [00:16<00:00, 5.45it/s, train/loss=7.950]
Epoch 0: | | 92/? [00:16<00:00, 5.41it/s, train/loss=7.950]
Epoch 0: | | 92/? [00:17<00:00, 5.41it/s, train/loss=55.00]
Epoch 0: | | 93/? [00:17<00:00, 5.45it/s, train/loss=55.00]
Epoch 0: | | 93/? [00:17<00:00, 5.45it/s, train/loss=7.930]
Epoch 0: | | 94/? [00:17<00:00, 5.41it/s, train/loss=7.930]
Epoch 0: | | 94/? [00:17<00:00, 5.41it/s, train/loss=47.60]
Epoch 0: | | 95/? [00:17<00:00, 5.45it/s, train/loss=47.60]
Epoch 0: | | 95/? [00:17<00:00, 5.45it/s, train/loss=7.880]
Epoch 0: | | 96/? [00:17<00:00, 5.42it/s, train/loss=7.880]
Epoch 0: | | 96/? [00:17<00:00, 5.42it/s, train/loss=53.40]
Epoch 0: | | 97/? [00:17<00:00, 5.46it/s, train/loss=53.40]
Epoch 0: | | 97/? [00:17<00:00, 5.46it/s, train/loss=7.830]
Epoch 0: | | 98/? [00:18<00:00, 5.43it/s, train/loss=7.830]
Epoch 0: | | 98/? [00:18<00:00, 5.43it/s, train/loss=52.20]
Epoch 0: | | 99/? [00:18<00:00, 5.47it/s, train/loss=52.20]
Epoch 0: | | 99/? [00:18<00:00, 5.47it/s, train/loss=7.710]
Epoch 0: | | 100/? [00:18<00:00, 5.44it/s, train/loss=7.710]
Epoch 0: | | 100/? [00:18<00:00, 5.44it/s, train/loss=46.20]
Epoch 0: | | 101/? [00:18<00:00, 5.48it/s, train/loss=46.20]
Epoch 0: | | 101/? [00:18<00:00, 5.48it/s, train/loss=7.540]
Epoch 0: | | 102/? [00:18<00:00, 5.45it/s, train/loss=7.540]
Epoch 0: | | 102/? [00:18<00:00, 5.45it/s, train/loss=63.90]
Epoch 0: | | 103/? [00:18<00:00, 5.49it/s, train/loss=63.90]
Epoch 0: | | 103/? [00:18<00:00, 5.49it/s, train/loss=7.310]
Epoch 0: | | 104/? [00:19<00:00, 5.46it/s, train/loss=7.310]
Epoch 0: | | 104/? [00:19<00:00, 5.46it/s, train/loss=70.90]
Epoch 0: | | 105/? [00:19<00:00, 5.49it/s, train/loss=70.90]
Epoch 0: | | 105/? [00:19<00:00, 5.49it/s, train/loss=7.160]
Epoch 0: | | 106/? [00:19<00:00, 5.46it/s, train/loss=7.160]
Epoch 0: | | 106/? [00:19<00:00, 5.46it/s, train/loss=59.10]
Epoch 0: | | 107/? [00:19<00:00, 5.50it/s, train/loss=59.10]
Epoch 0: | | 107/? [00:19<00:00, 5.50it/s, train/loss=7.080]
Epoch 0: | | 108/? [00:19<00:00, 5.47it/s, train/loss=7.080]
Epoch 0: | | 108/? [00:19<00:00, 5.47it/s, train/loss=57.80]
Epoch 0: | | 109/? [00:19<00:00, 5.51it/s, train/loss=57.80]
Epoch 0: | | 109/? [00:19<00:00, 5.51it/s, train/loss=7.080]
Epoch 0: | | 110/? [00:20<00:00, 5.47it/s, train/loss=7.080]
Epoch 0: | | 110/? [00:20<00:00, 5.47it/s, train/loss=41.90]
Epoch 0: | | 111/? [00:20<00:00, 5.51it/s, train/loss=41.90]
Epoch 0: | | 111/? [00:20<00:00, 5.51it/s, train/loss=7.140]
Epoch 0: | | 112/? [00:20<00:00, 5.48it/s, train/loss=7.140]
Epoch 0: | | 112/? [00:20<00:00, 5.48it/s, train/loss=56.10]
Epoch 0: | | 113/? [00:20<00:00, 5.52it/s, train/loss=56.10]
Epoch 0: | | 113/? [00:20<00:00, 5.52it/s, train/loss=7.250]
Epoch 0: | | 114/? [00:20<00:00, 5.49it/s, train/loss=7.250]
Epoch 0: | | 114/? [00:20<00:00, 5.49it/s, train/loss=48.80]
Epoch 0: | | 115/? [00:20<00:00, 5.53it/s, train/loss=48.80]
Epoch 0: | | 115/? [00:20<00:00, 5.53it/s, train/loss=7.310]
Epoch 0: | | 116/? [00:21<00:00, 5.50it/s, train/loss=7.310]
Epoch 0: | | 116/? [00:21<00:00, 5.50it/s, train/loss=51.80]
Epoch 0: | | 117/? [00:21<00:00, 5.54it/s, train/loss=51.80]
Epoch 0: | | 117/? [00:21<00:00, 5.54it/s, train/loss=7.300]
Epoch 0: | | 118/? [00:21<00:00, 5.51it/s, train/loss=7.300]
Epoch 0: | | 118/? [00:21<00:00, 5.51it/s, train/loss=47.40]
Epoch 0: | | 119/? [00:21<00:00, 5.54it/s, train/loss=47.40]
Epoch 0: | | 119/? [00:21<00:00, 5.54it/s, train/loss=7.190]
Epoch 0: | | 120/? [00:21<00:00, 5.52it/s, train/loss=7.190]
Epoch 0: | | 120/? [00:21<00:00, 5.52it/s, train/loss=49.40]
Epoch 0: | | 121/? [00:21<00:00, 5.55it/s, train/loss=49.40]
Epoch 0: | | 121/? [00:21<00:00, 5.55it/s, train/loss=7.070]
Epoch 0: | | 122/? [00:22<00:00, 5.52it/s, train/loss=7.070]
Epoch 0: | | 122/? [00:22<00:00, 5.52it/s, train/loss=48.40]
Epoch 0: | | 123/? [00:22<00:00, 5.56it/s, train/loss=48.40]
Epoch 0: | | 123/? [00:22<00:00, 5.56it/s, train/loss=6.940]
Epoch 0: | | 124/? [00:22<00:00, 5.53it/s, train/loss=6.940]
Epoch 0: | | 124/? [00:22<00:00, 5.53it/s, train/loss=98.00]
Epoch 0: | | 125/? [00:22<00:00, 5.56it/s, train/loss=98.00]
Epoch 0: | | 125/? [00:22<00:00, 5.56it/s, train/loss=6.790]
Epoch 0: | | 126/? [00:22<00:00, 5.54it/s, train/loss=6.790]
Epoch 0: | | 126/? [00:22<00:00, 5.54it/s, train/loss=34.70]
Epoch 0: | | 127/? [00:22<00:00, 5.57it/s, train/loss=34.70]
Epoch 0: | | 127/? [00:22<00:00, 5.57it/s, train/loss=6.770]
Epoch 0: | | 128/? [00:23<00:00, 5.54it/s, train/loss=6.770]
Epoch 0: | | 128/? [00:23<00:00, 5.54it/s, train/loss=24.60]
Epoch 0: | | 129/? [00:23<00:00, 5.58it/s, train/loss=24.60]
Epoch 0: | | 129/? [00:23<00:00, 5.58it/s, train/loss=6.750]
Epoch 0: | | 130/? [00:23<00:00, 5.55it/s, train/loss=6.750]
Epoch 0: | | 130/? [00:23<00:00, 5.55it/s, train/loss=42.10]
Epoch 0: | | 131/? [00:23<00:00, 5.59it/s, train/loss=42.10]
Epoch 0: | | 131/? [00:23<00:00, 5.59it/s, train/loss=6.640]
Epoch 0: | | 132/? [00:23<00:00, 5.56it/s, train/loss=6.640]
Epoch 0: | | 132/? [00:23<00:00, 5.56it/s, train/loss=64.70]
Epoch 0: | | 133/? [00:23<00:00, 5.59it/s, train/loss=64.70]
Epoch 0: | | 133/? [00:23<00:00, 5.59it/s, train/loss=6.450]
Epoch 0: | | 134/? [00:24<00:00, 5.57it/s, train/loss=6.450]
Epoch 0: | | 134/? [00:24<00:00, 5.57it/s, train/loss=47.10]
Epoch 0: | | 135/? [00:24<00:00, 5.60it/s, train/loss=47.10]
Epoch 0: | | 135/? [00:24<00:00, 5.60it/s, train/loss=6.330]
Epoch 0: | | 136/? [00:24<00:00, 5.57it/s, train/loss=6.330]
Epoch 0: | | 136/? [00:24<00:00, 5.57it/s, train/loss=42.00]
Epoch 0: | | 137/? [00:24<00:00, 5.61it/s, train/loss=42.00]
Epoch 0: | | 137/? [00:24<00:00, 5.61it/s, train/loss=6.280]
Epoch 0: | | 138/? [00:24<00:00, 5.58it/s, train/loss=6.280]
Epoch 0: | | 138/? [00:24<00:00, 5.58it/s, train/loss=46.60]
Epoch 0: | | 139/? [00:24<00:00, 5.61it/s, train/loss=46.60]
Epoch 0: | | 139/? [00:24<00:00, 5.61it/s, train/loss=6.390]
Epoch 0: | | 140/? [00:25<00:00, 5.59it/s, train/loss=6.390]
Epoch 0: | | 140/? [00:25<00:00, 5.59it/s, train/loss=33.50]
Epoch 0: | | 141/? [00:25<00:00, 5.62it/s, train/loss=33.50]
Epoch 0: | | 141/? [00:25<00:00, 5.62it/s, train/loss=6.580]
Epoch 0: | | 142/? [00:25<00:00, 5.59it/s, train/loss=6.580]
Epoch 0: | | 142/? [00:25<00:00, 5.59it/s, train/loss=30.50]
Epoch 0: | | 143/? [00:25<00:00, 5.63it/s, train/loss=30.50]
Epoch 0: | | 143/? [00:25<00:00, 5.63it/s, train/loss=6.660]
Epoch 0: | | 144/? [00:25<00:00, 5.60it/s, train/loss=6.660]
Epoch 0: | | 144/? [00:25<00:00, 5.60it/s, train/loss=38.60]
Epoch 0: | | 145/? [00:25<00:00, 5.62it/s, train/loss=38.60]
Epoch 0: | | 145/? [00:25<00:00, 5.62it/s, train/loss=6.590]
Epoch 0: | | 146/? [00:26<00:00, 5.60it/s, train/loss=6.590]
Epoch 0: | | 146/? [00:26<00:00, 5.60it/s, train/loss=34.10]
Epoch 0: | | 147/? [00:26<00:00, 5.62it/s, train/loss=34.10]
Epoch 0: | | 147/? [00:26<00:00, 5.62it/s, train/loss=6.380]
Epoch 0: | | 148/? [00:26<00:00, 5.59it/s, train/loss=6.380]
Epoch 0: | | 148/? [00:26<00:00, 5.59it/s, train/loss=64.90]
Epoch 0: | | 149/? [00:26<00:00, 5.62it/s, train/loss=64.90]
Epoch 0: | | 149/? [00:26<00:00, 5.62it/s, train/loss=6.170]
Epoch 0: | | 150/? [00:26<00:00, 5.59it/s, train/loss=6.170]
Epoch 0: | | 150/? [00:26<00:00, 5.59it/s, train/loss=38.60]
Epoch 0: | | 151/? [00:26<00:00, 5.62it/s, train/loss=38.60]
Epoch 0: | | 151/? [00:26<00:00, 5.62it/s, train/loss=6.060]
Epoch 0: | | 152/? [00:27<00:00, 5.60it/s, train/loss=6.060]
Epoch 0: | | 152/? [00:27<00:00, 5.60it/s, train/loss=45.40]
Epoch 0: | | 153/? [00:27<00:00, 5.62it/s, train/loss=45.40]
Epoch 0: | | 153/? [00:27<00:00, 5.62it/s, train/loss=5.980]
Epoch 0: | | 154/? [00:27<00:00, 5.60it/s, train/loss=5.980]
Epoch 0: | | 154/? [00:27<00:00, 5.60it/s, train/loss=33.70]
Epoch 0: | | 155/? [00:27<00:00, 5.63it/s, train/loss=33.70]
Epoch 0: | | 155/? [00:27<00:00, 5.63it/s, train/loss=5.930]
Epoch 0: | | 156/? [00:27<00:00, 5.60it/s, train/loss=5.930]
Epoch 0: | | 156/? [00:27<00:00, 5.60it/s, train/loss=35.70]
Epoch 0: | | 157/? [00:27<00:00, 5.63it/s, train/loss=35.70]
Epoch 0: | | 157/? [00:27<00:00, 5.63it/s, train/loss=5.870]
Epoch 0: | | 158/? [00:28<00:00, 5.60it/s, train/loss=5.870]
Epoch 0: | | 158/? [00:28<00:00, 5.60it/s, train/loss=26.40]
Epoch 0: | | 159/? [00:28<00:00, 5.63it/s, train/loss=26.40]
Epoch 0: | | 159/? [00:28<00:00, 5.63it/s, train/loss=5.840]
Epoch 0: | | 160/? [00:28<00:00, 5.61it/s, train/loss=5.840]
Epoch 0: | | 160/? [00:28<00:00, 5.61it/s, train/loss=49.70]
Epoch 0: | | 161/? [00:28<00:00, 5.64it/s, train/loss=49.70]
Epoch 0: | | 161/? [00:28<00:00, 5.64it/s, train/loss=5.760]
Epoch 0: | | 162/? [00:28<00:00, 5.61it/s, train/loss=5.760]
Epoch 0: | | 162/? [00:28<00:00, 5.61it/s, train/loss=51.80]
Epoch 0: | | 163/? [00:28<00:00, 5.64it/s, train/loss=51.80]
Epoch 0: | | 163/? [00:28<00:00, 5.64it/s, train/loss=5.590]
Epoch 0: | | 164/? [00:29<00:00, 5.62it/s, train/loss=5.590]
Epoch 0: | | 164/? [00:29<00:00, 5.62it/s, train/loss=25.90]
Epoch 0: | | 165/? [00:29<00:00, 5.65it/s, train/loss=25.90]
Epoch 0: | | 165/? [00:29<00:00, 5.65it/s, train/loss=5.480]
Epoch 0: | | 166/? [00:29<00:00, 5.63it/s, train/loss=5.480]
Epoch 0: | | 166/? [00:29<00:00, 5.62it/s, train/loss=44.60]
Epoch 0: | | 167/? [00:29<00:00, 5.65it/s, train/loss=44.60]
Epoch 0: | | 167/? [00:29<00:00, 5.65it/s, train/loss=5.450]
Epoch 0: | | 168/? [00:29<00:00, 5.63it/s, train/loss=5.450]
Epoch 0: | | 168/? [00:29<00:00, 5.63it/s, train/loss=28.10]
Epoch 0: | | 169/? [00:29<00:00, 5.66it/s, train/loss=28.10]
Epoch 0: | | 169/? [00:29<00:00, 5.66it/s, train/loss=5.520]
Epoch 0: | | 170/? [00:30<00:00, 5.63it/s, train/loss=5.520]
Epoch 0: | | 170/? [00:30<00:00, 5.63it/s, train/loss=40.30]
Epoch 0: | | 171/? [00:30<00:00, 5.66it/s, train/loss=40.30]
Epoch 0: | | 171/? [00:30<00:00, 5.66it/s, train/loss=5.610]
Epoch 0: | | 172/? [00:30<00:00, 5.64it/s, train/loss=5.610]
Epoch 0: | | 172/? [00:30<00:00, 5.64it/s, train/loss=31.20]
Epoch 0: | | 173/? [00:30<00:00, 5.66it/s, train/loss=31.20]
Epoch 0: | | 173/? [00:30<00:00, 5.66it/s, train/loss=5.690]
Epoch 0: | | 174/? [00:30<00:00, 5.64it/s, train/loss=5.690]
Epoch 0: | | 174/? [00:30<00:00, 5.64it/s, train/loss=22.80]
Epoch 0: | | 175/? [00:30<00:00, 5.66it/s, train/loss=22.80]
Epoch 0: | | 175/? [00:30<00:00, 5.66it/s, train/loss=5.640]
Epoch 0: | | 176/? [00:31<00:00, 5.64it/s, train/loss=5.640]
Epoch 0: | | 176/? [00:31<00:00, 5.64it/s, train/loss=38.40]
Epoch 0: | | 177/? [00:31<00:00, 5.67it/s, train/loss=38.40]
Epoch 0: | | 177/? [00:31<00:00, 5.66it/s, train/loss=5.450]
Epoch 0: | | 178/? [00:31<00:00, 5.65it/s, train/loss=5.450]
Epoch 0: | | 178/? [00:31<00:00, 5.64it/s, train/loss=25.80]
Epoch 0: | | 179/? [00:31<00:00, 5.67it/s, train/loss=25.80]
Epoch 0: | | 179/? [00:31<00:00, 5.67it/s, train/loss=5.300]
Epoch 0: | | 180/? [00:31<00:00, 5.65it/s, train/loss=5.300]
Epoch 0: | | 180/? [00:31<00:00, 5.65it/s, train/loss=46.20]
Epoch 0: | | 181/? [00:31<00:00, 5.68it/s, train/loss=46.20]
Epoch 0: | | 181/? [00:31<00:00, 5.68it/s, train/loss=5.170]
Epoch 0: | | 182/? [00:32<00:00, 5.66it/s, train/loss=5.170]
Epoch 0: | | 182/? [00:32<00:00, 5.66it/s, train/loss=28.60]
Epoch 0: | | 183/? [00:32<00:00, 5.68it/s, train/loss=28.60]
Epoch 0: | | 183/? [00:32<00:00, 5.68it/s, train/loss=5.060]
Epoch 0: | | 184/? [00:32<00:00, 5.66it/s, train/loss=5.060]
Epoch 0: | | 184/? [00:32<00:00, 5.66it/s, train/loss=25.50]
Epoch 0: | | 185/? [00:32<00:00, 5.68it/s, train/loss=25.50]
Epoch 0: | | 185/? [00:32<00:00, 5.68it/s, train/loss=5.020]
Epoch 0: | | 186/? [00:32<00:00, 5.66it/s, train/loss=5.020]
Epoch 0: | | 186/? [00:32<00:00, 5.66it/s, train/loss=20.50]
Epoch 0: | | 187/? [00:32<00:00, 5.69it/s, train/loss=20.50]
Epoch 0: | | 187/? [00:32<00:00, 5.69it/s, train/loss=4.970]
Epoch 0: | | 188/? [00:33<00:00, 5.67it/s, train/loss=4.970]
Epoch 0: | | 188/? [00:33<00:00, 5.67it/s, train/loss=21.20]
Epoch 0: | | 189/? [00:33<00:00, 5.69it/s, train/loss=21.20]
Epoch 0: | | 189/? [00:33<00:00, 5.69it/s, train/loss=4.920]
Epoch 0: | | 190/? [00:33<00:00, 5.67it/s, train/loss=4.920]
Epoch 0: | | 190/? [00:33<00:00, 5.67it/s, train/loss=31.50]
Epoch 0: | | 191/? [00:33<00:00, 5.70it/s, train/loss=31.50]
Epoch 0: | | 191/? [00:33<00:00, 5.70it/s, train/loss=4.870]
Epoch 0: | | 192/? [00:33<00:00, 5.68it/s, train/loss=4.870]
Epoch 0: | | 192/? [00:33<00:00, 5.68it/s, train/loss=65.00]
Epoch 0: | | 193/? [00:33<00:00, 5.70it/s, train/loss=65.00]
Epoch 0: | | 193/? [00:33<00:00, 5.70it/s, train/loss=4.860]
Epoch 0: | | 194/? [00:34<00:00, 5.68it/s, train/loss=4.860]
Epoch 0: | | 194/? [00:34<00:00, 5.68it/s, train/loss=19.90]
Epoch 0: | | 195/? [00:34<00:00, 5.71it/s, train/loss=19.90]
Epoch 0: | | 195/? [00:34<00:00, 5.71it/s, train/loss=4.850]
Epoch 0: | | 196/? [00:34<00:00, 5.69it/s, train/loss=4.850]
Epoch 0: | | 196/? [00:34<00:00, 5.69it/s, train/loss=25.90]
Epoch 0: | | 197/? [00:34<00:00, 5.71it/s, train/loss=25.90]
Epoch 0: | | 197/? [00:34<00:00, 5.71it/s, train/loss=4.860]
Epoch 0: | | 198/? [00:34<00:00, 5.69it/s, train/loss=4.860]
Epoch 0: | | 198/? [00:34<00:00, 5.69it/s, train/loss=41.40]
Epoch 0: | | 199/? [00:34<00:00, 5.71it/s, train/loss=41.40]
Epoch 0: | | 199/? [00:34<00:00, 5.71it/s, train/loss=4.860]
Epoch 0: | | 200/? [00:35<00:00, 5.70it/s, train/loss=4.860]
Epoch 0: | | 200/? [00:35<00:00, 5.70it/s, train/loss=22.20]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:00, 53.35it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:00, 54.05it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:00, 54.08it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:00, 54.15it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:00, 54.23it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:00, 54.34it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:00, 54.29it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:00, 54.34it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:00, 54.38it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:00, 54.49it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:00, 54.56it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:00<00:00, 54.56it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:00<00:00, 54.60it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:00<00:00, 54.60it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:00<00:00, 54.60it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:00<00:00, 54.59it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:00<00:00, 53.41it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:00<00:00, 53.67it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:00<00:00, 53.89it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:00<00:00, 54.02it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:00<00:00, 54.18it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:00<00:00, 54.30it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:00<00:00, 54.46it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:00<00:00, 54.60it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:00<00:00, 54.73it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:00<00:00, 54.86it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:00<00:00, 54.97it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:00<00:00, 55.03it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:00<00:00, 54.81it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:00<00:00, 54.89it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:00<00:00, 54.48it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:00<00:00, 54.12it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:00<00:00, 53.75it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:00<00:00, 53.80it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:00<00:00, 53.90it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:00<00:00, 54.01it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:00<00:00, 54.00it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:00<00:00, 53.98it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:00<00:00, 53.96it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 53.95it/s][A
[A
Epoch 0: | | 200/? [00:36<00:00, 5.50it/s, train/loss=22.20]
Epoch 0: | | 201/? [00:36<00:00, 5.49it/s, train/loss=22.20]
Epoch 0: | | 201/? [00:36<00:00, 5.49it/s, train/loss=4.850]
Epoch 0: | | 202/? [00:36<00:00, 5.47it/s, train/loss=4.850]
Epoch 0: | | 202/? [00:36<00:00, 5.47it/s, train/loss=16.20]
Epoch 0: | | 203/? [00:36<00:00, 5.49it/s, train/loss=16.20]
Epoch 0: | | 203/? [00:36<00:00, 5.49it/s, train/loss=4.840]
Epoch 0: | | 204/? [00:37<00:00, 5.48it/s, train/loss=4.840]
Epoch 0: | | 204/? [00:37<00:00, 5.48it/s, train/loss=40.60]
Epoch 0: | | 205/? [00:37<00:00, 5.50it/s, train/loss=40.60]
Epoch 0: | | 205/? [00:37<00:00, 5.50it/s, train/loss=4.810]
Epoch 0: | | 206/? [00:37<00:00, 5.48it/s, train/loss=4.810]
Epoch 0: | | 206/? [00:37<00:00, 5.48it/s, train/loss=15.70]
Epoch 0: | | 207/? [00:37<00:00, 5.51it/s, train/loss=15.70]
Epoch 0: | | 207/? [00:37<00:00, 5.51it/s, train/loss=4.780]
Epoch 0: | | 208/? [00:37<00:00, 5.49it/s, train/loss=4.780]
Epoch 0: | | 208/? [00:37<00:00, 5.49it/s, train/loss=10.70]
Epoch 0: | | 209/? [00:37<00:00, 5.51it/s, train/loss=10.70]
Epoch 0: | | 209/? [00:37<00:00, 5.51it/s, train/loss=4.740]
Epoch 0: | | 210/? [00:38<00:00, 5.50it/s, train/loss=4.740]
Epoch 0: | | 210/? [00:38<00:00, 5.50it/s, train/loss=34.00]
Epoch 0: | | 211/? [00:38<00:00, 5.51it/s, train/loss=34.00]
Epoch 0: | | 211/? [00:38<00:00, 5.51it/s, train/loss=4.660]
Epoch 0: | | 212/? [00:38<00:00, 5.50it/s, train/loss=4.660]
Epoch 0: | | 212/? [00:38<00:00, 5.50it/s, train/loss=30.70]
Epoch 0: | | 213/? [00:38<00:00, 5.52it/s, train/loss=30.70]
Epoch 0: | | 213/? [00:38<00:00, 5.52it/s, train/loss=4.570]
Epoch 0: | | 214/? [00:38<00:00, 5.50it/s, train/loss=4.570]
Epoch 0: | | 214/? [00:38<00:00, 5.50it/s, train/loss=15.90]
Epoch 0: | | 215/? [00:38<00:00, 5.52it/s, train/loss=15.90]
Epoch 0: | | 215/? [00:38<00:00, 5.52it/s, train/loss=4.540]
Epoch 0: | | 216/? [00:39<00:00, 5.50it/s, train/loss=4.540]
Epoch 0: | | 216/? [00:39<00:00, 5.50it/s, train/loss=25.80]
Epoch 0: | | 217/? [00:39<00:00, 5.52it/s, train/loss=25.80]
Epoch 0: | | 217/? [00:39<00:00, 5.52it/s, train/loss=4.500]
Epoch 0: | | 218/? [00:39<00:00, 5.50it/s, train/loss=4.500]
Epoch 0: | | 218/? [00:39<00:00, 5.50it/s, train/loss=30.50]
Epoch 0: | | 219/? [00:39<00:00, 5.52it/s, train/loss=30.50]
Epoch 0: | | 219/? [00:39<00:00, 5.52it/s, train/loss=4.460]
Epoch 0: | | 220/? [00:39<00:00, 5.50it/s, train/loss=4.460]
Epoch 0: | | 220/? [00:39<00:00, 5.50it/s, train/loss=67.90]
Epoch 0: | | 221/? [00:40<00:00, 5.52it/s, train/loss=67.90]
Epoch 0: | | 221/? [00:40<00:00, 5.52it/s, train/loss=4.400]
Epoch 0: | | 222/? [00:40<00:00, 5.50it/s, train/loss=4.400]
Epoch 0: | | 222/? [00:40<00:00, 5.50it/s, train/loss=21.40]
Epoch 0: | | 223/? [00:40<00:00, 5.52it/s, train/loss=21.40]
Epoch 0: | | 223/? [00:40<00:00, 5.52it/s, train/loss=4.370]
Epoch 0: | | 224/? [00:40<00:00, 5.50it/s, train/loss=4.370]
Epoch 0: | | 224/? [00:40<00:00, 5.50it/s, train/loss=37.50]
Epoch 0: | | 225/? [00:40<00:00, 5.52it/s, train/loss=37.50]
Epoch 0: | | 225/? [00:40<00:00, 5.52it/s, train/loss=4.340]
Epoch 0: | | 226/? [00:41<00:00, 5.50it/s, train/loss=4.340]
Epoch 0: | | 226/? [00:41<00:00, 5.50it/s, train/loss=8.740]
Epoch 0: | | 227/? [00:41<00:00, 5.52it/s, train/loss=8.740]
Epoch 0: | | 227/? [00:41<00:00, 5.52it/s, train/loss=4.320]
Epoch 0: | | 228/? [00:41<00:00, 5.50it/s, train/loss=4.320]
Epoch 0: | | 228/? [00:41<00:00, 5.50it/s, train/loss=11.40]
Epoch 0: | | 229/? [00:41<00:00, 5.52it/s, train/loss=11.40]
Epoch 0: | | 229/? [00:41<00:00, 5.52it/s, train/loss=4.270]
Epoch 0: | | 230/? [00:41<00:00, 5.50it/s, train/loss=4.270]
Epoch 0: | | 230/? [00:41<00:00, 5.50it/s, train/loss=16.20]
Epoch 0: | | 231/? [00:41<00:00, 5.52it/s, train/loss=16.20]
Epoch 0: | | 231/? [00:41<00:00, 5.52it/s, train/loss=4.210]
Epoch 0: | | 232/? [00:42<00:00, 5.51it/s, train/loss=4.210]
Epoch 0: | | 232/? [00:42<00:00, 5.51it/s, train/loss=14.70]
Epoch 0: | | 233/? [00:42<00:00, 5.52it/s, train/loss=14.70]
Epoch 0: | | 233/? [00:42<00:00, 5.52it/s, train/loss=4.140]
Epoch 0: | | 234/? [00:42<00:00, 5.51it/s, train/loss=4.140]
Epoch 0: | | 234/? [00:42<00:00, 5.51it/s, train/loss=13.80]
Epoch 0: | | 235/? [00:42<00:00, 5.52it/s, train/loss=13.80]
Epoch 0: | | 235/? [00:42<00:00, 5.52it/s, train/loss=4.070]
Epoch 0: | | 236/? [00:42<00:00, 5.51it/s, train/loss=4.070]
Epoch 0: | | 236/? [00:42<00:00, 5.51it/s, train/loss=21.90]
Epoch 0: | | 237/? [00:42<00:00, 5.52it/s, train/loss=21.90]
Epoch 0: | | 237/? [00:42<00:00, 5.52it/s, train/loss=3.970]
Epoch 0: | | 238/? [00:43<00:00, 5.51it/s, train/loss=3.970]
Epoch 0: | | 238/? [00:43<00:00, 5.51it/s, train/loss=30.50]
Epoch 0: | | 239/? [00:43<00:00, 5.53it/s, train/loss=30.50]
Epoch 0: | | 239/? [00:43<00:00, 5.53it/s, train/loss=3.910]
Epoch 0: | | 240/? [00:43<00:00, 5.51it/s, train/loss=3.910]
Epoch 0: | | 240/? [00:43<00:00, 5.51it/s, train/loss=12.20]
Epoch 0: | | 241/? [00:43<00:00, 5.53it/s, train/loss=12.20]
Epoch 0: | | 241/? [00:43<00:00, 5.53it/s, train/loss=3.890]
Epoch 0: | | 242/? [00:43<00:00, 5.51it/s, train/loss=3.890]
Epoch 0: | | 242/? [00:43<00:00, 5.51it/s, train/loss=52.70]
Epoch 0: | | 243/? [00:43<00:00, 5.53it/s, train/loss=52.70]
Epoch 0: | | 243/? [00:43<00:00, 5.53it/s, train/loss=3.820]
Epoch 0: | | 244/? [00:44<00:00, 5.51it/s, train/loss=3.820]
Epoch 0: | | 244/? [00:44<00:00, 5.51it/s, train/loss=12.60]
Epoch 0: | | 245/? [00:44<00:00, 5.53it/s, train/loss=12.60]
Epoch 0: | | 245/? [00:44<00:00, 5.53it/s, train/loss=3.750]
Epoch 0: | | 246/? [00:44<00:00, 5.52it/s, train/loss=3.750]
Epoch 0: | | 246/? [00:44<00:00, 5.52it/s, train/loss=22.40]
Epoch 0: | | 247/? [00:44<00:00, 5.53it/s, train/loss=22.40]
Epoch 0: | | 247/? [00:44<00:00, 5.53it/s, train/loss=3.740]
Epoch 0: | | 248/? [00:44<00:00, 5.52it/s, train/loss=3.740]
Epoch 0: | | 248/? [00:44<00:00, 5.52it/s, train/loss=31.60]
Epoch 0: | | 249/? [00:44<00:00, 5.54it/s, train/loss=31.60]
Epoch 0: | | 249/? [00:44<00:00, 5.54it/s, train/loss=3.760]
Epoch 0: | | 250/? [00:45<00:00, 5.53it/s, train/loss=3.760]
Epoch 0: | | 250/? [00:45<00:00, 5.53it/s, train/loss=9.880]
Epoch 0: | | 251/? [00:45<00:00, 5.54it/s, train/loss=9.880]
Epoch 0: | | 251/? [00:45<00:00, 5.54it/s, train/loss=3.770]
Epoch 0: | | 252/? [00:45<00:00, 5.53it/s, train/loss=3.770]
Epoch 0: | | 252/? [00:45<00:00, 5.53it/s, train/loss=28.30]
Epoch 0: | | 253/? [00:45<00:00, 5.55it/s, train/loss=28.30]
Epoch 0: | | 253/? [00:45<00:00, 5.55it/s, train/loss=3.730]
Epoch 0: | | 254/? [00:45<00:00, 5.54it/s, train/loss=3.730]
Epoch 0: | | 254/? [00:45<00:00, 5.54it/s, train/loss=11.40]
Epoch 0: | | 255/? [00:45<00:00, 5.55it/s, train/loss=11.40]
Epoch 0: | | 255/? [00:45<00:00, 5.55it/s, train/loss=3.640]
Epoch 0: | | 256/? [00:46<00:00, 5.54it/s, train/loss=3.640]
Epoch 0: | | 256/? [00:46<00:00, 5.54it/s, train/loss=24.80]
Epoch 0: | | 257/? [00:46<00:00, 5.56it/s, train/loss=24.80]
Epoch 0: | | 257/? [00:46<00:00, 5.56it/s, train/loss=3.570]
Epoch 0: | | 258/? [00:46<00:00, 5.54it/s, train/loss=3.570]
Epoch 0: | | 258/? [00:46<00:00, 5.54it/s, train/loss=37.10]
Epoch 0: | | 259/? [00:46<00:00, 5.56it/s, train/loss=37.10]
Epoch 0: | | 259/? [00:46<00:00, 5.56it/s, train/loss=3.530]
Epoch 0: | | 260/? [00:46<00:00, 5.55it/s, train/loss=3.530]
Epoch 0: | | 260/? [00:46<00:00, 5.55it/s, train/loss=23.60]
Epoch 0: | | 261/? [00:46<00:00, 5.56it/s, train/loss=23.60]
Epoch 0: | | 261/? [00:46<00:00, 5.56it/s, train/loss=3.540]
Epoch 0: | | 262/? [00:47<00:00, 5.55it/s, train/loss=3.540]
Epoch 0: | | 262/? [00:47<00:00, 5.55it/s, train/loss=45.00]
Epoch 0: | | 263/? [00:47<00:00, 5.57it/s, train/loss=45.00]
Epoch 0: | | 263/? [00:47<00:00, 5.57it/s, train/loss=3.530]
Epoch 0: | | 264/? [00:47<00:00, 5.55it/s, train/loss=3.530]
Epoch 0: | | 264/? [00:47<00:00, 5.55it/s, train/loss=10.10]
Epoch 0: | | 265/? [00:47<00:00, 5.57it/s, train/loss=10.10]
Epoch 0: | | 265/? [00:47<00:00, 5.57it/s, train/loss=3.530]
Epoch 0: | | 266/? [00:47<00:00, 5.56it/s, train/loss=3.530]
Epoch 0: | | 266/? [00:47<00:00, 5.56it/s, train/loss=12.90]
Epoch 0: | | 267/? [00:47<00:00, 5.57it/s, train/loss=12.90]
Epoch 0: | | 267/? [00:47<00:00, 5.57it/s, train/loss=3.530]
Epoch 0: | | 268/? [00:48<00:00, 5.56it/s, train/loss=3.530]
Epoch 0: | | 268/? [00:48<00:00, 5.56it/s, train/loss=32.20]
Epoch 0: | | 269/? [00:48<00:00, 5.58it/s, train/loss=32.20]
Epoch 0: | | 269/? [00:48<00:00, 5.58it/s, train/loss=3.480]
Epoch 0: | | 270/? [00:48<00:00, 5.57it/s, train/loss=3.480]
Epoch 0: | | 270/? [00:48<00:00, 5.57it/s, train/loss=10.20]
Epoch 0: | | 271/? [00:48<00:00, 5.58it/s, train/loss=10.20]
Epoch 0: | | 271/? [00:48<00:00, 5.58it/s, train/loss=3.440]
Epoch 0: | | 272/? [00:48<00:00, 5.57it/s, train/loss=3.440]
Epoch 0: | | 272/? [00:48<00:00, 5.57it/s, train/loss=9.860]
Epoch 0: | | 273/? [00:48<00:00, 5.59it/s, train/loss=9.860]
Epoch 0: | | 273/? [00:48<00:00, 5.59it/s, train/loss=3.400]
Epoch 0: | | 274/? [00:49<00:00, 5.57it/s, train/loss=3.400]
Epoch 0: | | 274/? [00:49<00:00, 5.57it/s, train/loss=25.90]
Epoch 0: | | 275/? [00:49<00:00, 5.59it/s, train/loss=25.90]
Epoch 0: | | 275/? [00:49<00:00, 5.59it/s, train/loss=3.400]
Epoch 0: | | 276/? [00:49<00:00, 5.58it/s, train/loss=3.400]
Epoch 0: | | 276/? [00:49<00:00, 5.58it/s, train/loss=37.60]
Epoch 0: | | 277/? [00:49<00:00, 5.59it/s, train/loss=37.60]
Epoch 0: | | 277/? [00:49<00:00, 5.59it/s, train/loss=3.430]
Epoch 0: | | 278/? [00:49<00:00, 5.58it/s, train/loss=3.430]
Epoch 0: | | 278/? [00:49<00:00, 5.58it/s, train/loss=18.80]
Epoch 0: | | 279/? [00:49<00:00, 5.60it/s, train/loss=18.80]
Epoch 0: | | 279/? [00:49<00:00, 5.60it/s, train/loss=3.440]
Epoch 0: | | 280/? [00:50<00:00, 5.58it/s, train/loss=3.440]
Epoch 0: | | 280/? [00:50<00:00, 5.58it/s, train/loss=28.50]
Epoch 0: | | 281/? [00:50<00:00, 5.60it/s, train/loss=28.50]
Epoch 0: | | 281/? [00:50<00:00, 5.60it/s, train/loss=3.410]
Epoch 0: | | 282/? [00:50<00:00, 5.59it/s, train/loss=3.410]
Epoch 0: | | 282/? [00:50<00:00, 5.59it/s, train/loss=9.970]
Epoch 0: | | 283/? [00:50<00:00, 5.60it/s, train/loss=9.970]
Epoch 0: | | 283/? [00:50<00:00, 5.60it/s, train/loss=3.390]
Epoch 0: | | 284/? [00:50<00:00, 5.59it/s, train/loss=3.390]
Epoch 0: | | 284/? [00:50<00:00, 5.59it/s, train/loss=40.30]
Epoch 0: | | 285/? [00:50<00:00, 5.60it/s, train/loss=40.30]
Epoch 0: | | 285/? [00:50<00:00, 5.60it/s, train/loss=3.380]
Epoch 0: | | 286/? [00:51<00:00, 5.59it/s, train/loss=3.380]
Epoch 0: | | 286/? [00:51<00:00, 5.59it/s, train/loss=31.70]
Epoch 0: | | 287/? [00:51<00:00, 5.61it/s, train/loss=31.70]
Epoch 0: | | 287/? [00:51<00:00, 5.61it/s, train/loss=3.400]
Epoch 0: | | 288/? [00:51<00:00, 5.60it/s, train/loss=3.400]
Epoch 0: | | 288/? [00:51<00:00, 5.60it/s, train/loss=15.20]
Epoch 0: | | 289/? [00:51<00:00, 5.61it/s, train/loss=15.20]
Epoch 0: | | 289/? [00:51<00:00, 5.61it/s, train/loss=3.410]
Epoch 0: | | 290/? [00:51<00:00, 5.60it/s, train/loss=3.410]
Epoch 0: | | 290/? [00:51<00:00, 5.60it/s, train/loss=14.10]
Epoch 0: | | 291/? [00:51<00:00, 5.61it/s, train/loss=14.10]
Epoch 0: | | 291/? [00:51<00:00, 5.61it/s, train/loss=3.420]
Epoch 0: | | 292/? [00:52<00:00, 5.60it/s, train/loss=3.420]
Epoch 0: | | 292/? [00:52<00:00, 5.60it/s, train/loss=19.10]
Epoch 0: | | 293/? [00:52<00:00, 5.61it/s, train/loss=19.10]
Epoch 0: | | 293/? [00:52<00:00, 5.61it/s, train/loss=3.400]
Epoch 0: | | 294/? [00:52<00:00, 5.60it/s, train/loss=3.400]
Epoch 0: | | 294/? [00:52<00:00, 5.60it/s, train/loss=24.80]
Epoch 0: | | 295/? [00:52<00:00, 5.62it/s, train/loss=24.80]
Epoch 0: | | 295/? [00:52<00:00, 5.62it/s, train/loss=3.340]
Epoch 0: | | 296/? [00:52<00:00, 5.61it/s, train/loss=3.340]
Epoch 0: | | 296/? [00:52<00:00, 5.60it/s, train/loss=39.10]
Epoch 0: | | 297/? [00:52<00:00, 5.62it/s, train/loss=39.10]
Epoch 0: | | 297/? [00:52<00:00, 5.62it/s, train/loss=3.290]
Epoch 0: | | 298/? [00:53<00:00, 5.61it/s, train/loss=3.290]
Epoch 0: | | 298/? [00:53<00:00, 5.61it/s, train/loss=8.320]
Epoch 0: | | 299/? [00:53<00:00, 5.62it/s, train/loss=8.320]
Epoch 0: | | 299/? [00:53<00:00, 5.62it/s, train/loss=3.340]
Epoch 0: | | 300/? [00:53<00:00, 5.61it/s, train/loss=3.340]
Epoch 0: | | 300/? [00:53<00:00, 5.61it/s, train/loss=19.60]
Epoch 0: | | 301/? [00:53<00:00, 5.63it/s, train/loss=19.60]
Epoch 0: | | 301/? [00:53<00:00, 5.63it/s, train/loss=3.370]
Epoch 0: | | 302/? [00:53<00:00, 5.61it/s, train/loss=3.370]
Epoch 0: | | 302/? [00:53<00:00, 5.61it/s, train/loss=28.90]
Epoch 0: | | 303/? [00:53<00:00, 5.63it/s, train/loss=28.90]
Epoch 0: | | 303/? [00:53<00:00, 5.63it/s, train/loss=3.270]
Epoch 0: | | 304/? [00:54<00:00, 5.62it/s, train/loss=3.270]
Epoch 0: | | 304/? [00:54<00:00, 5.62it/s, train/loss=24.00]
Epoch 0: | | 305/? [00:54<00:00, 5.63it/s, train/loss=24.00]
Epoch 0: | | 305/? [00:54<00:00, 5.63it/s, train/loss=3.110]
Epoch 0: | | 306/? [00:54<00:00, 5.62it/s, train/loss=3.110]
Epoch 0: | | 306/? [00:54<00:00, 5.62it/s, train/loss=18.70]
Epoch 0: | | 307/? [00:54<00:00, 5.63it/s, train/loss=18.70]
Epoch 0: | | 307/? [00:54<00:00, 5.63it/s, train/loss=3.060]
Epoch 0: | | 308/? [00:54<00:00, 5.62it/s, train/loss=3.060]
Epoch 0: | | 308/? [00:54<00:00, 5.62it/s, train/loss=24.10]
Epoch 0: | | 309/? [00:54<00:00, 5.63it/s, train/loss=24.10]
Epoch 0: | | 309/? [00:54<00:00, 5.63it/s, train/loss=3.140]
Epoch 0: | | 310/? [00:55<00:00, 5.62it/s, train/loss=3.140]
Epoch 0: | | 310/? [00:55<00:00, 5.62it/s, train/loss=24.70]
Epoch 0: | | 311/? [00:55<00:00, 5.63it/s, train/loss=24.70]
Epoch 0: | | 311/? [00:55<00:00, 5.63it/s, train/loss=3.210]
Epoch 0: | | 312/? [00:55<00:00, 5.62it/s, train/loss=3.210]
Epoch 0: | | 312/? [00:55<00:00, 5.62it/s, train/loss=15.20]
Epoch 0: | | 313/? [00:55<00:00, 5.64it/s, train/loss=15.20]
Epoch 0: | | 313/? [00:55<00:00, 5.64it/s, train/loss=3.240]
Epoch 0: | | 314/? [00:55<00:00, 5.63it/s, train/loss=3.240]
Epoch 0: | | 314/? [00:55<00:00, 5.63it/s, train/loss=31.30]
Epoch 0: | | 315/? [00:55<00:00, 5.64it/s, train/loss=31.30]
Epoch 0: | | 315/? [00:55<00:00, 5.64it/s, train/loss=3.230]
Epoch 0: | | 316/? [00:56<00:00, 5.63it/s, train/loss=3.230]
Epoch 0: | | 316/? [00:56<00:00, 5.63it/s, train/loss=16.70]
Epoch 0: | | 317/? [00:56<00:00, 5.64it/s, train/loss=16.70]
Epoch 0: | | 317/? [00:56<00:00, 5.64it/s, train/loss=3.200]
Epoch 0: | | 318/? [00:56<00:00, 5.63it/s, train/loss=3.200]
Epoch 0: | | 318/? [00:56<00:00, 5.63it/s, train/loss=18.80]
Epoch 0: | | 319/? [00:56<00:00, 5.65it/s, train/loss=18.80]
Epoch 0: | | 319/? [00:56<00:00, 5.65it/s, train/loss=3.190]
Epoch 0: | | 320/? [00:56<00:00, 5.64it/s, train/loss=3.190]
Epoch 0: | | 320/? [00:56<00:00, 5.64it/s, train/loss=37.10]
Epoch 0: | | 321/? [00:56<00:00, 5.65it/s, train/loss=37.10]
Epoch 0: | | 321/? [00:56<00:00, 5.65it/s, train/loss=3.160]
Epoch 0: | | 322/? [00:57<00:00, 5.64it/s, train/loss=3.160]
Epoch 0: | | 322/? [00:57<00:00, 5.64it/s, train/loss=29.70]
Epoch 0: | | 323/? [00:57<00:00, 5.65it/s, train/loss=29.70]
Epoch 0: | | 323/? [00:57<00:00, 5.65it/s, train/loss=3.120]
Epoch 0: | | 324/? [00:57<00:00, 5.64it/s, train/loss=3.120]
Epoch 0: | | 324/? [00:57<00:00, 5.64it/s, train/loss=22.20]
Epoch 0: | | 325/? [00:57<00:00, 5.66it/s, train/loss=22.20]
Epoch 0: | | 325/? [00:57<00:00, 5.66it/s, train/loss=3.130]
Epoch 0: | | 326/? [00:57<00:00, 5.65it/s, train/loss=3.130]
Epoch 0: | | 326/? [00:57<00:00, 5.65it/s, train/loss=23.50]
Epoch 0: | | 327/? [00:57<00:00, 5.66it/s, train/loss=23.50]
Epoch 0: | | 327/? [00:57<00:00, 5.66it/s, train/loss=3.110]
Epoch 0: | | 328/? [00:58<00:00, 5.65it/s, train/loss=3.110]
Epoch 0: | | 328/? [00:58<00:00, 5.65it/s, train/loss=37.80]
Epoch 0: | | 329/? [00:58<00:00, 5.66it/s, train/loss=37.80]
Epoch 0: | | 329/? [00:58<00:00, 5.66it/s, train/loss=3.010]
Epoch 0: | | 330/? [00:58<00:00, 5.65it/s, train/loss=3.010]
Epoch 0: | | 330/? [00:58<00:00, 5.65it/s, train/loss=30.40]
Epoch 0: | | 331/? [00:58<00:00, 5.66it/s, train/loss=30.40]
Epoch 0: | | 331/? [00:58<00:00, 5.66it/s, train/loss=2.920]
Epoch 0: | | 332/? [00:58<00:00, 5.65it/s, train/loss=2.920]
Epoch 0: | | 332/? [00:58<00:00, 5.65it/s, train/loss=20.70]
Epoch 0: | | 333/? [00:58<00:00, 5.67it/s, train/loss=20.70]
Epoch 0: | | 333/? [00:58<00:00, 5.67it/s, train/loss=2.860]
Epoch 0: | | 334/? [00:59<00:00, 5.66it/s, train/loss=2.860]
Epoch 0: | | 334/? [00:59<00:00, 5.66it/s, train/loss=10.10]
Epoch 0: | | 335/? [00:59<00:00, 5.67it/s, train/loss=10.10]
Epoch 0: | | 335/? [00:59<00:00, 5.67it/s, train/loss=2.800]
Epoch 0: | | 336/? [00:59<00:00, 5.66it/s, train/loss=2.800]
Epoch 0: | | 336/? [00:59<00:00, 5.66it/s, train/loss=38.50]
Epoch 0: | | 337/? [00:59<00:00, 5.67it/s, train/loss=38.50]
Epoch 0: | | 337/? [00:59<00:00, 5.67it/s, train/loss=2.760]
Epoch 0: | | 338/? [00:59<00:00, 5.66it/s, train/loss=2.760]
Epoch 0: | | 338/? [00:59<00:00, 5.66it/s, train/loss=17.30]
Epoch 0: | | 339/? [00:59<00:00, 5.68it/s, train/loss=17.30]
Epoch 0: | | 339/? [00:59<00:00, 5.68it/s, train/loss=2.760]
Epoch 0: | | 340/? [01:00<00:00, 5.66it/s, train/loss=2.760]
Epoch 0: | | 340/? [01:00<00:00, 5.66it/s, train/loss=30.30]
Epoch 0: | | 341/? [01:00<00:00, 5.68it/s, train/loss=30.30]
Epoch 0: | | 341/? [01:00<00:00, 5.68it/s, train/loss=2.770]
Epoch 0: | | 342/? [01:00<00:00, 5.67it/s, train/loss=2.770]
Epoch 0: | | 342/? [01:00<00:00, 5.67it/s, train/loss=40.10]
Epoch 0: | | 343/? [01:00<00:00, 5.68it/s, train/loss=40.10]
Epoch 0: | | 343/? [01:00<00:00, 5.68it/s, train/loss=2.790]
Epoch 0: | | 344/? [01:00<00:00, 5.67it/s, train/loss=2.790]
Epoch 0: | | 344/? [01:00<00:00, 5.67it/s, train/loss=7.000]
Epoch 0: | | 345/? [01:00<00:00, 5.68it/s, train/loss=7.000]
Epoch 0: | | 345/? [01:00<00:00, 5.68it/s, train/loss=2.850]
Epoch 0: | | 346/? [01:00<00:00, 5.67it/s, train/loss=2.850]
Epoch 0: | | 346/? [01:00<00:00, 5.67it/s, train/loss=23.60]
Epoch 0: | | 347/? [01:01<00:00, 5.69it/s, train/loss=23.60]
Epoch 0: | | 347/? [01:01<00:00, 5.69it/s, train/loss=2.880]
Epoch 0: | | 348/? [01:01<00:00, 5.68it/s, train/loss=2.880]
Epoch 0: | | 348/? [01:01<00:00, 5.68it/s, train/loss=57.60]
Epoch 0: | | 349/? [01:01<00:00, 5.69it/s, train/loss=57.60]
Epoch 0: | | 349/? [01:01<00:00, 5.69it/s, train/loss=2.860]
Epoch 0: | | 350/? [01:01<00:00, 5.68it/s, train/loss=2.860]
Epoch 0: | | 350/? [01:01<00:00, 5.68it/s, train/loss=14.50]
Epoch 0: | | 351/? [01:01<00:00, 5.69it/s, train/loss=14.50]
Epoch 0: | | 351/? [01:01<00:00, 5.69it/s, train/loss=2.870]
Epoch 0: | | 352/? [01:01<00:00, 5.68it/s, train/loss=2.870]
Epoch 0: | | 352/? [01:01<00:00, 5.68it/s, train/loss=11.60]
Epoch 0: | | 353/? [01:01<00:00, 5.69it/s, train/loss=11.60]
Epoch 0: | | 353/? [01:01<00:00, 5.69it/s, train/loss=2.890]
Epoch 0: | | 354/? [01:02<00:00, 5.68it/s, train/loss=2.890]
Epoch 0: | | 354/? [01:02<00:00, 5.68it/s, train/loss=49.20]
Epoch 0: | | 355/? [01:02<00:00, 5.70it/s, train/loss=49.20]
Epoch 0: | | 355/? [01:02<00:00, 5.70it/s, train/loss=2.900]
Epoch 0: | | 356/? [01:02<00:00, 5.69it/s, train/loss=2.900]
Epoch 0: | | 356/? [01:02<00:00, 5.69it/s, train/loss=7.090]
Epoch 0: | | 357/? [01:02<00:00, 5.70it/s, train/loss=7.090]
Epoch 0: | | 357/? [01:02<00:00, 5.70it/s, train/loss=2.930]
Epoch 0: | | 358/? [01:02<00:00, 5.69it/s, train/loss=2.930]
Epoch 0: | | 358/? [01:02<00:00, 5.69it/s, train/loss=68.30]
Epoch 0: | | 359/? [01:02<00:00, 5.70it/s, train/loss=68.30]
Epoch 0: | | 359/? [01:02<00:00, 5.70it/s, train/loss=3.030]
Epoch 0: | | 360/? [01:03<00:00, 5.69it/s, train/loss=3.030]
Epoch 0: | | 360/? [01:03<00:00, 5.69it/s, train/loss=14.50]
Epoch 0: | | 361/? [01:03<00:00, 5.70it/s, train/loss=14.50]
Epoch 0: | | 361/? [01:03<00:00, 5.70it/s, train/loss=3.160]
Epoch 0: | | 362/? [01:03<00:00, 5.69it/s, train/loss=3.160]
Epoch 0: | | 362/? [01:03<00:00, 5.69it/s, train/loss=9.390]
Epoch 0: | | 363/? [01:03<00:00, 5.71it/s, train/loss=9.390]
Epoch 0: | | 363/? [01:03<00:00, 5.71it/s, train/loss=3.190]
Epoch 0: | | 364/? [01:03<00:00, 5.70it/s, train/loss=3.190]
Epoch 0: | | 364/? [01:03<00:00, 5.70it/s, train/loss=34.60]
Epoch 0: | | 365/? [01:03<00:00, 5.71it/s, train/loss=34.60]
Epoch 0: | | 365/? [01:03<00:00, 5.71it/s, train/loss=3.110]
Epoch 0: | | 366/? [01:04<00:00, 5.70it/s, train/loss=3.110]
Epoch 0: | | 366/? [01:04<00:00, 5.70it/s, train/loss=13.80]
Epoch 0: | | 367/? [01:04<00:00, 5.71it/s, train/loss=13.80]
Epoch 0: | | 367/? [01:04<00:00, 5.71it/s, train/loss=2.990]
Epoch 0: | | 368/? [01:04<00:00, 5.70it/s, train/loss=2.990]
Epoch 0: | | 368/? [01:04<00:00, 5.70it/s, train/loss=24.20]
Epoch 0: | | 369/? [01:04<00:00, 5.71it/s, train/loss=24.20]
Epoch 0: | | 369/? [01:04<00:00, 5.71it/s, train/loss=2.900]
Epoch 0: | | 370/? [01:04<00:00, 5.70it/s, train/loss=2.900]
Epoch 0: | | 370/? [01:04<00:00, 5.70it/s, train/loss=19.60]
Epoch 0: | | 371/? [01:04<00:00, 5.72it/s, train/loss=19.60]
Epoch 0: | | 371/? [01:04<00:00, 5.72it/s, train/loss=2.840]
Epoch 0: | | 372/? [01:05<00:00, 5.71it/s, train/loss=2.840]
Epoch 0: | | 372/? [01:05<00:00, 5.71it/s, train/loss=24.40]
Epoch 0: | | 373/? [01:05<00:00, 5.72it/s, train/loss=24.40]
Epoch 0: | | 373/? [01:05<00:00, 5.72it/s, train/loss=2.810]
Epoch 0: | | 374/? [01:05<00:00, 5.71it/s, train/loss=2.810]
Epoch 0: | | 374/? [01:05<00:00, 5.71it/s, train/loss=10.40]
Epoch 0: | | 375/? [01:05<00:00, 5.72it/s, train/loss=10.40]
Epoch 0: | | 375/? [01:05<00:00, 5.72it/s, train/loss=2.780]
Epoch 0: | | 376/? [01:05<00:00, 5.71it/s, train/loss=2.780]
Epoch 0: | | 376/? [01:05<00:00, 5.71it/s, train/loss=34.00]
Epoch 0: | | 377/? [01:05<00:00, 5.72it/s, train/loss=34.00]
Epoch 0: | | 377/? [01:05<00:00, 5.72it/s, train/loss=2.710]
Epoch 0: | | 378/? [01:06<00:00, 5.71it/s, train/loss=2.710]
Epoch 0: | | 378/? [01:06<00:00, 5.71it/s, train/loss=24.10]
Epoch 0: | | 379/? [01:06<00:00, 5.72it/s, train/loss=24.10]
Epoch 0: | | 379/? [01:06<00:00, 5.72it/s, train/loss=2.650]
Epoch 0: | | 380/? [01:06<00:00, 5.71it/s, train/loss=2.650]
Epoch 0: | | 380/? [01:06<00:00, 5.71it/s, train/loss=17.60]
Epoch 0: | | 381/? [01:06<00:00, 5.73it/s, train/loss=17.60]
Epoch 0: | | 381/? [01:06<00:00, 5.73it/s, train/loss=2.650]
Epoch 0: | | 382/? [01:06<00:00, 5.72it/s, train/loss=2.650]
Epoch 0: | | 382/? [01:06<00:00, 5.72it/s, train/loss=31.10]
Epoch 0: | | 383/? [01:06<00:00, 5.73it/s, train/loss=31.10]
Epoch 0: | | 383/? [01:06<00:00, 5.73it/s, train/loss=2.690]
Epoch 0: | | 384/? [01:07<00:00, 5.72it/s, train/loss=2.690]
Epoch 0: | | 384/? [01:07<00:00, 5.72it/s, train/loss=27.60]
Epoch 0: | | 385/? [01:07<00:00, 5.73it/s, train/loss=27.60]
Epoch 0: | | 385/? [01:07<00:00, 5.73it/s, train/loss=2.720]
Epoch 0: | | 386/? [01:07<00:00, 5.72it/s, train/loss=2.720]
Epoch 0: | | 386/? [01:07<00:00, 5.72it/s, train/loss=19.10]
Epoch 0: | | 387/? [01:07<00:00, 5.73it/s, train/loss=19.10]
Epoch 0: | | 387/? [01:07<00:00, 5.73it/s, train/loss=2.690]
Epoch 0: | | 388/? [01:07<00:00, 5.72it/s, train/loss=2.690]
Epoch 0: | | 388/? [01:07<00:00, 5.72it/s, train/loss=9.580]
Epoch 0: | | 389/? [01:07<00:00, 5.74it/s, train/loss=9.580]
Epoch 0: | | 389/? [01:07<00:00, 5.74it/s, train/loss=2.640]
Epoch 0: | | 390/? [01:08<00:00, 5.73it/s, train/loss=2.640]
Epoch 0: | | 390/? [01:08<00:00, 5.73it/s, train/loss=16.10]
Epoch 0: | | 391/? [01:08<00:00, 5.74it/s, train/loss=16.10]
Epoch 0: | | 391/? [01:08<00:00, 5.74it/s, train/loss=2.580]
Epoch 0: | | 392/? [01:08<00:00, 5.73it/s, train/loss=2.580]
Epoch 0: | | 392/? [01:08<00:00, 5.73it/s, train/loss=37.50]
Epoch 0: | | 393/? [01:08<00:00, 5.74it/s, train/loss=37.50]
Epoch 0: | | 393/? [01:08<00:00, 5.74it/s, train/loss=2.530]
Epoch 0: | | 394/? [01:08<00:00, 5.73it/s, train/loss=2.530]
Epoch 0: | | 394/? [01:08<00:00, 5.73it/s, train/loss=15.50]
Epoch 0: | | 395/? [01:08<00:00, 5.74it/s, train/loss=15.50]
Epoch 0: | | 395/? [01:08<00:00, 5.74it/s, train/loss=2.500]
Epoch 0: | | 396/? [01:09<00:00, 5.73it/s, train/loss=2.500]
Epoch 0: | | 396/? [01:09<00:00, 5.73it/s, train/loss=19.40]
Epoch 0: | | 397/? [01:09<00:00, 5.74it/s, train/loss=19.40]
Epoch 0: | | 397/? [01:09<00:00, 5.74it/s, train/loss=2.490]
Epoch 0: | | 398/? [01:09<00:00, 5.74it/s, train/loss=2.490]
Epoch 0: | | 398/? [01:09<00:00, 5.73it/s, train/loss=19.80]
Epoch 0: | | 399/? [01:09<00:00, 5.75it/s, train/loss=19.80]
Epoch 0: | | 399/? [01:09<00:00, 5.75it/s, train/loss=2.490]
Epoch 0: | | 400/? [01:09<00:00, 5.74it/s, train/loss=2.490]
Epoch 0: | | 400/? [01:09<00:00, 5.74it/s, train/loss=34.10]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:00, 71.57it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:00, 70.04it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:00, 70.02it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:00, 70.00it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:00, 69.62it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:00, 69.44it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:00, 69.47it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:00, 69.54it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:00, 69.70it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:00, 69.82it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:00, 69.97it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:00<00:00, 69.85it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:00<00:00, 68.85it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:00<00:00, 68.93it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:00<00:00, 68.83it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:00<00:00, 68.29it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:00<00:00, 67.23it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:00<00:00, 67.04it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:00<00:00, 66.67it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:00<00:00, 66.50it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:00<00:00, 66.28it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:00<00:00, 63.16it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:00<00:00, 63.25it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:00<00:00, 63.45it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:00<00:00, 63.66it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:00<00:00, 63.87it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:00<00:00, 64.11it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:00<00:00, 64.35it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:00<00:00, 64.58it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:00<00:00, 64.80it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:00<00:00, 64.93it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:00<00:00, 64.18it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:00<00:00, 64.16it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:00<00:00, 63.86it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:00<00:00, 63.84it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:00<00:00, 63.81it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:00<00:00, 63.78it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:00<00:00, 62.42it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:00<00:00, 62.44it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 62.45it/s][A
[A
Epoch 0: | | 400/? [01:10<00:00, 5.65it/s, train/loss=34.10]
Epoch 0: | | 401/? [01:11<00:00, 5.57it/s, train/loss=34.10]
Epoch 0: | | 401/? [01:11<00:00, 5.57it/s, train/loss=2.480]
Epoch 0: | | 402/? [01:12<00:00, 5.57it/s, train/loss=2.480]
Epoch 0: | | 402/? [01:12<00:00, 5.57it/s, train/loss=15.00]
Epoch 0: | | 403/? [01:12<00:00, 5.58it/s, train/loss=15.00]
Epoch 0: | | 403/? [01:12<00:00, 5.58it/s, train/loss=2.480]
Epoch 0: | | 404/? [01:12<00:00, 5.57it/s, train/loss=2.480]
Epoch 0: | | 404/? [01:12<00:00, 5.57it/s, train/loss=23.00]
Epoch 0: | | 405/? [01:12<00:00, 5.58it/s, train/loss=23.00]
Epoch 0: | | 405/? [01:12<00:00, 5.58it/s, train/loss=2.470]
Epoch 0: | | 406/? [01:12<00:00, 5.57it/s, train/loss=2.470]
Epoch 0: | | 406/? [01:12<00:00, 5.57it/s, train/loss=9.820]
Epoch 0: | | 407/? [01:12<00:00, 5.58it/s, train/loss=9.820]
Epoch 0: | | 407/? [01:12<00:00, 5.58it/s, train/loss=2.460]
Epoch 0: | | 408/? [01:13<00:00, 5.57it/s, train/loss=2.460]
Epoch 0: | | 408/? [01:13<00:00, 5.57it/s, train/loss=18.50]
Epoch 0: | | 409/? [01:13<00:00, 5.58it/s, train/loss=18.50]
Epoch 0: | | 409/? [01:13<00:00, 5.58it/s, train/loss=2.450]
Epoch 0: | | 410/? [01:13<00:00, 5.58it/s, train/loss=2.450]
Epoch 0: | | 410/? [01:13<00:00, 5.58it/s, train/loss=21.70]
Epoch 0: | | 411/? [01:13<00:00, 5.59it/s, train/loss=21.70]
Epoch 0: | | 411/? [01:13<00:00, 5.59it/s, train/loss=2.470]
Epoch 0: | | 412/? [01:13<00:00, 5.58it/s, train/loss=2.470]
Epoch 0: | | 412/? [01:13<00:00, 5.58it/s, train/loss=25.70]
Epoch 0: | | 413/? [01:13<00:00, 5.59it/s, train/loss=25.70]
Epoch 0: | | 413/? [01:13<00:00, 5.59it/s, train/loss=2.480]
Epoch 0: | | 414/? [01:14<00:00, 5.58it/s, train/loss=2.480]
Epoch 0: | | 414/? [01:14<00:00, 5.58it/s, train/loss=49.00]
Epoch 0: | | 415/? [01:14<00:00, 5.59it/s, train/loss=49.00]
Epoch 0: | | 415/? [01:14<00:00, 5.59it/s, train/loss=2.460]
Epoch 0: | | 416/? [01:14<00:00, 5.58it/s, train/loss=2.460]
Epoch 0: | | 416/? [01:14<00:00, 5.58it/s, train/loss=14.30]
Epoch 0: | | 417/? [01:14<00:00, 5.59it/s, train/loss=14.30]
Epoch 0: | | 417/? [01:14<00:00, 5.59it/s, train/loss=2.490]
Epoch 0: | | 418/? [01:14<00:00, 5.58it/s, train/loss=2.490]
Epoch 0: | | 418/? [01:14<00:00, 5.58it/s, train/loss=12.00]
Epoch 0: | | 419/? [01:14<00:00, 5.60it/s, train/loss=12.00]
Epoch 0: | | 419/? [01:14<00:00, 5.60it/s, train/loss=2.520]
Epoch 0: | | 420/? [01:15<00:00, 5.59it/s, train/loss=2.520]
Epoch 0: | | 420/? [01:15<00:00, 5.59it/s, train/loss=10.10]
Epoch 0: | | 421/? [01:15<00:00, 5.60it/s, train/loss=10.10]
Epoch 0: | | 421/? [01:15<00:00, 5.60it/s, train/loss=2.520]
Epoch 0: | | 422/? [01:15<00:00, 5.59it/s, train/loss=2.520]
Epoch 0: | | 422/? [01:15<00:00, 5.59it/s, train/loss=27.00]
Epoch 0: | | 423/? [01:15<00:00, 5.60it/s, train/loss=27.00]
Epoch 0: | | 423/? [01:15<00:00, 5.60it/s, train/loss=2.470]
Epoch 0: | | 424/? [01:15<00:00, 5.59it/s, train/loss=2.470]
Epoch 0: | | 424/? [01:15<00:00, 5.59it/s, train/loss=22.70]
Epoch 0: | | 425/? [01:15<00:00, 5.60it/s, train/loss=22.70]
Epoch 0: | | 425/? [01:15<00:00, 5.60it/s, train/loss=2.420]
Epoch 0: | | 426/? [01:16<00:00, 5.60it/s, train/loss=2.420]
Epoch 0: | | 426/? [01:16<00:00, 5.60it/s, train/loss=9.020]
Epoch 0: | | 427/? [01:16<00:00, 5.61it/s, train/loss=9.020]
Epoch 0: | | 427/? [01:16<00:00, 5.61it/s, train/loss=2.360]
Epoch 0: | | 428/? [01:16<00:00, 5.60it/s, train/loss=2.360]
Epoch 0: | | 428/? [01:16<00:00, 5.60it/s, train/loss=41.80]
Epoch 0: | | 429/? [01:16<00:00, 5.61it/s, train/loss=41.80]
Epoch 0: | | 429/? [01:16<00:00, 5.61it/s, train/loss=2.330]
Epoch 0: | | 430/? [01:16<00:00, 5.60it/s, train/loss=2.330]
Epoch 0: | | 430/? [01:16<00:00, 5.60it/s, train/loss=36.30]
Epoch 0: | | 431/? [01:16<00:00, 5.61it/s, train/loss=36.30]
Epoch 0: | | 431/? [01:16<00:00, 5.61it/s, train/loss=2.320]
Epoch 0: | | 432/? [01:17<00:00, 5.60it/s, train/loss=2.320]
Epoch 0: | | 432/? [01:17<00:00, 5.60it/s, train/loss=16.50]
Epoch 0: | | 433/? [01:17<00:00, 5.61it/s, train/loss=16.50]
Epoch 0: | | 433/? [01:17<00:00, 5.61it/s, train/loss=2.340]
Epoch 0: | | 434/? [01:17<00:00, 5.61it/s, train/loss=2.340]
Epoch 0: | | 434/? [01:17<00:00, 5.61it/s, train/loss=23.30]
Epoch 0: | | 435/? [01:17<00:00, 5.62it/s, train/loss=23.30]
Epoch 0: | | 435/? [01:17<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 436/? [01:17<00:00, 5.61it/s, train/loss=2.350]
Epoch 0: | | 436/? [01:17<00:00, 5.61it/s, train/loss=32.70]
Epoch 0: | | 437/? [01:17<00:00, 5.62it/s, train/loss=32.70]
Epoch 0: | | 437/? [01:17<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 438/? [01:18<00:00, 5.61it/s, train/loss=2.350]
Epoch 0: | | 438/? [01:18<00:00, 5.61it/s, train/loss=33.70]
Epoch 0: | | 439/? [01:18<00:00, 5.62it/s, train/loss=33.70]
Epoch 0: | | 439/? [01:18<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 440/? [01:18<00:00, 5.61it/s, train/loss=2.350]
Epoch 0: | | 440/? [01:18<00:00, 5.61it/s, train/loss=12.70]
Epoch 0: | | 441/? [01:18<00:00, 5.62it/s, train/loss=12.70]
Epoch 0: | | 441/? [01:18<00:00, 5.62it/s, train/loss=2.360]
Epoch 0: | | 442/? [01:18<00:00, 5.62it/s, train/loss=2.360]
Epoch 0: | | 442/? [01:18<00:00, 5.62it/s, train/loss=16.30]
Epoch 0: | | 443/? [01:18<00:00, 5.63it/s, train/loss=16.30]
Epoch 0: | | 443/? [01:18<00:00, 5.63it/s, train/loss=2.330]
Epoch 0: | | 444/? [01:19<00:00, 5.62it/s, train/loss=2.330]
Epoch 0: | | 444/? [01:19<00:00, 5.62it/s, train/loss=21.40]
Epoch 0: | | 445/? [01:19<00:00, 5.63it/s, train/loss=21.40]
Epoch 0: | | 445/? [01:19<00:00, 5.63it/s, train/loss=2.320]
Epoch 0: | | 446/? [01:19<00:00, 5.62it/s, train/loss=2.320]
Epoch 0: | | 446/? [01:19<00:00, 5.62it/s, train/loss=19.00]
Epoch 0: | | 447/? [01:19<00:00, 5.63it/s, train/loss=19.00]
Epoch 0: | | 447/? [01:19<00:00, 5.63it/s, train/loss=2.330]
Epoch 0: | | 448/? [01:19<00:00, 5.62it/s, train/loss=2.330]
Epoch 0: | | 448/? [01:19<00:00, 5.62it/s, train/loss=16.60]
Epoch 0: | | 449/? [01:19<00:00, 5.63it/s, train/loss=16.60]
Epoch 0: | | 449/? [01:19<00:00, 5.63it/s, train/loss=2.320]
Epoch 0: | | 450/? [01:20<00:00, 5.62it/s, train/loss=2.320]
Epoch 0: | | 450/? [01:20<00:00, 5.62it/s, train/loss=18.70]
Epoch 0: | | 451/? [01:20<00:00, 5.63it/s, train/loss=18.70]
Epoch 0: | | 451/? [01:20<00:00, 5.63it/s, train/loss=2.290]
Epoch 0: | | 452/? [01:20<00:00, 5.62it/s, train/loss=2.290]
Epoch 0: | | 452/? [01:20<00:00, 5.62it/s, train/loss=10.30]
Epoch 0: | | 453/? [01:20<00:00, 5.63it/s, train/loss=10.30]
Epoch 0: | | 453/? [01:20<00:00, 5.63it/s, train/loss=2.250]
Epoch 0: | | 454/? [01:20<00:00, 5.62it/s, train/loss=2.250]
Epoch 0: | | 454/? [01:20<00:00, 5.62it/s, train/loss=25.40]
Epoch 0: | | 455/? [01:20<00:00, 5.63it/s, train/loss=25.40]
Epoch 0: | | 455/? [01:20<00:00, 5.63it/s, train/loss=2.210]
Epoch 0: | | 456/? [01:21<00:00, 5.62it/s, train/loss=2.210]
Epoch 0: | | 456/? [01:21<00:00, 5.62it/s, train/loss=8.850]
Epoch 0: | | 457/? [01:21<00:00, 5.63it/s, train/loss=8.850]
Epoch 0: | | 457/? [01:21<00:00, 5.63it/s, train/loss=2.160]
Epoch 0: | | 458/? [01:21<00:00, 5.62it/s, train/loss=2.160]
Epoch 0: | | 458/? [01:21<00:00, 5.62it/s, train/loss=13.90]
Epoch 0: | | 459/? [01:21<00:00, 5.63it/s, train/loss=13.90]
Epoch 0: | | 459/? [01:21<00:00, 5.63it/s, train/loss=2.120]
Epoch 0: | | 460/? [01:21<00:00, 5.62it/s, train/loss=2.120]
Epoch 0: | | 460/? [01:21<00:00, 5.62it/s, train/loss=32.80]
Epoch 0: | | 461/? [01:21<00:00, 5.63it/s, train/loss=32.80]
Epoch 0: | | 461/? [01:21<00:00, 5.63it/s, train/loss=2.120]
Epoch 0: | | 462/? [01:22<00:00, 5.62it/s, train/loss=2.120]
Epoch 0: | | 462/? [01:22<00:00, 5.62it/s, train/loss=12.30]
Epoch 0: | | 463/? [01:22<00:00, 5.63it/s, train/loss=12.30]
Epoch 0: | | 463/? [01:22<00:00, 5.63it/s, train/loss=2.140]
Epoch 0: | | 464/? [01:22<00:00, 5.62it/s, train/loss=2.140]
Epoch 0: | | 464/? [01:22<00:00, 5.62it/s, train/loss=24.00]
Epoch 0: | | 465/? [01:22<00:00, 5.63it/s, train/loss=24.00]
Epoch 0: | | 465/? [01:22<00:00, 5.63it/s, train/loss=2.120]
Epoch 0: | | 466/? [01:22<00:00, 5.62it/s, train/loss=2.120]
Epoch 0: | | 466/? [01:22<00:00, 5.62it/s, train/loss=28.10]
Epoch 0: | | 467/? [01:22<00:00, 5.63it/s, train/loss=28.10]
Epoch 0: | | 467/? [01:22<00:00, 5.63it/s, train/loss=2.070]
Epoch 0: | | 468/? [01:23<00:00, 5.62it/s, train/loss=2.070]
Epoch 0: | | 468/? [01:23<00:00, 5.62it/s, train/loss=12.20]
Epoch 0: | | 469/? [01:23<00:00, 5.63it/s, train/loss=12.20]
Epoch 0: | | 469/? [01:23<00:00, 5.63it/s, train/loss=2.060]
Epoch 0: | | 470/? [01:23<00:00, 5.62it/s, train/loss=2.060]
Epoch 0: | | 470/? [01:23<00:00, 5.62it/s, train/loss=20.10]
Epoch 0: | | 471/? [01:23<00:00, 5.63it/s, train/loss=20.10]
Epoch 0: | | 471/? [01:23<00:00, 5.63it/s, train/loss=2.090]
Epoch 0: | | 472/? [01:24<00:00, 5.62it/s, train/loss=2.090]
Epoch 0: | | 472/? [01:24<00:00, 5.62it/s, train/loss=16.70]
Epoch 0: | | 473/? [01:24<00:00, 5.63it/s, train/loss=16.70]
Epoch 0: | | 473/? [01:24<00:00, 5.63it/s, train/loss=2.170]
Epoch 0: | | 474/? [01:24<00:00, 5.62it/s, train/loss=2.170]
Epoch 0: | | 474/? [01:24<00:00, 5.62it/s, train/loss=36.50]
Epoch 0: | | 475/? [01:24<00:00, 5.63it/s, train/loss=36.50]
Epoch 0: | | 475/? [01:24<00:00, 5.63it/s, train/loss=2.250]
Epoch 0: | | 476/? [01:24<00:00, 5.62it/s, train/loss=2.250]
Epoch 0: | | 476/? [01:24<00:00, 5.62it/s, train/loss=45.30]
Epoch 0: | | 477/? [01:24<00:00, 5.63it/s, train/loss=45.30]
Epoch 0: | | 477/? [01:24<00:00, 5.63it/s, train/loss=2.370]
Epoch 0: | | 478/? [01:25<00:00, 5.62it/s, train/loss=2.370]
Epoch 0: | | 478/? [01:25<00:00, 5.62it/s, train/loss=29.20]
Epoch 0: | | 479/? [01:25<00:00, 5.63it/s, train/loss=29.20]
Epoch 0: | | 479/? [01:25<00:00, 5.63it/s, train/loss=2.420]
Epoch 0: | | 480/? [01:25<00:00, 5.62it/s, train/loss=2.420]
Epoch 0: | | 480/? [01:25<00:00, 5.62it/s, train/loss=20.70]
Epoch 0: | | 481/? [01:25<00:00, 5.63it/s, train/loss=20.70]
Epoch 0: | | 481/? [01:25<00:00, 5.63it/s, train/loss=2.400]
Epoch 0: | | 482/? [01:25<00:00, 5.62it/s, train/loss=2.400]
Epoch 0: | | 482/? [01:25<00:00, 5.62it/s, train/loss=24.80]
Epoch 0: | | 483/? [01:25<00:00, 5.62it/s, train/loss=24.80]
Epoch 0: | | 483/? [01:25<00:00, 5.62it/s, train/loss=2.330]
Epoch 0: | | 484/? [01:26<00:00, 5.62it/s, train/loss=2.330]
Epoch 0: | | 484/? [01:26<00:00, 5.62it/s, train/loss=17.00]
Epoch 0: | | 485/? [01:26<00:00, 5.62it/s, train/loss=17.00]
Epoch 0: | | 485/? [01:26<00:00, 5.62it/s, train/loss=2.290]
Epoch 0: | | 486/? [01:26<00:00, 5.62it/s, train/loss=2.290]
Epoch 0: | | 486/? [01:26<00:00, 5.62it/s, train/loss=29.70]
Epoch 0: | | 487/? [01:26<00:00, 5.62it/s, train/loss=29.70]
Epoch 0: | | 487/? [01:26<00:00, 5.62it/s, train/loss=2.260]
Epoch 0: | | 488/? [01:26<00:00, 5.62it/s, train/loss=2.260]
Epoch 0: | | 488/? [01:26<00:00, 5.62it/s, train/loss=24.80]
Epoch 0: | | 489/? [01:26<00:00, 5.62it/s, train/loss=24.80]
Epoch 0: | | 489/? [01:26<00:00, 5.62it/s, train/loss=2.250]
Epoch 0: | | 490/? [01:27<00:00, 5.62it/s, train/loss=2.250]
Epoch 0: | | 490/? [01:27<00:00, 5.62it/s, train/loss=34.60]
Epoch 0: | | 491/? [01:27<00:00, 5.62it/s, train/loss=34.60]
Epoch 0: | | 491/? [01:27<00:00, 5.62it/s, train/loss=2.250]
Epoch 0: | | 492/? [01:27<00:00, 5.62it/s, train/loss=2.250]
Epoch 0: | | 492/? [01:27<00:00, 5.62it/s, train/loss=27.40]
Epoch 0: | | 493/? [01:27<00:00, 5.62it/s, train/loss=27.40]
Epoch 0: | | 493/? [01:27<00:00, 5.62it/s, train/loss=2.270]
Epoch 0: | | 494/? [01:27<00:00, 5.62it/s, train/loss=2.270]
Epoch 0: | | 494/? [01:27<00:00, 5.62it/s, train/loss=17.20]
Epoch 0: | | 495/? [01:28<00:00, 5.62it/s, train/loss=17.20]
Epoch 0: | | 495/? [01:28<00:00, 5.62it/s, train/loss=2.320]
Epoch 0: | | 496/? [01:28<00:00, 5.62it/s, train/loss=2.320]
Epoch 0: | | 496/? [01:28<00:00, 5.62it/s, train/loss=31.80]
Epoch 0: | | 497/? [01:28<00:00, 5.62it/s, train/loss=31.80]
Epoch 0: | | 497/? [01:28<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 498/? [01:28<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 498/? [01:28<00:00, 5.62it/s, train/loss=33.30]
Epoch 0: | | 499/? [01:28<00:00, 5.62it/s, train/loss=33.30]
Epoch 0: | | 499/? [01:28<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 500/? [01:29<00:00, 5.62it/s, train/loss=2.350]
Epoch 0: | | 500/? [01:29<00:00, 5.62it/s, train/loss=15.50]
Epoch 0: | | 501/? [01:29<00:00, 5.62it/s, train/loss=15.50]
Epoch 0: | | 501/? [01:29<00:00, 5.62it/s, train/loss=2.380]
Epoch 0: | | 502/? [01:29<00:00, 5.62it/s, train/loss=2.380]
Epoch 0: | | 502/? [01:29<00:00, 5.62it/s, train/loss=11.30]
Epoch 0: | | 503/? [01:29<00:00, 5.62it/s, train/loss=11.30]
Epoch 0: | | 503/? [01:29<00:00, 5.62it/s, train/loss=2.360]
Epoch 0: | | 504/? [01:29<00:00, 5.62it/s, train/loss=2.360]
Epoch 0: | | 504/? [01:29<00:00, 5.62it/s, train/loss=9.480]
Epoch 0: | | 505/? [01:29<00:00, 5.62it/s, train/loss=9.480]
Epoch 0: | | 505/? [01:29<00:00, 5.62it/s, train/loss=2.330]
Epoch 0: | | 506/? [01:30<00:00, 5.62it/s, train/loss=2.330]
Epoch 0: | | 506/? [01:30<00:00, 5.62it/s, train/loss=15.00]
Epoch 0: | | 507/? [01:30<00:00, 5.62it/s, train/loss=15.00]
Epoch 0: | | 507/? [01:30<00:00, 5.62it/s, train/loss=2.290]
Epoch 0: | | 508/? [01:30<00:00, 5.62it/s, train/loss=2.290]
Epoch 0: | | 508/? [01:30<00:00, 5.62it/s, train/loss=9.350]
Epoch 0: | | 509/? [01:30<00:00, 5.62it/s, train/loss=9.350]
Epoch 0: | | 509/? [01:30<00:00, 5.62it/s, train/loss=2.240]
Epoch 0: | | 510/? [01:30<00:00, 5.62it/s, train/loss=2.240]
Epoch 0: | | 510/? [01:30<00:00, 5.62it/s, train/loss=21.50]
Epoch 0: | | 511/? [01:30<00:00, 5.63it/s, train/loss=21.50]
Epoch 0: | | 511/? [01:30<00:00, 5.63it/s, train/loss=2.190]
Epoch 0: | | 512/? [01:31<00:00, 5.62it/s, train/loss=2.190]
Epoch 0: | | 512/? [01:31<00:00, 5.62it/s, train/loss=24.70]
Epoch 0: | | 513/? [01:31<00:00, 5.63it/s, train/loss=24.70]
Epoch 0: | | 513/? [01:31<00:00, 5.63it/s, train/loss=2.150]
Epoch 0: | | 514/? [01:31<00:00, 5.62it/s, train/loss=2.150]
Epoch 0: | | 514/? [01:31<00:00, 5.62it/s, train/loss=27.40]
Epoch 0: | | 515/? [01:31<00:00, 5.63it/s, train/loss=27.40]
Epoch 0: | | 515/? [01:31<00:00, 5.63it/s, train/loss=2.130]
Epoch 0: | | 516/? [01:31<00:00, 5.62it/s, train/loss=2.130]
Epoch 0: | | 516/? [01:31<00:00, 5.62it/s, train/loss=33.50]
Epoch 0: | | 517/? [01:31<00:00, 5.63it/s, train/loss=33.50]
Epoch 0: | | 517/? [01:31<00:00, 5.63it/s, train/loss=2.140]
Epoch 0: | | 518/? [01:32<00:00, 5.63it/s, train/loss=2.140]
Epoch 0: | | 518/? [01:32<00:00, 5.62it/s, train/loss=14.40]
Epoch 0: | | 519/? [01:32<00:00, 5.63it/s, train/loss=14.40]
Epoch 0: | | 519/? [01:32<00:00, 5.63it/s, train/loss=2.180]
Epoch 0: | | 520/? [01:32<00:00, 5.63it/s, train/loss=2.180]
Epoch 0: | | 520/? [01:32<00:00, 5.63it/s, train/loss=60.00]
Epoch 0: | | 521/? [01:32<00:00, 5.64it/s, train/loss=60.00]
Epoch 0: | | 521/? [01:32<00:00, 5.64it/s, train/loss=2.210]
Epoch 0: | | 522/? [01:32<00:00, 5.63it/s, train/loss=2.210]
Epoch 0: | | 522/? [01:32<00:00, 5.63it/s, train/loss=20.10]
Epoch 0: | | 523/? [01:32<00:00, 5.64it/s, train/loss=20.10]
Epoch 0: | | 523/? [01:32<00:00, 5.64it/s, train/loss=2.260]
Epoch 0: | | 524/? [01:33<00:00, 5.63it/s, train/loss=2.260]
Epoch 0: | | 524/? [01:33<00:00, 5.63it/s, train/loss=32.00]
Epoch 0: | | 525/? [01:33<00:00, 5.64it/s, train/loss=32.00]
Epoch 0: | | 525/? [01:33<00:00, 5.64it/s, train/loss=2.300]
Epoch 0: | | 526/? [01:33<00:00, 5.63it/s, train/loss=2.300]
Epoch 0: | | 526/? [01:33<00:00, 5.63it/s, train/loss=32.60]
Epoch 0: | | 527/? [01:33<00:00, 5.64it/s, train/loss=32.60]
Epoch 0: | | 527/? [01:33<00:00, 5.64it/s, train/loss=2.300]
Epoch 0: | | 528/? [01:33<00:00, 5.63it/s, train/loss=2.300]
Epoch 0: | | 528/? [01:33<00:00, 5.63it/s, train/loss=29.10]
Epoch 0: | | 529/? [01:33<00:00, 5.64it/s, train/loss=29.10]
Epoch 0: | | 529/? [01:33<00:00, 5.64it/s, train/loss=2.290]
Epoch 0: | | 530/? [01:34<00:00, 5.63it/s, train/loss=2.290]
Epoch 0: | | 530/? [01:34<00:00, 5.63it/s, train/loss=37.40]
Epoch 0: | | 531/? [01:34<00:00, 5.64it/s, train/loss=37.40]
Epoch 0: | | 531/? [01:34<00:00, 5.64it/s, train/loss=2.250]
Epoch 0: | | 532/? [01:34<00:00, 5.64it/s, train/loss=2.250]
Epoch 0: | | 532/? [01:34<00:00, 5.64it/s, train/loss=50.00]
Epoch 0: | | 533/? [01:34<00:00, 5.64it/s, train/loss=50.00]
Epoch 0: | | 533/? [01:34<00:00, 5.64it/s, train/loss=2.210]
Epoch 0: | | 534/? [01:34<00:00, 5.64it/s, train/loss=2.210]
Epoch 0: | | 534/? [01:34<00:00, 5.64it/s, train/loss=18.50]
Epoch 0: | | 535/? [01:34<00:00, 5.65it/s, train/loss=18.50]
Epoch 0: | | 535/? [01:34<00:00, 5.65it/s, train/loss=2.210]
Epoch 0: | | 536/? [01:35<00:00, 5.64it/s, train/loss=2.210]
Epoch 0: | | 536/? [01:35<00:00, 5.64it/s, train/loss=15.60]
Epoch 0: | | 537/? [01:35<00:00, 5.65it/s, train/loss=15.60]
Epoch 0: | | 537/? [01:35<00:00, 5.65it/s, train/loss=2.220]
Epoch 0: | | 538/? [01:35<00:00, 5.64it/s, train/loss=2.220]
Epoch 0: | | 538/? [01:35<00:00, 5.64it/s, train/loss=10.90]
Epoch 0: | | 539/? [01:35<00:00, 5.65it/s, train/loss=10.90]
Epoch 0: | | 539/? [01:35<00:00, 5.65it/s, train/loss=2.210]
Epoch 0: | | 540/? [01:35<00:00, 5.64it/s, train/loss=2.210]
Epoch 0: | | 540/? [01:35<00:00, 5.64it/s, train/loss=46.40]
Epoch 0: | | 541/? [01:35<00:00, 5.65it/s, train/loss=46.40]
Epoch 0: | | 541/? [01:35<00:00, 5.65it/s, train/loss=2.180]
Epoch 0: | | 542/? [01:36<00:00, 5.64it/s, train/loss=2.180]
Epoch 0: | | 542/? [01:36<00:00, 5.64it/s, train/loss=11.40]
Epoch 0: | | 543/? [01:36<00:00, 5.65it/s, train/loss=11.40]
Epoch 0: | | 543/? [01:36<00:00, 5.65it/s, train/loss=2.160]
Epoch 0: | | 544/? [01:36<00:00, 5.65it/s, train/loss=2.160]
Epoch 0: | | 544/? [01:36<00:00, 5.65it/s, train/loss=48.70]
Epoch 0: | | 545/? [01:36<00:00, 5.65it/s, train/loss=48.70]
Epoch 0: | | 545/? [01:36<00:00, 5.65it/s, train/loss=2.150]
Epoch 0: | | 546/? [01:36<00:00, 5.65it/s, train/loss=2.150]
Epoch 0: | | 546/? [01:36<00:00, 5.65it/s, train/loss=22.10]
Epoch 0: | | 547/? [01:36<00:00, 5.66it/s, train/loss=22.10]
Epoch 0: | | 547/? [01:36<00:00, 5.65it/s, train/loss=2.240]
Epoch 0: | | 548/? [01:37<00:00, 5.65it/s, train/loss=2.240]
Epoch 0: | | 548/? [01:37<00:00, 5.65it/s, train/loss=29.10]
Epoch 0: | | 549/? [01:37<00:00, 5.66it/s, train/loss=29.10]
Epoch 0: | | 549/? [01:37<00:00, 5.66it/s, train/loss=2.350]
Epoch 0: | | 550/? [01:37<00:00, 5.65it/s, train/loss=2.350]
Epoch 0: | | 550/? [01:37<00:00, 5.65it/s, train/loss=12.00]
Epoch 0: | | 551/? [01:37<00:00, 5.66it/s, train/loss=12.00]
Epoch 0: | | 551/? [01:37<00:00, 5.66it/s, train/loss=2.400]
Epoch 0: | | 552/? [01:37<00:00, 5.65it/s, train/loss=2.400]
Epoch 0: | | 552/? [01:37<00:00, 5.65it/s, train/loss=17.40]
Epoch 0: | | 553/? [01:37<00:00, 5.66it/s, train/loss=17.40]
Epoch 0: | | 553/? [01:37<00:00, 5.66it/s, train/loss=2.390]
Epoch 0: | | 554/? [01:37<00:00, 5.65it/s, train/loss=2.390]
Epoch 0: | | 554/? [01:37<00:00, 5.65it/s, train/loss=17.00]
Epoch 0: | | 555/? [01:38<00:00, 5.66it/s, train/loss=17.00]
Epoch 0: | | 555/? [01:38<00:00, 5.66it/s, train/loss=2.330]
Epoch 0: | | 556/? [01:38<00:00, 5.66it/s, train/loss=2.330]
Epoch 0: | | 556/? [01:38<00:00, 5.66it/s, train/loss=19.20]
Epoch 0: | | 557/? [01:38<00:00, 5.66it/s, train/loss=19.20]
Epoch 0: | | 557/? [01:38<00:00, 5.66it/s, train/loss=2.260]
Epoch 0: | | 558/? [01:38<00:00, 5.66it/s, train/loss=2.260]
Epoch 0: | | 558/? [01:38<00:00, 5.66it/s, train/loss=24.90]
Epoch 0: | | 559/? [01:38<00:00, 5.66it/s, train/loss=24.90]
Epoch 0: | | 559/? [01:38<00:00, 5.66it/s, train/loss=2.240]
Epoch 0: | | 560/? [01:38<00:00, 5.66it/s, train/loss=2.240]
Epoch 0: | | 560/? [01:38<00:00, 5.66it/s, train/loss=37.70]
Epoch 0: | | 561/? [01:39<00:00, 5.67it/s, train/loss=37.70]
Epoch 0: | | 561/? [01:39<00:00, 5.67it/s, train/loss=2.240]
Epoch 0: | | 562/? [01:39<00:00, 5.66it/s, train/loss=2.240]
Epoch 0: | | 562/? [01:39<00:00, 5.66it/s, train/loss=29.60]
Epoch 0: | | 563/? [01:39<00:00, 5.67it/s, train/loss=29.60]
Epoch 0: | | 563/? [01:39<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 564/? [01:39<00:00, 5.66it/s, train/loss=2.200]
Epoch 0: | | 564/? [01:39<00:00, 5.66it/s, train/loss=13.10]
Epoch 0: | | 565/? [01:39<00:00, 5.67it/s, train/loss=13.10]
Epoch 0: | | 565/? [01:39<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 566/? [01:39<00:00, 5.66it/s, train/loss=2.180]
Epoch 0: | | 566/? [01:39<00:00, 5.66it/s, train/loss=14.70]
Epoch 0: | | 567/? [01:39<00:00, 5.67it/s, train/loss=14.70]
Epoch 0: | | 567/? [01:39<00:00, 5.67it/s, train/loss=2.170]
Epoch 0: | | 568/? [01:40<00:00, 5.66it/s, train/loss=2.170]
Epoch 0: | | 568/? [01:40<00:00, 5.66it/s, train/loss=25.70]
Epoch 0: | | 569/? [01:40<00:00, 5.67it/s, train/loss=25.70]
Epoch 0: | | 569/? [01:40<00:00, 5.67it/s, train/loss=2.150]
Epoch 0: | | 570/? [01:40<00:00, 5.67it/s, train/loss=2.150]
Epoch 0: | | 570/? [01:40<00:00, 5.67it/s, train/loss=20.20]
Epoch 0: | | 571/? [01:40<00:00, 5.67it/s, train/loss=20.20]
Epoch 0: | | 571/? [01:40<00:00, 5.67it/s, train/loss=2.120]
Epoch 0: | | 572/? [01:40<00:00, 5.66it/s, train/loss=2.120]
Epoch 0: | | 572/? [01:40<00:00, 5.66it/s, train/loss=24.90]
Epoch 0: | | 573/? [01:41<00:00, 5.67it/s, train/loss=24.90]
Epoch 0: | | 573/? [01:41<00:00, 5.67it/s, train/loss=2.140]
Epoch 0: | | 574/? [01:41<00:00, 5.67it/s, train/loss=2.140]
Epoch 0: | | 574/? [01:41<00:00, 5.67it/s, train/loss=19.00]
Epoch 0: | | 575/? [01:41<00:00, 5.67it/s, train/loss=19.00]
Epoch 0: | | 575/? [01:41<00:00, 5.67it/s, train/loss=2.190]
Epoch 0: | | 576/? [01:41<00:00, 5.67it/s, train/loss=2.190]
Epoch 0: | | 576/? [01:41<00:00, 5.67it/s, train/loss=11.50]
Epoch 0: | | 577/? [01:41<00:00, 5.67it/s, train/loss=11.50]
Epoch 0: | | 577/? [01:41<00:00, 5.67it/s, train/loss=2.240]
Epoch 0: | | 578/? [01:41<00:00, 5.67it/s, train/loss=2.240]
Epoch 0: | | 578/? [01:41<00:00, 5.67it/s, train/loss=19.60]
Epoch 0: | | 579/? [01:42<00:00, 5.68it/s, train/loss=19.60]
Epoch 0: | | 579/? [01:42<00:00, 5.68it/s, train/loss=2.230]
Epoch 0: | | 580/? [01:42<00:00, 5.67it/s, train/loss=2.230]
Epoch 0: | | 580/? [01:42<00:00, 5.67it/s, train/loss=39.90]
Epoch 0: | | 581/? [01:42<00:00, 5.68it/s, train/loss=39.90]
Epoch 0: | | 581/? [01:42<00:00, 5.68it/s, train/loss=2.140]
Epoch 0: | | 582/? [01:42<00:00, 5.67it/s, train/loss=2.140]
Epoch 0: | | 582/? [01:42<00:00, 5.67it/s, train/loss=14.50]
Epoch 0: | | 583/? [01:42<00:00, 5.68it/s, train/loss=14.50]
Epoch 0: | | 583/? [01:42<00:00, 5.68it/s, train/loss=2.050]
Epoch 0: | | 584/? [01:42<00:00, 5.67it/s, train/loss=2.050]
Epoch 0: | | 584/? [01:42<00:00, 5.67it/s, train/loss=28.80]
Epoch 0: | | 585/? [01:43<00:00, 5.68it/s, train/loss=28.80]
Epoch 0: | | 585/? [01:43<00:00, 5.68it/s, train/loss=2.020]
Epoch 0: | | 586/? [01:43<00:00, 5.67it/s, train/loss=2.020]
Epoch 0: | | 586/? [01:43<00:00, 5.67it/s, train/loss=32.90]
Epoch 0: | | 587/? [01:43<00:00, 5.68it/s, train/loss=32.90]
Epoch 0: | | 587/? [01:43<00:00, 5.68it/s, train/loss=2.000]
Epoch 0: | | 588/? [01:43<00:00, 5.67it/s, train/loss=2.000]
Epoch 0: | | 588/? [01:43<00:00, 5.67it/s, train/loss=26.10]
Epoch 0: | | 589/? [01:43<00:00, 5.68it/s, train/loss=26.10]
Epoch 0: | | 589/? [01:43<00:00, 5.68it/s, train/loss=2.020]
Epoch 0: | | 590/? [01:43<00:00, 5.68it/s, train/loss=2.020]
Epoch 0: | | 590/? [01:43<00:00, 5.68it/s, train/loss=37.00]
Epoch 0: | | 591/? [01:43<00:00, 5.68it/s, train/loss=37.00]
Epoch 0: | | 591/? [01:43<00:00, 5.68it/s, train/loss=2.080]
Epoch 0: | | 592/? [01:44<00:00, 5.68it/s, train/loss=2.080]
Epoch 0: | | 592/? [01:44<00:00, 5.68it/s, train/loss=17.80]
Epoch 0: | | 593/? [01:44<00:00, 5.68it/s, train/loss=17.80]
Epoch 0: | | 593/? [01:44<00:00, 5.68it/s, train/loss=2.140]
Epoch 0: | | 594/? [01:44<00:00, 5.68it/s, train/loss=2.140]
Epoch 0: | | 594/? [01:44<00:00, 5.68it/s, train/loss=27.40]
Epoch 0: | | 595/? [01:44<00:00, 5.69it/s, train/loss=27.40]
Epoch 0: | | 595/? [01:44<00:00, 5.69it/s, train/loss=2.160]
Epoch 0: | | 596/? [01:44<00:00, 5.68it/s, train/loss=2.160]
Epoch 0: | | 596/? [01:44<00:00, 5.68it/s, train/loss=26.80]
Epoch 0: | | 597/? [01:44<00:00, 5.69it/s, train/loss=26.80]
Epoch 0: | | 597/? [01:44<00:00, 5.69it/s, train/loss=2.160]
Epoch 0: | | 598/? [01:45<00:00, 5.68it/s, train/loss=2.160]
Epoch 0: | | 598/? [01:45<00:00, 5.68it/s, train/loss=32.30]
Epoch 0: | | 599/? [01:45<00:00, 5.69it/s, train/loss=32.30]
Epoch 0: | | 599/? [01:45<00:00, 5.69it/s, train/loss=2.180]
Epoch 0: | | 600/? [01:45<00:00, 5.68it/s, train/loss=2.180]
Epoch 0: | | 600/? [01:45<00:00, 5.68it/s, train/loss=27.90]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:00, 62.82it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:00, 63.32it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:00, 64.21it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:00, 65.06it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:00, 65.52it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:00, 65.97it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:00, 66.31it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:00, 66.59it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:00, 66.79it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:00, 66.84it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:00, 66.80it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:00<00:00, 66.97it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:00<00:00, 66.92it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:00<00:00, 66.42it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:00<00:00, 66.48it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:00<00:00, 66.46it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:00<00:00, 66.55it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:00<00:00, 66.63it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:00<00:00, 66.70it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:00<00:00, 66.75it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:00<00:00, 66.67it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:00<00:00, 66.75it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:00<00:00, 66.76it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:00<00:00, 66.78it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:00<00:00, 66.79it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:00<00:00, 66.81it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:00<00:00, 66.88it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:00<00:00, 66.93it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:00<00:00, 67.00it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:00<00:00, 66.79it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:00<00:00, 65.50it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:00<00:00, 65.37it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:00<00:00, 64.63it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:00<00:00, 64.36it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:00<00:00, 64.40it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:00<00:00, 64.43it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:00<00:00, 64.44it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:00<00:00, 64.43it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:00<00:00, 64.41it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 64.39it/s][A
[A
Epoch 0: | | 600/? [01:46<00:00, 5.62it/s, train/loss=27.90]
Epoch 0: | | 601/? [01:47<00:00, 5.60it/s, train/loss=27.90]
Epoch 0: | | 601/? [01:47<00:00, 5.60it/s, train/loss=2.240]
Epoch 0: | | 602/? [01:47<00:00, 5.60it/s, train/loss=2.240]
Epoch 0: | | 602/? [01:47<00:00, 5.60it/s, train/loss=27.10]
Epoch 0: | | 603/? [01:47<00:00, 5.61it/s, train/loss=27.10]
Epoch 0: | | 603/? [01:47<00:00, 5.61it/s, train/loss=2.310]
Epoch 0: | | 604/? [01:47<00:00, 5.60it/s, train/loss=2.310]
Epoch 0: | | 604/? [01:47<00:00, 5.60it/s, train/loss=33.40]
Epoch 0: | | 605/? [01:47<00:00, 5.61it/s, train/loss=33.40]
Epoch 0: | | 605/? [01:47<00:00, 5.61it/s, train/loss=2.350]
Epoch 0: | | 606/? [01:48<00:00, 5.60it/s, train/loss=2.350]
Epoch 0: | | 606/? [01:48<00:00, 5.60it/s, train/loss=13.90]
Epoch 0: | | 607/? [01:48<00:00, 5.61it/s, train/loss=13.90]
Epoch 0: | | 607/? [01:48<00:00, 5.61it/s, train/loss=2.310]
Epoch 0: | | 608/? [01:48<00:00, 5.60it/s, train/loss=2.310]
Epoch 0: | | 608/? [01:48<00:00, 5.60it/s, train/loss=19.40]
Epoch 0: | | 609/? [01:48<00:00, 5.61it/s, train/loss=19.40]
Epoch 0: | | 609/? [01:48<00:00, 5.61it/s, train/loss=2.240]
Epoch 0: | | 610/? [01:48<00:00, 5.60it/s, train/loss=2.240]
Epoch 0: | | 610/? [01:48<00:00, 5.60it/s, train/loss=10.60]
Epoch 0: | | 611/? [01:48<00:00, 5.61it/s, train/loss=10.60]
Epoch 0: | | 611/? [01:48<00:00, 5.61it/s, train/loss=2.180]
Epoch 0: | | 612/? [01:49<00:00, 5.61it/s, train/loss=2.180]
Epoch 0: | | 612/? [01:49<00:00, 5.61it/s, train/loss=23.00]
Epoch 0: | | 613/? [01:49<00:00, 5.61it/s, train/loss=23.00]
Epoch 0: | | 613/? [01:49<00:00, 5.61it/s, train/loss=2.130]
Epoch 0: | | 614/? [01:49<00:00, 5.61it/s, train/loss=2.130]
Epoch 0: | | 614/? [01:49<00:00, 5.61it/s, train/loss=15.30]
Epoch 0: | | 615/? [01:49<00:00, 5.61it/s, train/loss=15.30]
Epoch 0: | | 615/? [01:49<00:00, 5.61it/s, train/loss=2.090]
Epoch 0: | | 616/? [01:49<00:00, 5.61it/s, train/loss=2.090]
Epoch 0: | | 616/? [01:49<00:00, 5.61it/s, train/loss=34.00]
Epoch 0: | | 617/? [01:49<00:00, 5.62it/s, train/loss=34.00]
Epoch 0: | | 617/? [01:49<00:00, 5.62it/s, train/loss=2.060]
Epoch 0: | | 618/? [01:50<00:00, 5.61it/s, train/loss=2.060]
Epoch 0: | | 618/? [01:50<00:00, 5.61it/s, train/loss=10.70]
Epoch 0: | | 619/? [01:50<00:00, 5.62it/s, train/loss=10.70]
Epoch 0: | | 619/? [01:50<00:00, 5.62it/s, train/loss=2.020]
Epoch 0: | | 620/? [01:50<00:00, 5.61it/s, train/loss=2.020]
Epoch 0: | | 620/? [01:50<00:00, 5.61it/s, train/loss=12.90]
Epoch 0: | | 621/? [01:50<00:00, 5.62it/s, train/loss=12.90]
Epoch 0: | | 621/? [01:50<00:00, 5.62it/s, train/loss=1.970]
Epoch 0: | | 622/? [01:50<00:00, 5.61it/s, train/loss=1.970]
Epoch 0: | | 622/? [01:50<00:00, 5.61it/s, train/loss=21.60]
Epoch 0: | | 623/? [01:50<00:00, 5.62it/s, train/loss=21.60]
Epoch 0: | | 623/? [01:50<00:00, 5.62it/s, train/loss=1.930]
Epoch 0: | | 624/? [01:51<00:00, 5.61it/s, train/loss=1.930]
Epoch 0: | | 624/? [01:51<00:00, 5.61it/s, train/loss=36.80]
Epoch 0: | | 625/? [01:51<00:00, 5.62it/s, train/loss=36.80]
Epoch 0: | | 625/? [01:51<00:00, 5.62it/s, train/loss=1.920]
Epoch 0: | | 626/? [01:51<00:00, 5.62it/s, train/loss=1.920]
Epoch 0: | | 626/? [01:51<00:00, 5.62it/s, train/loss=26.50]
Epoch 0: | | 627/? [01:51<00:00, 5.62it/s, train/loss=26.50]
Epoch 0: | | 627/? [01:51<00:00, 5.62it/s, train/loss=1.930]
Epoch 0: | | 628/? [01:51<00:00, 5.62it/s, train/loss=1.930]
Epoch 0: | | 628/? [01:51<00:00, 5.62it/s, train/loss=28.90]
Epoch 0: | | 629/? [01:51<00:00, 5.62it/s, train/loss=28.90]
Epoch 0: | | 629/? [01:51<00:00, 5.62it/s, train/loss=1.910]
Epoch 0: | | 630/? [01:52<00:00, 5.62it/s, train/loss=1.910]
Epoch 0: | | 630/? [01:52<00:00, 5.62it/s, train/loss=35.60]
Epoch 0: | | 631/? [01:52<00:00, 5.63it/s, train/loss=35.60]
Epoch 0: | | 631/? [01:52<00:00, 5.63it/s, train/loss=1.900]
Epoch 0: | | 632/? [01:52<00:00, 5.62it/s, train/loss=1.900]
Epoch 0: | | 632/? [01:52<00:00, 5.62it/s, train/loss=15.00]
Epoch 0: | | 633/? [01:52<00:00, 5.63it/s, train/loss=15.00]
Epoch 0: | | 633/? [01:52<00:00, 5.63it/s, train/loss=1.970]
Epoch 0: | | 634/? [01:52<00:00, 5.62it/s, train/loss=1.970]
Epoch 0: | | 634/? [01:52<00:00, 5.62it/s, train/loss=19.70]
Epoch 0: | | 635/? [01:52<00:00, 5.63it/s, train/loss=19.70]
Epoch 0: | | 635/? [01:52<00:00, 5.63it/s, train/loss=2.050]
Epoch 0: | | 636/? [01:53<00:00, 5.62it/s, train/loss=2.050]
Epoch 0: | | 636/? [01:53<00:00, 5.62it/s, train/loss=33.90]
Epoch 0: | | 637/? [01:53<00:00, 5.63it/s, train/loss=33.90]
Epoch 0: | | 637/? [01:53<00:00, 5.63it/s, train/loss=2.140]
Epoch 0: | | 638/? [01:53<00:00, 5.63it/s, train/loss=2.140]
Epoch 0: | | 638/? [01:53<00:00, 5.62it/s, train/loss=30.40]
Epoch 0: | | 639/? [01:53<00:00, 5.63it/s, train/loss=30.40]
Epoch 0: | | 639/? [01:53<00:00, 5.63it/s, train/loss=2.220]
Epoch 0: | | 640/? [01:53<00:00, 5.63it/s, train/loss=2.220]
Epoch 0: | | 640/? [01:53<00:00, 5.63it/s, train/loss=25.00]
Epoch 0: | | 641/? [01:53<00:00, 5.63it/s, train/loss=25.00]
Epoch 0: | | 641/? [01:53<00:00, 5.63it/s, train/loss=2.240]
Epoch 0: | | 642/? [01:54<00:00, 5.63it/s, train/loss=2.240]
Epoch 0: | | 642/? [01:54<00:00, 5.63it/s, train/loss=10.00]
Epoch 0: | | 643/? [01:54<00:00, 5.63it/s, train/loss=10.00]
Epoch 0: | | 643/? [01:54<00:00, 5.63it/s, train/loss=2.220]
Epoch 0: | | 644/? [01:54<00:00, 5.63it/s, train/loss=2.220]
Epoch 0: | | 644/? [01:54<00:00, 5.63it/s, train/loss=22.80]
Epoch 0: | | 645/? [01:54<00:00, 5.63it/s, train/loss=22.80]
Epoch 0: | | 645/? [01:54<00:00, 5.63it/s, train/loss=2.190]
Epoch 0: | | 646/? [01:54<00:00, 5.63it/s, train/loss=2.190]
Epoch 0: | | 646/? [01:54<00:00, 5.63it/s, train/loss=22.90]
Epoch 0: | | 647/? [01:54<00:00, 5.64it/s, train/loss=22.90]
Epoch 0: | | 647/? [01:54<00:00, 5.64it/s, train/loss=2.190]
Epoch 0: | | 648/? [01:55<00:00, 5.63it/s, train/loss=2.190]
Epoch 0: | | 648/? [01:55<00:00, 5.63it/s, train/loss=42.40]
Epoch 0: | | 649/? [01:55<00:00, 5.64it/s, train/loss=42.40]
Epoch 0: | | 649/? [01:55<00:00, 5.64it/s, train/loss=2.190]
Epoch 0: | | 650/? [01:55<00:00, 5.63it/s, train/loss=2.190]
Epoch 0: | | 650/? [01:55<00:00, 5.63it/s, train/loss=61.90]
Epoch 0: | | 651/? [01:55<00:00, 5.64it/s, train/loss=61.90]
Epoch 0: | | 651/? [01:55<00:00, 5.64it/s, train/loss=2.180]
Epoch 0: | | 652/? [01:55<00:00, 5.63it/s, train/loss=2.180]
Epoch 0: | | 652/? [01:55<00:00, 5.63it/s, train/loss=38.10]
Epoch 0: | | 653/? [01:55<00:00, 5.64it/s, train/loss=38.10]
Epoch 0: | | 653/? [01:55<00:00, 5.64it/s, train/loss=2.180]
Epoch 0: | | 654/? [01:56<00:00, 5.63it/s, train/loss=2.180]
Epoch 0: | | 654/? [01:56<00:00, 5.63it/s, train/loss=20.60]
Epoch 0: | | 655/? [01:56<00:00, 5.64it/s, train/loss=20.60]
Epoch 0: | | 655/? [01:56<00:00, 5.64it/s, train/loss=2.230]
Epoch 0: | | 656/? [01:56<00:00, 5.64it/s, train/loss=2.230]
Epoch 0: | | 656/? [01:56<00:00, 5.64it/s, train/loss=18.20]
Epoch 0: | | 657/? [01:56<00:00, 5.64it/s, train/loss=18.20]
Epoch 0: | | 657/? [01:56<00:00, 5.64it/s, train/loss=2.270]
Epoch 0: | | 658/? [01:56<00:00, 5.64it/s, train/loss=2.270]
Epoch 0: | | 658/? [01:56<00:00, 5.64it/s, train/loss=17.30]
Epoch 0: | | 659/? [01:56<00:00, 5.64it/s, train/loss=17.30]
Epoch 0: | | 659/? [01:56<00:00, 5.64it/s, train/loss=2.290]
Epoch 0: | | 660/? [01:57<00:00, 5.64it/s, train/loss=2.290]
Epoch 0: | | 660/? [01:57<00:00, 5.64it/s, train/loss=11.40]
Epoch 0: | | 661/? [01:57<00:00, 5.64it/s, train/loss=11.40]
Epoch 0: | | 661/? [01:57<00:00, 5.64it/s, train/loss=2.270]
Epoch 0: | | 662/? [01:57<00:00, 5.64it/s, train/loss=2.270]
Epoch 0: | | 662/? [01:57<00:00, 5.64it/s, train/loss=14.50]
Epoch 0: | | 663/? [01:57<00:00, 5.65it/s, train/loss=14.50]
Epoch 0: | | 663/? [01:57<00:00, 5.65it/s, train/loss=2.210]
Epoch 0: | | 664/? [01:57<00:00, 5.64it/s, train/loss=2.210]
Epoch 0: | | 664/? [01:57<00:00, 5.64it/s, train/loss=24.50]
Epoch 0: | | 665/? [01:57<00:00, 5.65it/s, train/loss=24.50]
Epoch 0: | | 665/? [01:57<00:00, 5.65it/s, train/loss=2.100]
Epoch 0: | | 666/? [01:58<00:00, 5.64it/s, train/loss=2.100]
Epoch 0: | | 666/? [01:58<00:00, 5.64it/s, train/loss=29.30]
Epoch 0: | | 667/? [01:58<00:00, 5.65it/s, train/loss=29.30]
Epoch 0: | | 667/? [01:58<00:00, 5.65it/s, train/loss=2.000]
Epoch 0: | | 668/? [01:58<00:00, 5.64it/s, train/loss=2.000]
Epoch 0: | | 668/? [01:58<00:00, 5.64it/s, train/loss=24.10]
Epoch 0: | | 669/? [01:58<00:00, 5.65it/s, train/loss=24.10]
Epoch 0: | | 669/? [01:58<00:00, 5.65it/s, train/loss=1.960]
Epoch 0: | | 670/? [01:58<00:00, 5.64it/s, train/loss=1.960]
Epoch 0: | | 670/? [01:58<00:00, 5.64it/s, train/loss=32.10]
Epoch 0: | | 671/? [01:58<00:00, 5.65it/s, train/loss=32.10]
Epoch 0: | | 671/? [01:58<00:00, 5.65it/s, train/loss=1.950]
Epoch 0: | | 672/? [01:59<00:00, 5.65it/s, train/loss=1.950]
Epoch 0: | | 672/? [01:59<00:00, 5.65it/s, train/loss=21.70]
Epoch 0: | | 673/? [01:59<00:00, 5.65it/s, train/loss=21.70]
Epoch 0: | | 673/? [01:59<00:00, 5.65it/s, train/loss=1.960]
Epoch 0: | | 674/? [01:59<00:00, 5.65it/s, train/loss=1.960]
Epoch 0: | | 674/? [01:59<00:00, 5.65it/s, train/loss=31.20]
Epoch 0: | | 675/? [01:59<00:00, 5.65it/s, train/loss=31.20]
Epoch 0: | | 675/? [01:59<00:00, 5.65it/s, train/loss=1.980]
Epoch 0: | | 676/? [01:59<00:00, 5.65it/s, train/loss=1.980]
Epoch 0: | | 676/? [01:59<00:00, 5.65it/s, train/loss=10.90]
Epoch 0: | | 677/? [01:59<00:00, 5.65it/s, train/loss=10.90]
Epoch 0: | | 677/? [01:59<00:00, 5.65it/s, train/loss=2.000]
Epoch 0: | | 678/? [02:00<00:00, 5.65it/s, train/loss=2.000]
Epoch 0: | | 678/? [02:00<00:00, 5.65it/s, train/loss=11.30]
Epoch 0: | | 679/? [02:00<00:00, 5.66it/s, train/loss=11.30]
Epoch 0: | | 679/? [02:00<00:00, 5.66it/s, train/loss=2.020]
Epoch 0: | | 680/? [02:00<00:00, 5.65it/s, train/loss=2.020]
Epoch 0: | | 680/? [02:00<00:00, 5.65it/s, train/loss=26.00]
Epoch 0: | | 681/? [02:00<00:00, 5.66it/s, train/loss=26.00]
Epoch 0: | | 681/? [02:00<00:00, 5.66it/s, train/loss=2.000]
Epoch 0: | | 682/? [02:00<00:00, 5.65it/s, train/loss=2.000]
Epoch 0: | | 682/? [02:00<00:00, 5.65it/s, train/loss=26.70]
Epoch 0: | | 683/? [02:00<00:00, 5.66it/s, train/loss=26.70]
Epoch 0: | | 683/? [02:00<00:00, 5.66it/s, train/loss=1.980]
Epoch 0: | | 684/? [02:01<00:00, 5.65it/s, train/loss=1.980]
Epoch 0: | | 684/? [02:01<00:00, 5.65it/s, train/loss=8.930]
Epoch 0: | | 685/? [02:01<00:00, 5.66it/s, train/loss=8.930]
Epoch 0: | | 685/? [02:01<00:00, 5.66it/s, train/loss=1.980]
Epoch 0: | | 686/? [02:01<00:00, 5.65it/s, train/loss=1.980]
Epoch 0: | | 686/? [02:01<00:00, 5.65it/s, train/loss=37.30]
Epoch 0: | | 687/? [02:01<00:00, 5.66it/s, train/loss=37.30]
Epoch 0: | | 687/? [02:01<00:00, 5.66it/s, train/loss=1.970]
Epoch 0: | | 688/? [02:01<00:00, 5.65it/s, train/loss=1.970]
Epoch 0: | | 688/? [02:01<00:00, 5.65it/s, train/loss=30.80]
Epoch 0: | | 689/? [02:01<00:00, 5.66it/s, train/loss=30.80]
Epoch 0: | | 689/? [02:01<00:00, 5.66it/s, train/loss=2.160]
Epoch 0: | | 690/? [02:02<00:00, 5.65it/s, train/loss=2.160]
Epoch 0: | | 690/? [02:02<00:00, 5.65it/s, train/loss=32.70]
Epoch 0: | | 691/? [02:02<00:00, 5.66it/s, train/loss=32.70]
Epoch 0: | | 691/? [02:02<00:00, 5.66it/s, train/loss=2.230]
Epoch 0: | | 692/? [02:02<00:00, 5.65it/s, train/loss=2.230]
Epoch 0: | | 692/? [02:02<00:00, 5.65it/s, train/loss=22.50]
Epoch 0: | | 693/? [02:02<00:00, 5.66it/s, train/loss=22.50]
Epoch 0: | | 693/? [02:02<00:00, 5.66it/s, train/loss=2.280]
Epoch 0: | | 694/? [02:02<00:00, 5.65it/s, train/loss=2.280]
Epoch 0: | | 694/? [02:02<00:00, 5.65it/s, train/loss=23.20]
Epoch 0: | | 695/? [02:02<00:00, 5.66it/s, train/loss=23.20]
Epoch 0: | | 695/? [02:02<00:00, 5.66it/s, train/loss=2.250]
Epoch 0: | | 696/? [02:03<00:00, 5.65it/s, train/loss=2.250]
Epoch 0: | | 696/? [02:03<00:00, 5.65it/s, train/loss=40.20]
Epoch 0: | | 697/? [02:03<00:00, 5.66it/s, train/loss=40.20]
Epoch 0: | | 697/? [02:03<00:00, 5.66it/s, train/loss=2.170]
Epoch 0: | | 698/? [02:03<00:00, 5.66it/s, train/loss=2.170]
Epoch 0: | | 698/? [02:03<00:00, 5.66it/s, train/loss=16.40]
Epoch 0: | | 699/? [02:03<00:00, 5.66it/s, train/loss=16.40]
Epoch 0: | | 699/? [02:03<00:00, 5.66it/s, train/loss=2.140]
Epoch 0: | | 700/? [02:03<00:00, 5.66it/s, train/loss=2.140]
Epoch 0: | | 700/? [02:03<00:00, 5.66it/s, train/loss=13.90]
Epoch 0: | | 701/? [02:03<00:00, 5.66it/s, train/loss=13.90]
Epoch 0: | | 701/? [02:03<00:00, 5.66it/s, train/loss=2.160]
Epoch 0: | | 702/? [02:04<00:00, 5.66it/s, train/loss=2.160]
Epoch 0: | | 702/? [02:04<00:00, 5.66it/s, train/loss=18.10]
Epoch 0: | | 703/? [02:04<00:00, 5.67it/s, train/loss=18.10]
Epoch 0: | | 703/? [02:04<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 704/? [02:04<00:00, 5.66it/s, train/loss=2.180]
Epoch 0: | | 704/? [02:04<00:00, 5.66it/s, train/loss=23.20]
Epoch 0: | | 705/? [02:04<00:00, 5.67it/s, train/loss=23.20]
Epoch 0: | | 705/? [02:04<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 706/? [02:04<00:00, 5.66it/s, train/loss=2.180]
Epoch 0: | | 706/? [02:04<00:00, 5.66it/s, train/loss=31.30]
Epoch 0: | | 707/? [02:04<00:00, 5.67it/s, train/loss=31.30]
Epoch 0: | | 707/? [02:04<00:00, 5.67it/s, train/loss=2.160]
Epoch 0: | | 708/? [02:04<00:00, 5.66it/s, train/loss=2.160]
Epoch 0: | | 708/? [02:04<00:00, 5.66it/s, train/loss=19.40]
Epoch 0: | | 709/? [02:05<00:00, 5.67it/s, train/loss=19.40]
Epoch 0: | | 709/? [02:05<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 710/? [02:05<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 710/? [02:05<00:00, 5.67it/s, train/loss=31.20]
Epoch 0: | | 711/? [02:05<00:00, 5.67it/s, train/loss=31.20]
Epoch 0: | | 711/? [02:05<00:00, 5.67it/s, train/loss=2.220]
Epoch 0: | | 712/? [02:05<00:00, 5.67it/s, train/loss=2.220]
Epoch 0: | | 712/? [02:05<00:00, 5.67it/s, train/loss=46.40]
Epoch 0: | | 713/? [02:05<00:00, 5.67it/s, train/loss=46.40]
Epoch 0: | | 713/? [02:05<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 714/? [02:06<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 714/? [02:06<00:00, 5.67it/s, train/loss=31.40]
Epoch 0: | | 715/? [02:06<00:00, 5.67it/s, train/loss=31.40]
Epoch 0: | | 715/? [02:06<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 716/? [02:06<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 716/? [02:06<00:00, 5.67it/s, train/loss=35.10]
Epoch 0: | | 717/? [02:06<00:00, 5.67it/s, train/loss=35.10]
Epoch 0: | | 717/? [02:06<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 718/? [02:06<00:00, 5.67it/s, train/loss=2.200]
Epoch 0: | | 718/? [02:06<00:00, 5.67it/s, train/loss=23.40]
Epoch 0: | | 719/? [02:06<00:00, 5.67it/s, train/loss=23.40]
Epoch 0: | | 719/? [02:06<00:00, 5.67it/s, train/loss=2.210]
Epoch 0: | | 720/? [02:07<00:00, 5.67it/s, train/loss=2.210]
Epoch 0: | | 720/? [02:07<00:00, 5.67it/s, train/loss=16.20]
Epoch 0: | | 721/? [02:07<00:00, 5.67it/s, train/loss=16.20]
Epoch 0: | | 721/? [02:07<00:00, 5.67it/s, train/loss=2.210]
Epoch 0: | | 722/? [02:07<00:00, 5.67it/s, train/loss=2.210]
Epoch 0: | | 722/? [02:07<00:00, 5.67it/s, train/loss=22.00]
Epoch 0: | | 723/? [02:07<00:00, 5.67it/s, train/loss=22.00]
Epoch 0: | | 723/? [02:07<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 724/? [02:07<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 724/? [02:07<00:00, 5.67it/s, train/loss=50.60]
Epoch 0: | | 725/? [02:07<00:00, 5.68it/s, train/loss=50.60]
Epoch 0: | | 725/? [02:07<00:00, 5.68it/s, train/loss=2.160]
Epoch 0: | | 726/? [02:08<00:00, 5.67it/s, train/loss=2.160]
Epoch 0: | | 726/? [02:08<00:00, 5.67it/s, train/loss=44.00]
Epoch 0: | | 727/? [02:08<00:00, 5.68it/s, train/loss=44.00]
Epoch 0: | | 727/? [02:08<00:00, 5.68it/s, train/loss=2.180]
Epoch 0: | | 728/? [02:08<00:00, 5.67it/s, train/loss=2.180]
Epoch 0: | | 728/? [02:08<00:00, 5.67it/s, train/loss=33.60]
Epoch 0: | | 729/? [02:08<00:00, 5.68it/s, train/loss=33.60]
Epoch 0: | | 729/? [02:08<00:00, 5.68it/s, train/loss=2.210]
Epoch 0: | | 730/? [02:08<00:00, 5.67it/s, train/loss=2.210]
Epoch 0: | | 730/? [02:08<00:00, 5.67it/s, train/loss=20.70]
Epoch 0: | | 731/? [02:08<00:00, 5.68it/s, train/loss=20.70]
Epoch 0: | | 731/? [02:08<00:00, 5.68it/s, train/loss=2.210]
Epoch 0: | | 732/? [02:08<00:00, 5.68it/s, train/loss=2.210]
Epoch 0: | | 732/? [02:08<00:00, 5.68it/s, train/loss=19.10]
Epoch 0: | | 733/? [02:09<00:00, 5.68it/s, train/loss=19.10]
Epoch 0: | | 733/? [02:09<00:00, 5.68it/s, train/loss=2.180]
Epoch 0: | | 734/? [02:09<00:00, 5.68it/s, train/loss=2.180]
Epoch 0: | | 734/? [02:09<00:00, 5.68it/s, train/loss=17.30]
Epoch 0: | | 735/? [02:09<00:00, 5.68it/s, train/loss=17.30]
Epoch 0: | | 735/? [02:09<00:00, 5.68it/s, train/loss=2.130]
Epoch 0: | | 736/? [02:09<00:00, 5.68it/s, train/loss=2.130]
Epoch 0: | | 736/? [02:09<00:00, 5.68it/s, train/loss=32.90]
Epoch 0: | | 737/? [02:09<00:00, 5.68it/s, train/loss=32.90]
Epoch 0: | | 737/? [02:09<00:00, 5.68it/s, train/loss=2.070]
Epoch 0: | | 738/? [02:09<00:00, 5.68it/s, train/loss=2.070]
Epoch 0: | | 738/? [02:09<00:00, 5.68it/s, train/loss=25.10]
Epoch 0: | | 739/? [02:09<00:00, 5.69it/s, train/loss=25.10]
Epoch 0: | | 739/? [02:09<00:00, 5.69it/s, train/loss=2.010]
Epoch 0: | | 740/? [02:10<00:00, 5.68it/s, train/loss=2.010]
Epoch 0: | | 740/? [02:10<00:00, 5.68it/s, train/loss=26.20]
Epoch 0: | | 741/? [02:10<00:00, 5.69it/s, train/loss=26.20]
Epoch 0: | | 741/? [02:10<00:00, 5.69it/s, train/loss=1.970]
Epoch 0: | | 742/? [02:10<00:00, 5.68it/s, train/loss=1.970]
Epoch 0: | | 742/? [02:10<00:00, 5.68it/s, train/loss=38.50]
Epoch 0: | | 743/? [02:10<00:00, 5.69it/s, train/loss=38.50]
Epoch 0: | | 743/? [02:10<00:00, 5.69it/s, train/loss=1.960]
Epoch 0: | | 744/? [02:10<00:00, 5.68it/s, train/loss=1.960]
Epoch 0: | | 744/? [02:10<00:00, 5.68it/s, train/loss=26.20]
Epoch 0: | | 745/? [02:10<00:00, 5.69it/s, train/loss=26.20]
Epoch 0: | | 745/? [02:10<00:00, 5.69it/s, train/loss=1.960]
Epoch 0: | | 746/? [02:11<00:00, 5.68it/s, train/loss=1.960]
Epoch 0: | | 746/? [02:11<00:00, 5.68it/s, train/loss=29.00]
Epoch 0: | | 747/? [02:11<00:00, 5.69it/s, train/loss=29.00]
Epoch 0: | | 747/? [02:11<00:00, 5.69it/s, train/loss=1.990]
Epoch 0: | | 748/? [02:11<00:00, 5.69it/s, train/loss=1.990]
Epoch 0: | | 748/? [02:11<00:00, 5.69it/s, train/loss=15.30]
Epoch 0: | | 749/? [02:11<00:00, 5.69it/s, train/loss=15.30]
Epoch 0: | | 749/? [02:11<00:00, 5.69it/s, train/loss=2.030]
Epoch 0: | | 750/? [02:11<00:00, 5.69it/s, train/loss=2.030]
Epoch 0: | | 750/? [02:11<00:00, 5.69it/s, train/loss=52.50]
Epoch 0: | | 751/? [02:11<00:00, 5.69it/s, train/loss=52.50]
Epoch 0: | | 751/? [02:11<00:00, 5.69it/s, train/loss=2.080]
Epoch 0: | | 752/? [02:12<00:00, 5.69it/s, train/loss=2.080]
Epoch 0: | | 752/? [02:12<00:00, 5.69it/s, train/loss=38.80]
Epoch 0: | | 753/? [02:12<00:00, 5.69it/s, train/loss=38.80]
Epoch 0: | | 753/? [02:12<00:00, 5.69it/s, train/loss=2.160]
Epoch 0: | | 754/? [02:12<00:00, 5.69it/s, train/loss=2.160]
Epoch 0: | | 754/? [02:12<00:00, 5.69it/s, train/loss=16.20]
Epoch 0: | | 755/? [02:12<00:00, 5.70it/s, train/loss=16.20]
Epoch 0: | | 755/? [02:12<00:00, 5.69it/s, train/loss=2.220]
Epoch 0: | | 756/? [02:12<00:00, 5.69it/s, train/loss=2.220]
Epoch 0: | | 756/? [02:12<00:00, 5.69it/s, train/loss=35.80]
Epoch 0: | | 757/? [02:12<00:00, 5.70it/s, train/loss=35.80]
Epoch 0: | | 757/? [02:12<00:00, 5.70it/s, train/loss=2.240]
Epoch 0: | | 758/? [02:13<00:00, 5.69it/s, train/loss=2.240]
Epoch 0: | | 758/? [02:13<00:00, 5.69it/s, train/loss=64.60]
Epoch 0: | | 759/? [02:13<00:00, 5.70it/s, train/loss=64.60]
Epoch 0: | | 759/? [02:13<00:00, 5.70it/s, train/loss=2.280]
Epoch 0: | | 760/? [02:13<00:00, 5.69it/s, train/loss=2.280]
Epoch 0: | | 760/? [02:13<00:00, 5.69it/s, train/loss=38.20]
Epoch 0: | | 761/? [02:13<00:00, 5.70it/s, train/loss=38.20]
Epoch 0: | | 761/? [02:13<00:00, 5.70it/s, train/loss=2.400]
Epoch 0: | | 762/? [02:13<00:00, 5.69it/s, train/loss=2.400]
Epoch 0: | | 762/? [02:13<00:00, 5.69it/s, train/loss=23.40]
Epoch 0: | | 763/? [02:13<00:00, 5.70it/s, train/loss=23.40]
Epoch 0: | | 763/? [02:13<00:00, 5.70it/s, train/loss=2.530]
Epoch 0: | | 764/? [02:14<00:00, 5.70it/s, train/loss=2.530]
Epoch 0: | | 764/? [02:14<00:00, 5.70it/s, train/loss=37.80]
Epoch 0: | | 765/? [02:14<00:00, 5.70it/s, train/loss=37.80]
Epoch 0: | | 765/? [02:14<00:00, 5.70it/s, train/loss=2.580]
Epoch 0: | | 766/? [02:14<00:00, 5.70it/s, train/loss=2.580]
Epoch 0: | | 766/? [02:14<00:00, 5.70it/s, train/loss=9.400]
Epoch 0: | | 767/? [02:14<00:00, 5.70it/s, train/loss=9.400]
Epoch 0: | | 767/? [02:14<00:00, 5.70it/s, train/loss=2.530]
Epoch 0: | | 768/? [02:14<00:00, 5.70it/s, train/loss=2.530]
Epoch 0: | | 768/? [02:14<00:00, 5.70it/s, train/loss=17.00]
Epoch 0: | | 769/? [02:14<00:00, 5.70it/s, train/loss=17.00]
Epoch 0: | | 769/? [02:14<00:00, 5.70it/s, train/loss=2.400]
Epoch 0: | | 770/? [02:15<00:00, 5.70it/s, train/loss=2.400]
Epoch 0: | | 770/? [02:15<00:00, 5.70it/s, train/loss=17.40]
Epoch 0: | | 771/? [02:15<00:00, 5.70it/s, train/loss=17.40]
Epoch 0: | | 771/? [02:15<00:00, 5.70it/s, train/loss=2.240]
Epoch 0: | | 772/? [02:15<00:00, 5.70it/s, train/loss=2.240]
Epoch 0: | | 772/? [02:15<00:00, 5.70it/s, train/loss=43.20]
Epoch 0: | | 773/? [02:15<00:00, 5.71it/s, train/loss=43.20]
Epoch 0: | | 773/? [02:15<00:00, 5.71it/s, train/loss=2.160]
Epoch 0: | | 774/? [02:15<00:00, 5.70it/s, train/loss=2.160]
Epoch 0: | | 774/? [02:15<00:00, 5.70it/s, train/loss=21.60]
Epoch 0: | | 775/? [02:15<00:00, 5.71it/s, train/loss=21.60]
Epoch 0: | | 775/? [02:15<00:00, 5.71it/s, train/loss=2.140]
Epoch 0: | | 776/? [02:16<00:00, 5.70it/s, train/loss=2.140]
Epoch 0: | | 776/? [02:16<00:00, 5.70it/s, train/loss=20.60]
Epoch 0: | | 777/? [02:16<00:00, 5.71it/s, train/loss=20.60]
Epoch 0: | | 777/? [02:16<00:00, 5.71it/s, train/loss=2.150]
Epoch 0: | | 778/? [02:16<00:00, 5.70it/s, train/loss=2.150]
Epoch 0: | | 778/? [02:16<00:00, 5.70it/s, train/loss=14.50]
Epoch 0: | | 779/? [02:16<00:00, 5.71it/s, train/loss=14.50]
Epoch 0: | | 779/? [02:16<00:00, 5.71it/s, train/loss=2.200]
Epoch 0: | | 780/? [02:16<00:00, 5.70it/s, train/loss=2.200]
Epoch 0: | | 780/? [02:16<00:00, 5.70it/s, train/loss=29.70]
Epoch 0: | | 781/? [02:16<00:00, 5.71it/s, train/loss=29.70]
Epoch 0: | | 781/? [02:16<00:00, 5.71it/s, train/loss=2.210]
Epoch 0: | | 782/? [02:17<00:00, 5.71it/s, train/loss=2.210]
Epoch 0: | | 782/? [02:17<00:00, 5.71it/s, train/loss=6.770]
Epoch 0: | | 783/? [02:17<00:00, 5.71it/s, train/loss=6.770]
Epoch 0: | | 783/? [02:17<00:00, 5.71it/s, train/loss=2.180]
Epoch 0: | | 784/? [02:17<00:00, 5.71it/s, train/loss=2.180]
Epoch 0: | | 784/? [02:17<00:00, 5.71it/s, train/loss=51.80]
Epoch 0: | | 785/? [02:17<00:00, 5.71it/s, train/loss=51.80]
Epoch 0: | | 785/? [02:17<00:00, 5.71it/s, train/loss=2.120]
Epoch 0: | | 786/? [02:17<00:00, 5.71it/s, train/loss=2.120]
Epoch 0: | | 786/? [02:17<00:00, 5.71it/s, train/loss=13.10]
Epoch 0: | | 787/? [02:17<00:00, 5.71it/s, train/loss=13.10]
Epoch 0: | | 787/? [02:17<00:00, 5.71it/s, train/loss=2.060]
Epoch 0: | | 788/? [02:18<00:00, 5.71it/s, train/loss=2.060]
Epoch 0: | | 788/? [02:18<00:00, 5.71it/s, train/loss=31.40]
Epoch 0: | | 789/? [02:18<00:00, 5.71it/s, train/loss=31.40]
Epoch 0: | | 789/? [02:18<00:00, 5.71it/s, train/loss=2.040]
Epoch 0: | | 790/? [02:18<00:00, 5.71it/s, train/loss=2.040]
Epoch 0: | | 790/? [02:18<00:00, 5.71it/s, train/loss=18.20]
Epoch 0: | | 791/? [02:18<00:00, 5.71it/s, train/loss=18.20]
Epoch 0: | | 791/? [02:18<00:00, 5.71it/s, train/loss=2.020]
Epoch 0: | | 792/? [02:18<00:00, 5.71it/s, train/loss=2.020]
Epoch 0: | | 792/? [02:18<00:00, 5.71it/s, train/loss=19.10]
Epoch 0: | | 793/? [02:18<00:00, 5.72it/s, train/loss=19.10]
Epoch 0: | | 793/? [02:18<00:00, 5.72it/s, train/loss=2.000]
Epoch 0: | | 794/? [02:19<00:00, 5.71it/s, train/loss=2.000]
Epoch 0: | | 794/? [02:19<00:00, 5.71it/s, train/loss=11.40]
Epoch 0: | | 795/? [02:19<00:00, 5.72it/s, train/loss=11.40]
Epoch 0: | | 795/? [02:19<00:00, 5.72it/s, train/loss=1.990]
Epoch 0: | | 796/? [02:19<00:00, 5.71it/s, train/loss=1.990]
Epoch 0: | | 796/? [02:19<00:00, 5.71it/s, train/loss=21.00]
Epoch 0: | | 797/? [02:19<00:00, 5.72it/s, train/loss=21.00]
Epoch 0: | | 797/? [02:19<00:00, 5.72it/s, train/loss=1.990]
Epoch 0: | | 798/? [02:19<00:00, 5.71it/s, train/loss=1.990]
Epoch 0: | | 798/? [02:19<00:00, 5.71it/s, train/loss=19.80]
Epoch 0: | | 799/? [02:19<00:00, 5.72it/s, train/loss=19.80]
Epoch 0: | | 799/? [02:19<00:00, 5.72it/s, train/loss=1.960]
Epoch 0: | | 800/? [02:20<00:00, 5.71it/s, train/loss=1.960]
Epoch 0: | | 800/? [02:20<00:00, 5.71it/s, train/loss=19.80]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:00, 65.46it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:01, 31.53it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:00, 38.31it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:00, 40.70it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:00, 37.31it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:00, 40.04it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:00, 42.57it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:00, 44.78it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:00, 46.68it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:00, 48.30it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:00, 49.68it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:00<00:00, 50.92it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:00<00:00, 51.66it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:00<00:00, 52.59it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:00<00:00, 53.46it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:00<00:00, 54.25it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:00<00:00, 54.95it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:00<00:00, 55.61it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:00<00:00, 56.23it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:00<00:00, 56.76it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:00<00:00, 57.23it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:00<00:00, 57.70it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:00<00:00, 58.15it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:00<00:00, 56.91it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:00<00:00, 57.10it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:00<00:00, 57.49it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:00<00:00, 57.87it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:00<00:00, 58.21it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:00<00:00, 58.55it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:00<00:00, 58.87it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:00<00:00, 59.02it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:00<00:00, 59.31it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:00<00:00, 59.58it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:00<00:00, 59.84it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:00<00:00, 60.09it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:00<00:00, 60.31it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:00<00:00, 60.51it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:00<00:00, 60.69it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:00<00:00, 60.86it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:00<00:00, 61.03it/s][A
[A
Epoch 0: | | 800/? [02:21<00:00, 5.65it/s, train/loss=19.80]
`Trainer.fit` stopped: `max_steps=800` reached.
Epoch 0: | | 800/? [02:21<00:00, 5.65it/s, train/loss=19.80]
Epoch 0: | | 800/? [02:21<00:00, 5.64it/s, train/loss=19.80]
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 64, 64, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 64, 64])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
Testing: | | 0/? [00:00<?, ?it/s]
Testing: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 1%| | 1/120 [00:00<00:01, 63.71it/s]
Testing DataLoader 0: 2%|▏ | 2/120 [00:00<00:01, 65.37it/s]
Testing DataLoader 0: 2%|▎ | 3/120 [00:00<00:01, 67.23it/s]
Testing DataLoader 0: 3%|▎ | 4/120 [00:00<00:01, 68.26it/s]
Testing DataLoader 0: 4%|▍ | 5/120 [00:00<00:01, 68.84it/s]
Testing DataLoader 0: 5%|▌ | 6/120 [00:00<00:01, 68.90it/s]
Testing DataLoader 0: 6%|▌ | 7/120 [00:00<00:01, 69.07it/s]
Testing DataLoader 0: 7%|▋ | 8/120 [00:00<00:01, 69.10it/s]
Testing DataLoader 0: 8%|▊ | 9/120 [00:00<00:01, 66.13it/s]
Testing DataLoader 0: 8%|▊ | 10/120 [00:00<00:01, 60.76it/s]
Testing DataLoader 0: 9%|▉ | 11/120 [00:00<00:01, 61.49it/s]
Testing DataLoader 0: 10%|█ | 12/120 [00:00<00:01, 62.13it/s]
Testing DataLoader 0: 11%|█ | 13/120 [00:00<00:01, 62.68it/s]
Testing DataLoader 0: 12%|█▏ | 14/120 [00:00<00:01, 63.19it/s]
Testing DataLoader 0: 12%|█▎ | 15/120 [00:00<00:01, 63.63it/s]
Testing DataLoader 0: 13%|█▎ | 16/120 [00:00<00:01, 63.97it/s]
Testing DataLoader 0: 14%|█▍ | 17/120 [00:00<00:01, 64.28it/s]
Testing DataLoader 0: 15%|█▌ | 18/120 [00:00<00:01, 64.59it/s]
Testing DataLoader 0: 16%|█▌ | 19/120 [00:00<00:01, 64.89it/s]
Testing DataLoader 0: 17%|█▋ | 20/120 [00:00<00:01, 65.16it/s]
Testing DataLoader 0: 18%|█▊ | 21/120 [00:00<00:01, 65.39it/s]
Testing DataLoader 0: 18%|█▊ | 22/120 [00:00<00:01, 61.40it/s]
Testing DataLoader 0: 19%|█▉ | 23/120 [00:00<00:01, 58.31it/s]
Testing DataLoader 0: 20%|██ | 24/120 [00:00<00:01, 55.72it/s]
Testing DataLoader 0: 21%|██ | 25/120 [00:00<00:01, 53.55it/s]
Testing DataLoader 0: 22%|██▏ | 26/120 [00:00<00:01, 54.03it/s]
Testing DataLoader 0: 22%|██▎ | 27/120 [00:00<00:01, 54.49it/s]
Testing DataLoader 0: 23%|██▎ | 28/120 [00:00<00:01, 54.93it/s]
Testing DataLoader 0: 24%|██▍ | 29/120 [00:00<00:01, 55.35it/s]
Testing DataLoader 0: 25%|██▌ | 30/120 [00:00<00:01, 55.73it/s]
Testing DataLoader 0: 26%|██▌ | 31/120 [00:00<00:01, 56.11it/s]
Testing DataLoader 0: 27%|██▋ | 32/120 [00:00<00:01, 56.46it/s]
Testing DataLoader 0: 28%|██▊ | 33/120 [00:00<00:01, 56.81it/s]
Testing DataLoader 0: 28%|██▊ | 34/120 [00:00<00:01, 57.14it/s]
Testing DataLoader 0: 29%|██▉ | 35/120 [00:00<00:01, 57.46it/s]
Testing DataLoader 0: 30%|███ | 36/120 [00:00<00:01, 57.75it/s]
Testing DataLoader 0: 31%|███ | 37/120 [00:00<00:01, 58.04it/s]
Testing DataLoader 0: 32%|███▏ | 38/120 [00:00<00:01, 58.29it/s]
Testing DataLoader 0: 32%|███▎ | 39/120 [00:00<00:01, 58.55it/s]
Testing DataLoader 0: 33%|███▎ | 40/120 [00:00<00:01, 58.79it/s]
Testing DataLoader 0: 34%|███▍ | 41/120 [00:00<00:01, 59.03it/s]
Testing DataLoader 0: 35%|███▌ | 42/120 [00:00<00:01, 59.25it/s]
Testing DataLoader 0: 36%|███▌ | 43/120 [00:00<00:01, 59.47it/s]
Testing DataLoader 0: 37%|███▋ | 44/120 [00:00<00:01, 59.68it/s]
Testing DataLoader 0: 38%|███▊ | 45/120 [00:00<00:01, 59.84it/s]
Testing DataLoader 0: 38%|███▊ | 46/120 [00:00<00:01, 60.04it/s]
Testing DataLoader 0: 39%|███▉ | 47/120 [00:00<00:01, 60.22it/s]
Testing DataLoader 0: 40%|████ | 48/120 [00:00<00:01, 60.40it/s]
Testing DataLoader 0: 41%|████ | 49/120 [00:00<00:01, 60.57it/s]
Testing DataLoader 0: 42%|████▏ | 50/120 [00:00<00:01, 60.74it/s]
Testing DataLoader 0: 42%|████▎ | 51/120 [00:00<00:01, 60.90it/s]
Testing DataLoader 0: 43%|████▎ | 52/120 [00:00<00:01, 60.98it/s]
Testing DataLoader 0: 44%|████▍ | 53/120 [00:00<00:01, 61.13it/s]
Testing DataLoader 0: 45%|████▌ | 54/120 [00:00<00:01, 61.28it/s]
Testing DataLoader 0: 46%|████▌ | 55/120 [00:00<00:01, 61.42it/s]
Testing DataLoader 0: 47%|████▋ | 56/120 [00:00<00:01, 61.56it/s]
Testing DataLoader 0: 48%|████▊ | 57/120 [00:00<00:01, 61.69it/s]
Testing DataLoader 0: 48%|████▊ | 58/120 [00:00<00:01, 61.83it/s]
Testing DataLoader 0: 49%|████▉ | 59/120 [00:00<00:00, 61.95it/s]
Testing DataLoader 0: 50%|█████ | 60/120 [00:00<00:00, 62.08it/s]
Testing DataLoader 0: 51%|█████ | 61/120 [00:00<00:00, 62.20it/s]
Testing DataLoader 0: 52%|█████▏ | 62/120 [00:00<00:00, 62.32it/s]
Testing DataLoader 0: 52%|█████▎ | 63/120 [00:01<00:00, 62.44it/s]
Testing DataLoader 0: 53%|█████▎ | 64/120 [00:01<00:00, 62.55it/s]
Testing DataLoader 0: 54%|█████▍ | 65/120 [00:01<00:00, 62.65it/s]
Testing DataLoader 0: 55%|█████▌ | 66/120 [00:01<00:00, 62.76it/s]
Testing DataLoader 0: 56%|█████▌ | 67/120 [00:01<00:00, 62.85it/s]
Testing DataLoader 0: 57%|█████▋ | 68/120 [00:01<00:00, 62.95it/s]
Testing DataLoader 0: 57%|█████▊ | 69/120 [00:01<00:00, 63.04it/s]
Testing DataLoader 0: 58%|█████▊ | 70/120 [00:01<00:00, 63.14it/s]
Testing DataLoader 0: 59%|█████▉ | 71/120 [00:01<00:00, 63.23it/s]
Testing DataLoader 0: 60%|██████ | 72/120 [00:01<00:00, 63.01it/s]
Testing DataLoader 0: 61%|██████ | 73/120 [00:01<00:00, 62.79it/s]
Testing DataLoader 0: 62%|██████▏ | 74/120 [00:01<00:00, 61.71it/s]
Testing DataLoader 0: 62%|██████▎ | 75/120 [00:01<00:00, 60.96it/s]
Testing DataLoader 0: 63%|██████▎ | 76/120 [00:01<00:00, 60.23it/s]
Testing DataLoader 0: 64%|██████▍ | 77/120 [00:01<00:00, 60.32it/s]
Testing DataLoader 0: 65%|██████▌ | 78/120 [00:01<00:00, 60.42it/s]
Testing DataLoader 0: 66%|██████▌ | 79/120 [00:01<00:00, 60.53it/s]
Testing DataLoader 0: 67%|██████▋ | 80/120 [00:01<00:00, 60.47it/s]
Testing DataLoader 0: 68%|██████▊ | 81/120 [00:01<00:00, 60.57it/s]
Testing DataLoader 0: 68%|██████▊ | 82/120 [00:01<00:00, 60.67it/s]
Testing DataLoader 0: 69%|██████▉ | 83/120 [00:01<00:00, 60.75it/s]
Testing DataLoader 0: 70%|███████ | 84/120 [00:01<00:00, 60.84it/s]
Testing DataLoader 0: 71%|███████ | 85/120 [00:01<00:00, 60.93it/s]
Testing DataLoader 0: 72%|███████▏ | 86/120 [00:01<00:00, 61.02it/s]
Testing DataLoader 0: 72%|███████▎ | 87/120 [00:01<00:00, 61.11it/s]
Testing DataLoader 0: 73%|███████▎ | 88/120 [00:01<00:00, 61.21it/s]
Testing DataLoader 0: 74%|███████▍ | 89/120 [00:01<00:00, 61.30it/s]
Testing DataLoader 0: 75%|███████▌ | 90/120 [00:01<00:00, 61.39it/s]
Testing DataLoader 0: 76%|███████▌ | 91/120 [00:01<00:00, 61.48it/s]
Testing DataLoader 0: 77%|███████▋ | 92/120 [00:01<00:00, 61.55it/s]
Testing DataLoader 0: 78%|███████▊ | 93/120 [00:01<00:00, 61.61it/s]
Testing DataLoader 0: 78%|███████▊ | 94/120 [00:01<00:00, 61.68it/s]
Testing DataLoader 0: 79%|███████▉ | 95/120 [00:01<00:00, 61.76it/s]
Testing DataLoader 0: 80%|████████ | 96/120 [00:01<00:00, 61.84it/s]
Testing DataLoader 0: 81%|████████ | 97/120 [00:01<00:00, 61.91it/s]
Testing DataLoader 0: 82%|████████▏ | 98/120 [00:01<00:00, 61.99it/s]
Testing DataLoader 0: 82%|████████▎ | 99/120 [00:01<00:00, 62.06it/s]
Testing DataLoader 0: 83%|████████▎ | 100/120 [00:01<00:00, 62.13it/s]
Testing DataLoader 0: 84%|████████▍ | 101/120 [00:01<00:00, 62.21it/s]
Testing DataLoader 0: 85%|████████▌ | 102/120 [00:01<00:00, 62.28it/s]
Testing DataLoader 0: 86%|████████▌ | 103/120 [00:01<00:00, 62.35it/s]
Testing DataLoader 0: 87%|████████▋ | 104/120 [00:01<00:00, 62.41it/s]
Testing DataLoader 0: 88%|████████▊ | 105/120 [00:01<00:00, 62.46it/s]
Testing DataLoader 0: 88%|████████▊ | 106/120 [00:01<00:00, 62.52it/s]
Testing DataLoader 0: 89%|████████▉ | 107/120 [00:01<00:00, 62.58it/s]
Testing DataLoader 0: 90%|█████████ | 108/120 [00:01<00:00, 62.64it/s]
Testing DataLoader 0: 91%|█████████ | 109/120 [00:01<00:00, 62.70it/s]
Testing DataLoader 0: 92%|█████████▏| 110/120 [00:01<00:00, 62.76it/s]
Testing DataLoader 0: 92%|█████████▎| 111/120 [00:01<00:00, 62.82it/s]
Testing DataLoader 0: 93%|█████████▎| 112/120 [00:01<00:00, 62.88it/s]
Testing DataLoader 0: 94%|█████████▍| 113/120 [00:01<00:00, 62.92it/s]
Testing DataLoader 0: 95%|█████████▌| 114/120 [00:01<00:00, 62.98it/s]
Testing DataLoader 0: 96%|█████████▌| 115/120 [00:01<00:00, 63.04it/s]
Testing DataLoader 0: 97%|█████████▋| 116/120 [00:01<00:00, 63.09it/s]
Testing DataLoader 0: 98%|█████████▊| 117/120 [00:01<00:00, 63.14it/s]
Testing DataLoader 0: 98%|█████████▊| 118/120 [00:01<00:00, 63.19it/s]
Testing DataLoader 0: 99%|█████████▉| 119/120 [00:01<00:00, 63.24it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:01<00:00, 63.31it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:02<00:00, 48.06it/s]
Test results saved to outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/save
Running step 2: NeuS
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 128, 'width': 128, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': True, 'requires_normal': False, 'random_camera': {'height': 128, 'width': 128, 'batch_size': 1, 'eval_height': 256, 'eval_width': 256, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-coarse-neus',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-coarse-neus',
'resume': None,
'seed': 0,
'system': {'stage': 'coarse', 'geometry_type': 'implicit-sdf', 'geometry': {'radius': 2.0, 'normal_type': 'finite_difference', 'sdf_bias': 'sphere', 'sdf_bias_params': 0.5, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378, 'start_level': 8, 'start_step': 2000, 'update_steps': 500}}, 'material_type': 'no-material', 'material': {'requires_normal': True}, 'background_type': 'solid-color-background', 'renderer_type': 'neus-volume-renderer', 'renderer': {'radius': 2.0, 'num_samples_per_ray': 512, 'cos_anneal_end_steps': 800, 'eval_chunk_size': 8192}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': 0, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.05, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_orient': 10.0, 'lambda_sparsity': 0.1, 'lambda_opaque': 0.1, 'lambda_clip': 0.0, 'lambda_eikonal': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'betas': [0.9, 0.99], 'eps': 1e-15}, 'params': {'geometry.encoding': {'lr': 0.01}, 'geometry.sdf_network': {'lr': 0.001}, 'geometry.feature_network': {'lr': 0.001}, 'renderer': {'lr': 0.001}}}, 'weights': 'outputs/dreamcraft3d-coarse-nerf/replicate_user@20240222-134035/ckpts/last.ckpt'},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-134422',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': '16-mixed'},
'trial_dir': 'outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422',
'trial_name': 'replicate_user@20240222-134422',
'use_timestamp': True}
Loading Deep Floyd ...
Couldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d74fb6-298d8d076e9d29f944cbc198;0e1233af-4a94-4850-a984-d00aa82f1e06)
Cannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Repo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..
Will try to load from local cache.
Loading pipeline components...: 0%| | 0/3 [00:00<?, ?it/s]
Loading pipeline components...: 33%|███▎ | 1/3 [00:00<00:00, 4.81it/s]
Loading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 12.46it/s]
Loaded Deep Floyd!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
Using 16bit Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name | Type | Params
----------------------------------------------------
0 | geometry | ImplicitSDF | 12.6 M
1 | material | NoMaterial | 0
2 | background | SolidColorBackground | 0
3 | renderer | NeuSVolumeRenderer | 1
----------------------------------------------------
12.6 M Trainable params
0 Non-trainable params
12.6 M Total params
50.417 Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/save
Training: | | 0/? [00:00<?, ?it/s]
Training: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 1/? [00:00<00:00, 8.63it/s]
Epoch 0: | | 1/? [00:00<00:00, 8.58it/s, train/loss=82.50]
Epoch 0: | | 2/? [00:00<00:00, 4.07it/s, train/loss=82.50]
Epoch 0: | | 2/? [00:00<00:00, 4.07it/s, train/loss=13.30]
Epoch 0: | | 3/? [00:00<00:00, 5.11it/s, train/loss=13.30]
Epoch 0: | | 3/? [00:00<00:00, 5.10it/s, train/loss=70.40]
Epoch 0: | | 4/? [00:00<00:00, 4.22it/s, train/loss=70.40]
Epoch 0: | | 4/? [00:00<00:00, 4.21it/s, train/loss=15.60]
Epoch 0: | | 5/? [00:01<00:00, 4.76it/s, train/loss=15.60]
Epoch 0: | | 5/? [00:01<00:00, 4.75it/s, train/loss=61.30]
Epoch 0: | | 6/? [00:01<00:00, 4.18it/s, train/loss=61.30]
Epoch 0: | | 6/? [00:01<00:00, 4.17it/s, train/loss=14.90]
Epoch 0: | | 7/? [00:01<00:00, 4.39it/s, train/loss=14.90]
Epoch 0: | | 7/? [00:01<00:00, 4.38it/s, train/loss=53.20]
Epoch 0: | | 8/? [00:02<00:00, 3.95it/s, train/loss=53.20]
Epoch 0: | | 8/? [00:02<00:00, 3.95it/s, train/loss=29.60]
Epoch 0: | | 9/? [00:02<00:00, 4.12it/s, train/loss=29.60]
Epoch 0: | | 9/? [00:02<00:00, 4.12it/s, train/loss=45.60]
Epoch 0: | | 10/? [00:02<00:00, 3.83it/s, train/loss=45.60]
Epoch 0: | | 10/? [00:02<00:00, 3.83it/s, train/loss=42.30]
Epoch 0: | | 11/? [00:02<00:00, 3.97it/s, train/loss=42.30]
Epoch 0: | | 11/? [00:02<00:00, 3.97it/s, train/loss=39.00]
Epoch 0: | | 12/? [00:03<00:00, 3.77it/s, train/loss=39.00]
Epoch 0: | | 12/? [00:03<00:00, 3.77it/s, train/loss=23.80]
Epoch 0: | | 13/? [00:03<00:00, 3.88it/s, train/loss=23.80]
Epoch 0: | | 13/? [00:03<00:00, 3.88it/s, train/loss=33.10]
Epoch 0: | | 14/? [00:03<00:00, 3.70it/s, train/loss=33.10]
Epoch 0: | | 14/? [00:03<00:00, 3.70it/s, train/loss=28.80]
Epoch 0: | | 15/? [00:03<00:00, 3.88it/s, train/loss=28.80]
Epoch 0: | | 15/? [00:03<00:00, 3.88it/s, train/loss=28.20]
Epoch 0: | | 16/? [00:04<00:00, 3.81it/s, train/loss=28.20]
Epoch 0: | | 16/? [00:04<00:00, 3.81it/s, train/loss=52.40]
Epoch 0: | | 17/? [00:04<00:00, 3.97it/s, train/loss=52.40]
Epoch 0: | | 17/? [00:04<00:00, 3.97it/s, train/loss=24.40]
Epoch 0: | | 18/? [00:04<00:00, 3.90it/s, train/loss=24.40]
Epoch 0: | | 18/? [00:04<00:00, 3.90it/s, train/loss=14.60]
Epoch 0: | | 19/? [00:04<00:00, 4.05it/s, train/loss=14.60]
Epoch 0: | | 19/? [00:04<00:00, 4.04it/s, train/loss=21.40]
Epoch 0: | | 20/? [00:05<00:00, 3.98it/s, train/loss=21.40]
Epoch 0: | | 20/? [00:05<00:00, 3.98it/s, train/loss=11.20]
Epoch 0: | | 21/? [00:05<00:00, 4.11it/s, train/loss=11.20]
Epoch 0: | | 21/? [00:05<00:00, 4.11it/s, train/loss=19.20]
Epoch 0: | | 22/? [00:05<00:00, 4.05it/s, train/loss=19.20]
Epoch 0: | | 22/? [00:05<00:00, 4.05it/s, train/loss=45.90]
Epoch 0: | | 23/? [00:05<00:00, 4.18it/s, train/loss=45.90]
Epoch 0: | | 23/? [00:05<00:00, 4.18it/s, train/loss=17.60]
Epoch 0: | | 24/? [00:05<00:00, 4.12it/s, train/loss=17.60]
Epoch 0: | | 24/? [00:05<00:00, 4.12it/s, train/loss=15.40]
Epoch 0: | | 25/? [00:05<00:00, 4.24it/s, train/loss=15.40]
Epoch 0: | | 25/? [00:05<00:00, 4.24it/s, train/loss=16.30]
Epoch 0: | | 26/? [00:06<00:00, 4.18it/s, train/loss=16.30]
Epoch 0: | | 26/? [00:06<00:00, 4.18it/s, train/loss=29.90]
Epoch 0: | | 27/? [00:06<00:00, 4.30it/s, train/loss=29.90]
Epoch 0: | | 27/? [00:06<00:00, 4.30it/s, train/loss=15.40]
Epoch 0: | | 28/? [00:06<00:00, 4.24it/s, train/loss=15.40]
Epoch 0: | | 28/? [00:06<00:00, 4.24it/s, train/loss=13.20]
Epoch 0: | | 29/? [00:06<00:00, 4.36it/s, train/loss=13.20]
Epoch 0: | | 29/? [00:06<00:00, 4.36it/s, train/loss=14.50]
Epoch 0: | | 30/? [00:06<00:00, 4.30it/s, train/loss=14.50]
Epoch 0: | | 30/? [00:06<00:00, 4.30it/s, train/loss=6.360]
Epoch 0: | | 31/? [00:07<00:00, 4.41it/s, train/loss=6.360]
Epoch 0: | | 31/? [00:07<00:00, 4.41it/s, train/loss=13.70]
Epoch 0: | | 32/? [00:07<00:00, 4.36it/s, train/loss=13.70]
Epoch 0: | | 32/? [00:07<00:00, 4.36it/s, train/loss=14.30]
Epoch 0: | | 33/? [00:07<00:00, 4.41it/s, train/loss=14.30]
Epoch 0: | | 33/? [00:07<00:00, 4.41it/s, train/loss=13.00]
Epoch 0: | | 34/? [00:07<00:00, 4.36it/s, train/loss=13.00]
Epoch 0: | | 34/? [00:07<00:00, 4.36it/s, train/loss=12.60]
Epoch 0: | | 35/? [00:07<00:00, 4.46it/s, train/loss=12.60]
Epoch 0: | | 35/? [00:07<00:00, 4.45it/s, train/loss=12.40]
Epoch 0: | | 36/? [00:08<00:00, 4.41it/s, train/loss=12.40]
Epoch 0: | | 36/? [00:08<00:00, 4.41it/s, train/loss=16.80]
Epoch 0: | | 37/? [00:08<00:00, 4.50it/s, train/loss=16.80]
Epoch 0: | | 37/? [00:08<00:00, 4.50it/s, train/loss=11.90]
Epoch 0: | | 38/? [00:08<00:00, 4.45it/s, train/loss=11.90]
Epoch 0: | | 38/? [00:08<00:00, 4.45it/s, train/loss=52.20]
Epoch 0: | | 39/? [00:08<00:00, 4.54it/s, train/loss=52.20]
Epoch 0: | | 39/? [00:08<00:00, 4.54it/s, train/loss=11.30]
Epoch 0: | | 40/? [00:08<00:00, 4.50it/s, train/loss=11.30]
Epoch 0: | | 40/? [00:08<00:00, 4.49it/s, train/loss=16.60]
Epoch 0: | | 41/? [00:08<00:00, 4.58it/s, train/loss=16.60]
Epoch 0: | | 41/? [00:08<00:00, 4.58it/s, train/loss=10.90]
Epoch 0: | | 42/? [00:09<00:00, 4.54it/s, train/loss=10.90]
Epoch 0: | | 42/? [00:09<00:00, 4.54it/s, train/loss=24.50]
Epoch 0: | | 43/? [00:09<00:00, 4.61it/s, train/loss=24.50]
Epoch 0: | | 43/? [00:09<00:00, 4.61it/s, train/loss=10.50]
Epoch 0: | | 44/? [00:09<00:00, 4.57it/s, train/loss=10.50]
Epoch 0: | | 44/? [00:09<00:00, 4.57it/s, train/loss=35.50]
Epoch 0: | | 45/? [00:09<00:00, 4.65it/s, train/loss=35.50]
Epoch 0: | | 45/? [00:09<00:00, 4.65it/s, train/loss=10.10]
Epoch 0: | | 46/? [00:09<00:00, 4.61it/s, train/loss=10.10]
Epoch 0: | | 46/? [00:09<00:00, 4.61it/s, train/loss=26.20]
Epoch 0: | | 47/? [00:10<00:00, 4.68it/s, train/loss=26.20]
Epoch 0: | | 47/? [00:10<00:00, 4.68it/s, train/loss=9.790]
Epoch 0: | | 48/? [00:10<00:00, 4.64it/s, train/loss=9.790]
Epoch 0: | | 48/? [00:10<00:00, 4.64it/s, train/loss=14.20]
Epoch 0: | | 49/? [00:10<00:00, 4.72it/s, train/loss=14.20]
Epoch 0: | | 49/? [00:10<00:00, 4.72it/s, train/loss=9.460]
Epoch 0: | | 50/? [00:10<00:00, 4.68it/s, train/loss=9.460]
Epoch 0: | | 50/? [00:10<00:00, 4.68it/s, train/loss=31.70]
Epoch 0: | | 51/? [00:10<00:00, 4.75it/s, train/loss=31.70]
Epoch 0: | | 51/? [00:10<00:00, 4.75it/s, train/loss=9.160]
Epoch 0: | | 52/? [00:11<00:00, 4.71it/s, train/loss=9.160]
Epoch 0: | | 52/? [00:11<00:00, 4.71it/s, train/loss=24.50]
Epoch 0: | | 53/? [00:11<00:00, 4.78it/s, train/loss=24.50]
Epoch 0: | | 53/? [00:11<00:00, 4.78it/s, train/loss=8.860]
Epoch 0: | | 54/? [00:11<00:00, 4.74it/s, train/loss=8.860]
Epoch 0: | | 54/? [00:11<00:00, 4.74it/s, train/loss=22.90]
Epoch 0: | | 55/? [00:11<00:00, 4.81it/s, train/loss=22.90]
Epoch 0: | | 55/? [00:11<00:00, 4.81it/s, train/loss=8.610]
Epoch 0: | | 56/? [00:11<00:00, 4.77it/s, train/loss=8.610]
Epoch 0: | | 56/? [00:11<00:00, 4.77it/s, train/loss=50.00]
Epoch 0: | | 57/? [00:11<00:00, 4.83it/s, train/loss=50.00]
Epoch 0: | | 57/? [00:11<00:00, 4.83it/s, train/loss=8.320]
Epoch 0: | | 58/? [00:12<00:00, 4.79it/s, train/loss=8.320]
Epoch 0: | | 58/? [00:12<00:00, 4.79it/s, train/loss=10.20]
Epoch 0: | | 59/? [00:12<00:00, 4.86it/s, train/loss=10.20]
Epoch 0: | | 59/? [00:12<00:00, 4.86it/s, train/loss=8.120]
Epoch 0: | | 60/? [00:12<00:00, 4.82it/s, train/loss=8.120]
Epoch 0: | | 60/? [00:12<00:00, 4.82it/s, train/loss=25.00]
Epoch 0: | | 61/? [00:12<00:00, 4.88it/s, train/loss=25.00]
Epoch 0: | | 61/? [00:12<00:00, 4.88it/s, train/loss=7.890]
Epoch 0: | | 62/? [00:12<00:00, 4.85it/s, train/loss=7.890]
Epoch 0: | | 62/? [00:12<00:00, 4.85it/s, train/loss=39.10]
Epoch 0: | | 63/? [00:12<00:00, 4.91it/s, train/loss=39.10]
Epoch 0: | | 63/? [00:12<00:00, 4.91it/s, train/loss=7.680]
Epoch 0: | | 64/? [00:13<00:00, 4.87it/s, train/loss=7.680]
Epoch 0: | | 64/? [00:13<00:00, 4.87it/s, train/loss=19.80]
Epoch 0: | | 65/? [00:13<00:00, 4.93it/s, train/loss=19.80]
Epoch 0: | | 65/? [00:13<00:00, 4.93it/s, train/loss=7.520]
Epoch 0: | | 66/? [00:13<00:00, 4.89it/s, train/loss=7.520]
Epoch 0: | | 66/? [00:13<00:00, 4.89it/s, train/loss=25.30]
Epoch 0: | | 67/? [00:13<00:00, 4.95it/s, train/loss=25.30]
Epoch 0: | | 67/? [00:13<00:00, 4.95it/s, train/loss=7.340]
Epoch 0: | | 68/? [00:13<00:00, 4.92it/s, train/loss=7.340]
Epoch 0: | | 68/? [00:13<00:00, 4.92it/s, train/loss=26.40]
Epoch 0: | | 69/? [00:13<00:00, 4.97it/s, train/loss=26.40]
Epoch 0: | | 69/? [00:13<00:00, 4.97it/s, train/loss=7.160]
Epoch 0: | | 70/? [00:14<00:00, 4.94it/s, train/loss=7.160]
Epoch 0: | | 70/? [00:14<00:00, 4.94it/s, train/loss=28.30]
Epoch 0: | | 71/? [00:14<00:00, 4.99it/s, train/loss=28.30]
Epoch 0: | | 71/? [00:14<00:00, 4.99it/s, train/loss=6.960]
Epoch 0: | | 72/? [00:14<00:00, 4.96it/s, train/loss=6.960]
Epoch 0: | | 72/? [00:14<00:00, 4.96it/s, train/loss=19.70]
Epoch 0: | | 73/? [00:14<00:00, 5.01it/s, train/loss=19.70]
Epoch 0: | | 73/? [00:14<00:00, 5.01it/s, train/loss=6.810]
Epoch 0: | | 74/? [00:14<00:00, 4.98it/s, train/loss=6.810]
Epoch 0: | | 74/? [00:14<00:00, 4.98it/s, train/loss=25.40]
Epoch 0: | | 75/? [00:14<00:00, 5.03it/s, train/loss=25.40]
Epoch 0: | | 75/? [00:14<00:00, 5.03it/s, train/loss=6.630]
Epoch 0: | | 76/? [00:15<00:00, 5.00it/s, train/loss=6.630]
Epoch 0: | | 76/? [00:15<00:00, 5.00it/s, train/loss=38.60]
Epoch 0: | | 77/? [00:15<00:00, 5.05it/s, train/loss=38.60]
Epoch 0: | | 77/? [00:15<00:00, 5.05it/s, train/loss=6.480]
Epoch 0: | | 78/? [00:15<00:00, 5.02it/s, train/loss=6.480]
Epoch 0: | | 78/? [00:15<00:00, 5.02it/s, train/loss=13.70]
Epoch 0: | | 79/? [00:15<00:00, 5.07it/s, train/loss=13.70]
Epoch 0: | | 79/? [00:15<00:00, 5.07it/s, train/loss=6.330]
Epoch 0: | | 80/? [00:15<00:00, 5.04it/s, train/loss=6.330]
Epoch 0: | | 80/? [00:15<00:00, 5.03it/s, train/loss=32.80]
Epoch 0: | | 81/? [00:15<00:00, 5.08it/s, train/loss=32.80]
Epoch 0: | | 81/? [00:15<00:00, 5.08it/s, train/loss=6.160]
Epoch 0: | | 82/? [00:16<00:00, 5.05it/s, train/loss=6.160]
Epoch 0: | | 82/? [00:16<00:00, 5.05it/s, train/loss=79.20]
Epoch 0: | | 83/? [00:16<00:00, 5.10it/s, train/loss=79.20]
Epoch 0: | | 83/? [00:16<00:00, 5.10it/s, train/loss=6.010]
Epoch 0: | | 84/? [00:16<00:00, 5.07it/s, train/loss=6.010]
Epoch 0: | | 84/? [00:16<00:00, 5.07it/s, train/loss=9.970]
Epoch 0: | | 85/? [00:16<00:00, 5.11it/s, train/loss=9.970]
Epoch 0: | | 85/? [00:16<00:00, 5.11it/s, train/loss=6.020]
Epoch 0: | | 86/? [00:16<00:00, 5.08it/s, train/loss=6.020]
Epoch 0: | | 86/? [00:16<00:00, 5.08it/s, train/loss=9.380]
Epoch 0: | | 87/? [00:16<00:00, 5.13it/s, train/loss=9.380]
Epoch 0: | | 87/? [00:16<00:00, 5.13it/s, train/loss=5.970]
Epoch 0: | | 88/? [00:17<00:00, 5.10it/s, train/loss=5.970]
Epoch 0: | | 88/? [00:17<00:00, 5.10it/s, train/loss=43.40]
Epoch 0: | | 89/? [00:17<00:00, 5.14it/s, train/loss=43.40]
Epoch 0: | | 89/? [00:17<00:00, 5.14it/s, train/loss=5.850]
Epoch 0: | | 90/? [00:17<00:00, 5.11it/s, train/loss=5.850]
Epoch 0: | | 90/? [00:17<00:00, 5.11it/s, train/loss=31.80]
Epoch 0: | | 91/? [00:17<00:00, 5.16it/s, train/loss=31.80]
Epoch 0: | | 91/? [00:17<00:00, 5.16it/s, train/loss=5.750]
Epoch 0: | | 92/? [00:17<00:00, 5.13it/s, train/loss=5.750]
Epoch 0: | | 92/? [00:17<00:00, 5.13it/s, train/loss=30.60]
Epoch 0: | | 93/? [00:17<00:00, 5.17it/s, train/loss=30.60]
Epoch 0: | | 93/? [00:17<00:00, 5.17it/s, train/loss=5.680]
Epoch 0: | | 94/? [00:18<00:00, 5.14it/s, train/loss=5.680]
Epoch 0: | | 94/? [00:18<00:00, 5.14it/s, train/loss=7.830]
Epoch 0: | | 95/? [00:18<00:00, 5.18it/s, train/loss=7.830]
Epoch 0: | | 95/? [00:18<00:00, 5.18it/s, train/loss=5.570]
Epoch 0: | | 96/? [00:18<00:00, 5.16it/s, train/loss=5.570]
Epoch 0: | | 96/? [00:18<00:00, 5.16it/s, train/loss=74.70]
Epoch 0: | | 97/? [00:18<00:00, 5.20it/s, train/loss=74.70]
Epoch 0: | | 97/? [00:18<00:00, 5.20it/s, train/loss=5.550]
Epoch 0: | | 98/? [00:18<00:00, 5.17it/s, train/loss=5.550]
Epoch 0: | | 98/? [00:18<00:00, 5.17it/s, train/loss=28.10]
Epoch 0: | | 99/? [00:18<00:00, 5.21it/s, train/loss=28.10]
Epoch 0: | | 99/? [00:18<00:00, 5.21it/s, train/loss=5.500]
Epoch 0: | | 100/? [00:19<00:00, 5.18it/s, train/loss=5.500]
Epoch 0: | | 100/? [00:19<00:00, 5.18it/s, train/loss=26.30]
Epoch 0: | | 101/? [00:19<00:00, 5.22it/s, train/loss=26.30]
Epoch 0: | | 101/? [00:19<00:00, 5.22it/s, train/loss=5.460]
Epoch 0: | | 102/? [00:19<00:00, 5.20it/s, train/loss=5.460]
Epoch 0: | | 102/? [00:19<00:00, 5.20it/s, train/loss=18.60]
Epoch 0: | | 103/? [00:19<00:00, 5.24it/s, train/loss=18.60]
Epoch 0: | | 103/? [00:19<00:00, 5.24it/s, train/loss=5.390]
Epoch 0: | | 104/? [00:19<00:00, 5.21it/s, train/loss=5.390]
Epoch 0: | | 104/? [00:19<00:00, 5.21it/s, train/loss=35.60]
Epoch 0: | | 105/? [00:20<00:00, 5.25it/s, train/loss=35.60]
Epoch 0: | | 105/? [00:20<00:00, 5.25it/s, train/loss=5.390]
Epoch 0: | | 106/? [00:20<00:00, 5.22it/s, train/loss=5.390]
Epoch 0: | | 106/? [00:20<00:00, 5.22it/s, train/loss=27.10]
Epoch 0: | | 107/? [00:20<00:00, 5.26it/s, train/loss=27.10]
Epoch 0: | | 107/? [00:20<00:00, 5.26it/s, train/loss=5.360]
Epoch 0: | | 108/? [00:20<00:00, 5.23it/s, train/loss=5.360]
Epoch 0: | | 108/? [00:20<00:00, 5.23it/s, train/loss=19.40]
Epoch 0: | | 109/? [00:20<00:00, 5.27it/s, train/loss=19.40]
Epoch 0: | | 109/? [00:20<00:00, 5.27it/s, train/loss=5.320]
Epoch 0: | | 110/? [00:20<00:00, 5.24it/s, train/loss=5.320]
Epoch 0: | | 110/? [00:20<00:00, 5.24it/s, train/loss=11.00]
Epoch 0: | | 111/? [00:21<00:00, 5.28it/s, train/loss=11.00]
Epoch 0: | | 111/? [00:21<00:00, 5.28it/s, train/loss=5.210]
Epoch 0: | | 112/? [00:21<00:00, 5.25it/s, train/loss=5.210]
Epoch 0: | | 112/? [00:21<00:00, 5.25it/s, train/loss=31.30]
Epoch 0: | | 113/? [00:21<00:00, 5.29it/s, train/loss=31.30]
Epoch 0: | | 113/? [00:21<00:00, 5.29it/s, train/loss=5.080]
Epoch 0: | | 114/? [00:21<00:00, 5.27it/s, train/loss=5.080]
Epoch 0: | | 114/? [00:21<00:00, 5.26it/s, train/loss=13.40]
Epoch 0: | | 115/? [00:21<00:00, 5.30it/s, train/loss=13.40]
Epoch 0: | | 115/? [00:21<00:00, 5.30it/s, train/loss=5.000]
Epoch 0: | | 116/? [00:21<00:00, 5.28it/s, train/loss=5.000]
Epoch 0: | | 116/? [00:21<00:00, 5.28it/s, train/loss=21.70]
Epoch 0: | | 117/? [00:22<00:00, 5.31it/s, train/loss=21.70]
Epoch 0: | | 117/? [00:22<00:00, 5.31it/s, train/loss=4.900]
Epoch 0: | | 118/? [00:22<00:00, 5.29it/s, train/loss=4.900]
Epoch 0: | | 118/? [00:22<00:00, 5.29it/s, train/loss=29.80]
Epoch 0: | | 119/? [00:22<00:00, 5.32it/s, train/loss=29.80]
Epoch 0: | | 119/? [00:22<00:00, 5.32it/s, train/loss=4.820]
Epoch 0: | | 120/? [00:22<00:00, 5.30it/s, train/loss=4.820]
Epoch 0: | | 120/? [00:22<00:00, 5.30it/s, train/loss=16.00]
Epoch 0: | | 121/? [00:22<00:00, 5.33it/s, train/loss=16.00]
Epoch 0: | | 121/? [00:22<00:00, 5.33it/s, train/loss=4.760]
Epoch 0: | | 122/? [00:22<00:00, 5.31it/s, train/loss=4.760]
Epoch 0: | | 122/? [00:22<00:00, 5.31it/s, train/loss=9.140]
Epoch 0: | | 123/? [00:23<00:00, 5.34it/s, train/loss=9.140]
Epoch 0: | | 123/? [00:23<00:00, 5.34it/s, train/loss=4.590]
Epoch 0: | | 124/? [00:23<00:00, 5.31it/s, train/loss=4.590]
Epoch 0: | | 124/? [00:23<00:00, 5.31it/s, train/loss=15.00]
Epoch 0: | | 125/? [00:23<00:00, 5.35it/s, train/loss=15.00]
Epoch 0: | | 125/? [00:23<00:00, 5.35it/s, train/loss=4.540]
Epoch 0: | | 126/? [00:23<00:00, 5.33it/s, train/loss=4.540]
Epoch 0: | | 126/? [00:23<00:00, 5.32it/s, train/loss=29.10]
Epoch 0: | | 127/? [00:23<00:00, 5.36it/s, train/loss=29.10]
Epoch 0: | | 127/? [00:23<00:00, 5.36it/s, train/loss=4.470]
Epoch 0: | | 128/? [00:23<00:00, 5.33it/s, train/loss=4.470]
Epoch 0: | | 128/? [00:23<00:00, 5.33it/s, train/loss=14.60]
Epoch 0: | | 129/? [00:24<00:00, 5.37it/s, train/loss=14.60]
Epoch 0: | | 129/? [00:24<00:00, 5.37it/s, train/loss=4.440]
Epoch 0: | | 130/? [00:24<00:00, 5.34it/s, train/loss=4.440]
Epoch 0: | | 130/? [00:24<00:00, 5.34it/s, train/loss=53.50]
Epoch 0: | | 131/? [00:24<00:00, 5.38it/s, train/loss=53.50]
Epoch 0: | | 131/? [00:24<00:00, 5.38it/s, train/loss=4.370]
Epoch 0: | | 132/? [00:24<00:00, 5.35it/s, train/loss=4.370]
Epoch 0: | | 132/? [00:24<00:00, 5.35it/s, train/loss=21.30]
Epoch 0: | | 133/? [00:24<00:00, 5.39it/s, train/loss=21.30]
Epoch 0: | | 133/? [00:24<00:00, 5.38it/s, train/loss=4.300]
Epoch 0: | | 134/? [00:24<00:00, 5.36it/s, train/loss=4.300]
Epoch 0: | | 134/? [00:24<00:00, 5.36it/s, train/loss=41.60]
Epoch 0: | | 135/? [00:25<00:00, 5.39it/s, train/loss=41.60]
Epoch 0: | | 135/? [00:25<00:00, 5.39it/s, train/loss=4.300]
Epoch 0: | | 136/? [00:25<00:00, 5.37it/s, train/loss=4.300]
Epoch 0: | | 136/? [00:25<00:00, 5.37it/s, train/loss=56.40]
Epoch 0: | | 137/? [00:25<00:00, 5.40it/s, train/loss=56.40]
Epoch 0: | | 137/? [00:25<00:00, 5.40it/s, train/loss=4.250]
Epoch 0: | | 138/? [00:25<00:00, 5.38it/s, train/loss=4.250]
Epoch 0: | | 138/? [00:25<00:00, 5.38it/s, train/loss=27.90]
Epoch 0: | | 139/? [00:25<00:00, 5.41it/s, train/loss=27.90]
Epoch 0: | | 139/? [00:25<00:00, 5.41it/s, train/loss=4.200]
Epoch 0: | | 140/? [00:25<00:00, 5.39it/s, train/loss=4.200]
Epoch 0: | | 140/? [00:25<00:00, 5.39it/s, train/loss=23.60]
Epoch 0: | | 141/? [00:26<00:00, 5.42it/s, train/loss=23.60]
Epoch 0: | | 141/? [00:26<00:00, 5.42it/s, train/loss=4.210]
Epoch 0: | | 142/? [00:26<00:00, 5.39it/s, train/loss=4.210]
Epoch 0: | | 142/? [00:26<00:00, 5.39it/s, train/loss=34.30]
Epoch 0: | | 143/? [00:26<00:00, 5.42it/s, train/loss=34.30]
Epoch 0: | | 143/? [00:26<00:00, 5.42it/s, train/loss=4.270]
Epoch 0: | | 144/? [00:26<00:00, 5.40it/s, train/loss=4.270]
Epoch 0: | | 144/? [00:26<00:00, 5.40it/s, train/loss=11.00]
Epoch 0: | | 145/? [00:26<00:00, 5.43it/s, train/loss=11.00]
Epoch 0: | | 145/? [00:26<00:00, 5.43it/s, train/loss=4.260]
Epoch 0: | | 146/? [00:26<00:00, 5.41it/s, train/loss=4.260]
Epoch 0: | | 146/? [00:26<00:00, 5.41it/s, train/loss=16.60]
Epoch 0: | | 147/? [00:27<00:00, 5.44it/s, train/loss=16.60]
Epoch 0: | | 147/? [00:27<00:00, 5.44it/s, train/loss=4.250]
Epoch 0: | | 148/? [00:27<00:00, 5.42it/s, train/loss=4.250]
Epoch 0: | | 148/? [00:27<00:00, 5.42it/s, train/loss=56.10]
Epoch 0: | | 149/? [00:27<00:00, 5.45it/s, train/loss=56.10]
Epoch 0: | | 149/? [00:27<00:00, 5.45it/s, train/loss=4.270]
Epoch 0: | | 150/? [00:27<00:00, 5.43it/s, train/loss=4.270]
Epoch 0: | | 150/? [00:27<00:00, 5.43it/s, train/loss=17.70]
Epoch 0: | | 151/? [00:27<00:00, 5.46it/s, train/loss=17.70]
Epoch 0: | | 151/? [00:27<00:00, 5.46it/s, train/loss=4.270]
Epoch 0: | | 152/? [00:27<00:00, 5.44it/s, train/loss=4.270]
Epoch 0: | | 152/? [00:27<00:00, 5.44it/s, train/loss=29.20]
Epoch 0: | | 153/? [00:28<00:00, 5.46it/s, train/loss=29.20]
Epoch 0: | | 153/? [00:28<00:00, 5.46it/s, train/loss=4.220]
Epoch 0: | | 154/? [00:28<00:00, 5.44it/s, train/loss=4.220]
Epoch 0: | | 154/? [00:28<00:00, 5.44it/s, train/loss=24.70]
Epoch 0: | | 155/? [00:28<00:00, 5.47it/s, train/loss=24.70]
Epoch 0: | | 155/? [00:28<00:00, 5.47it/s, train/loss=4.170]
Epoch 0: | | 156/? [00:28<00:00, 5.45it/s, train/loss=4.170]
Epoch 0: | | 156/? [00:28<00:00, 5.45it/s, train/loss=32.10]
Epoch 0: | | 157/? [00:28<00:00, 5.48it/s, train/loss=32.10]
Epoch 0: | | 157/? [00:28<00:00, 5.48it/s, train/loss=4.130]
Epoch 0: | | 158/? [00:28<00:00, 5.46it/s, train/loss=4.130]
Epoch 0: | | 158/? [00:28<00:00, 5.46it/s, train/loss=50.40]
Epoch 0: | | 159/? [00:29<00:00, 5.47it/s, train/loss=50.40]
Epoch 0: | | 159/? [00:29<00:00, 5.47it/s, train/loss=4.160]
Epoch 0: | | 160/? [00:29<00:00, 5.45it/s, train/loss=4.160]
Epoch 0: | | 160/? [00:29<00:00, 5.45it/s, train/loss=39.00]
Epoch 0: | | 161/? [00:29<00:00, 5.47it/s, train/loss=39.00]
Epoch 0: | | 161/? [00:29<00:00, 5.47it/s, train/loss=4.080]
Epoch 0: | | 162/? [00:29<00:00, 5.45it/s, train/loss=4.080]
Epoch 0: | | 162/? [00:29<00:00, 5.45it/s, train/loss=23.90]
Epoch 0: | | 163/? [00:29<00:00, 5.48it/s, train/loss=23.90]
Epoch 0: | | 163/? [00:29<00:00, 5.48it/s, train/loss=4.140]
Epoch 0: | | 164/? [00:30<00:00, 5.46it/s, train/loss=4.140]
Epoch 0: | | 164/? [00:30<00:00, 5.46it/s, train/loss=20.70]
Epoch 0: | | 165/? [00:30<00:00, 5.48it/s, train/loss=20.70]
Epoch 0: | | 165/? [00:30<00:00, 5.48it/s, train/loss=3.990]
Epoch 0: | | 166/? [00:30<00:00, 5.46it/s, train/loss=3.990]
Epoch 0: | | 166/? [00:30<00:00, 5.46it/s, train/loss=46.60]
Epoch 0: | | 167/? [00:30<00:00, 5.49it/s, train/loss=46.60]
Epoch 0: | | 167/? [00:30<00:00, 5.49it/s, train/loss=4.030]
Epoch 0: | | 168/? [00:30<00:00, 5.47it/s, train/loss=4.030]
Epoch 0: | | 168/? [00:30<00:00, 5.47it/s, train/loss=31.20]
Epoch 0: | | 169/? [00:30<00:00, 5.50it/s, train/loss=31.20]
Epoch 0: | | 169/? [00:30<00:00, 5.50it/s, train/loss=3.920]
Epoch 0: | | 170/? [00:31<00:00, 5.48it/s, train/loss=3.920]
Epoch 0: | | 170/? [00:31<00:00, 5.48it/s, train/loss=24.30]
Epoch 0: | | 171/? [00:31<00:00, 5.49it/s, train/loss=24.30]
Epoch 0: | | 171/? [00:31<00:00, 5.49it/s, train/loss=3.860]
Epoch 0: | | 172/? [00:31<00:00, 5.47it/s, train/loss=3.860]
Epoch 0: | | 172/? [00:31<00:00, 5.47it/s, train/loss=48.80]
Epoch 0: | | 173/? [00:31<00:00, 5.49it/s, train/loss=48.80]
Epoch 0: | | 173/? [00:31<00:00, 5.49it/s, train/loss=3.870]
Epoch 0: | | 174/? [00:31<00:00, 5.45it/s, train/loss=3.870]
Epoch 0: | | 174/? [00:31<00:00, 5.45it/s, train/loss=29.00]
Epoch 0: | | 175/? [00:31<00:00, 5.47it/s, train/loss=29.00]
Epoch 0: | | 175/? [00:31<00:00, 5.47it/s, train/loss=3.860]
Epoch 0: | | 176/? [00:32<00:00, 5.45it/s, train/loss=3.860]
Epoch 0: | | 176/? [00:32<00:00, 5.45it/s, train/loss=28.10]
Epoch 0: | | 177/? [00:32<00:00, 5.47it/s, train/loss=28.10]
Epoch 0: | | 177/? [00:32<00:00, 5.47it/s, train/loss=3.830]
Epoch 0: | | 178/? [00:32<00:00, 5.45it/s, train/loss=3.830]
Epoch 0: | | 178/? [00:32<00:00, 5.45it/s, train/loss=29.80]
Epoch 0: | | 179/? [00:32<00:00, 5.48it/s, train/loss=29.80]
Epoch 0: | | 179/? [00:32<00:00, 5.48it/s, train/loss=3.810]
Epoch 0: | | 180/? [00:32<00:00, 5.46it/s, train/loss=3.810]
Epoch 0: | | 180/? [00:32<00:00, 5.46it/s, train/loss=22.60]
Epoch 0: | | 181/? [00:32<00:00, 5.49it/s, train/loss=22.60]
Epoch 0: | | 181/? [00:32<00:00, 5.49it/s, train/loss=3.810]
Epoch 0: | | 182/? [00:33<00:00, 5.47it/s, train/loss=3.810]
Epoch 0: | | 182/? [00:33<00:00, 5.47it/s, train/loss=17.40]
Epoch 0: | | 183/? [00:33<00:00, 5.49it/s, train/loss=17.40]
Epoch 0: | | 183/? [00:33<00:00, 5.49it/s, train/loss=3.830]
Epoch 0: | | 184/? [00:33<00:00, 5.47it/s, train/loss=3.830]
Epoch 0: | | 184/? [00:33<00:00, 5.47it/s, train/loss=26.80]
Epoch 0: | | 185/? [00:33<00:00, 5.50it/s, train/loss=26.80]
Epoch 0: | | 185/? [00:33<00:00, 5.50it/s, train/loss=3.770]
Epoch 0: | | 186/? [00:33<00:00, 5.48it/s, train/loss=3.770]
Epoch 0: | | 186/? [00:33<00:00, 5.48it/s, train/loss=24.20]
Epoch 0: | | 187/? [00:33<00:00, 5.51it/s, train/loss=24.20]
Epoch 0: | | 187/? [00:33<00:00, 5.51it/s, train/loss=3.750]
Epoch 0: | | 188/? [00:34<00:00, 5.49it/s, train/loss=3.750]
Epoch 0: | | 188/? [00:34<00:00, 5.49it/s, train/loss=24.00]
Epoch 0: | | 189/? [00:34<00:00, 5.51it/s, train/loss=24.00]
Epoch 0: | | 189/? [00:34<00:00, 5.51it/s, train/loss=3.690]
Epoch 0: | | 190/? [00:34<00:00, 5.50it/s, train/loss=3.690]
Epoch 0: | | 190/? [00:34<00:00, 5.50it/s, train/loss=21.50]
Epoch 0: | | 191/? [00:34<00:00, 5.52it/s, train/loss=21.50]
Epoch 0: | | 191/? [00:34<00:00, 5.52it/s, train/loss=3.680]
Epoch 0: | | 192/? [00:34<00:00, 5.50it/s, train/loss=3.680]
Epoch 0: | | 192/? [00:34<00:00, 5.50it/s, train/loss=36.10]
Epoch 0: | | 193/? [00:34<00:00, 5.53it/s, train/loss=36.10]
Epoch 0: | | 193/? [00:34<00:00, 5.52it/s, train/loss=3.640]
Epoch 0: | | 194/? [00:35<00:00, 5.51it/s, train/loss=3.640]
Epoch 0: | | 194/? [00:35<00:00, 5.51it/s, train/loss=13.30]
Epoch 0: | | 195/? [00:35<00:00, 5.53it/s, train/loss=13.30]
Epoch 0: | | 195/? [00:35<00:00, 5.53it/s, train/loss=3.600]
Epoch 0: | | 196/? [00:35<00:00, 5.51it/s, train/loss=3.600]
Epoch 0: | | 196/? [00:35<00:00, 5.51it/s, train/loss=33.60]
Epoch 0: | | 197/? [00:35<00:00, 5.53it/s, train/loss=33.60]
Epoch 0: | | 197/? [00:35<00:00, 5.52it/s, train/loss=3.520]
Epoch 0: | | 198/? [00:36<00:00, 5.50it/s, train/loss=3.520]
Epoch 0: | | 198/? [00:36<00:00, 5.50it/s, train/loss=35.50]
Epoch 0: | | 199/? [00:36<00:00, 5.51it/s, train/loss=35.50]
Epoch 0: | | 199/? [00:36<00:00, 5.51it/s, train/loss=3.470]
Epoch 0: | | 200/? [00:36<00:00, 5.48it/s, train/loss=3.470]
Epoch 0: | | 200/? [00:36<00:00, 5.48it/s, train/loss=14.60]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:10, 3.63it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:10, 3.65it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:10, 3.66it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:01<00:09, 3.65it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:01<00:09, 3.66it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:01<00:09, 3.66it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:01<00:08, 3.68it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:02<00:08, 3.67it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:02<00:08, 3.68it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:02<00:08, 3.68it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:02<00:07, 3.69it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:03<00:07, 3.69it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:03<00:07, 3.70it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:03<00:07, 3.70it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:04<00:06, 3.71it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:04<00:06, 3.71it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:04<00:06, 3.72it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:04<00:05, 3.72it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:05<00:05, 3.72it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:05<00:05, 3.73it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:05<00:05, 3.73it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:05<00:04, 3.73it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:06<00:04, 3.73it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:06<00:04, 3.73it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:06<00:04, 3.74it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:06<00:03, 3.74it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:07<00:03, 3.74it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:07<00:03, 3.75it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:07<00:02, 3.75it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:07<00:02, 3.75it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:08<00:02, 3.76it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:08<00:02, 3.76it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:08<00:01, 3.76it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:09<00:01, 3.77it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:09<00:01, 3.77it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:09<00:01, 3.78it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:09<00:00, 3.78it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:10<00:00, 3.79it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:10<00:00, 3.78it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:10<00:00, 3.78it/s][A
[A
Epoch 0: | | 200/? [00:47<00:00, 4.18it/s, train/loss=14.60]
Epoch 0: | | 201/? [00:48<00:00, 4.17it/s, train/loss=14.60]
Epoch 0: | | 201/? [00:48<00:00, 4.17it/s, train/loss=3.450]
Epoch 0: | | 202/? [00:48<00:00, 4.16it/s, train/loss=3.450]
Epoch 0: | | 202/? [00:48<00:00, 4.16it/s, train/loss=29.70]
Epoch 0: | | 203/? [00:48<00:00, 4.17it/s, train/loss=29.70]
Epoch 0: | | 203/? [00:48<00:00, 4.17it/s, train/loss=3.370]
Epoch 0: | | 204/? [00:49<00:00, 4.16it/s, train/loss=3.370]
Epoch 0: | | 204/? [00:49<00:00, 4.16it/s, train/loss=36.30]
Epoch 0: | | 205/? [00:49<00:00, 4.17it/s, train/loss=36.30]
Epoch 0: | | 205/? [00:49<00:00, 4.17it/s, train/loss=3.240]
Epoch 0: | | 206/? [00:49<00:00, 4.17it/s, train/loss=3.240]
Epoch 0: | | 206/? [00:49<00:00, 4.17it/s, train/loss=20.20]
Epoch 0: | | 207/? [00:49<00:00, 4.19it/s, train/loss=20.20]
Epoch 0: | | 207/? [00:49<00:00, 4.19it/s, train/loss=3.100]
Epoch 0: | | 208/? [00:49<00:00, 4.18it/s, train/loss=3.100]
Epoch 0: | | 208/? [00:49<00:00, 4.18it/s, train/loss=30.20]
Epoch 0: | | 209/? [00:49<00:00, 4.20it/s, train/loss=30.20]
Epoch 0: | | 209/? [00:49<00:00, 4.20it/s, train/loss=2.980]
Epoch 0: | | 210/? [00:50<00:00, 4.20it/s, train/loss=2.980]
Epoch 0: | | 210/? [00:50<00:00, 4.20it/s, train/loss=22.10]
Epoch 0: | | 211/? [00:50<00:00, 4.21it/s, train/loss=22.10]
Epoch 0: | | 211/? [00:50<00:00, 4.21it/s, train/loss=2.870]
Epoch 0: | | 212/? [00:50<00:00, 4.21it/s, train/loss=2.870]
Epoch 0: | | 212/? [00:50<00:00, 4.21it/s, train/loss=31.50]
Epoch 0: | | 213/? [00:50<00:00, 4.22it/s, train/loss=31.50]
Epoch 0: | | 213/? [00:50<00:00, 4.22it/s, train/loss=2.790]
Epoch 0: | | 214/? [00:50<00:00, 4.22it/s, train/loss=2.790]
Epoch 0: | | 214/? [00:50<00:00, 4.22it/s, train/loss=20.80]
Epoch 0: | | 215/? [00:50<00:00, 4.24it/s, train/loss=20.80]
Epoch 0: | | 215/? [00:50<00:00, 4.24it/s, train/loss=2.730]
Epoch 0: | | 216/? [00:51<00:00, 4.23it/s, train/loss=2.730]
Epoch 0: | | 216/? [00:51<00:00, 4.23it/s, train/loss=65.60]
Epoch 0: | | 217/? [00:51<00:00, 4.25it/s, train/loss=65.60]
Epoch 0: | | 217/? [00:51<00:00, 4.25it/s, train/loss=2.680]
Epoch 0: | | 218/? [00:51<00:00, 4.25it/s, train/loss=2.680]
Epoch 0: | | 218/? [00:51<00:00, 4.25it/s, train/loss=23.40]
Epoch 0: | | 219/? [00:51<00:00, 4.26it/s, train/loss=23.40]
Epoch 0: | | 219/? [00:51<00:00, 4.26it/s, train/loss=2.660]
Epoch 0: | | 220/? [00:51<00:00, 4.26it/s, train/loss=2.660]
Epoch 0: | | 220/? [00:51<00:00, 4.26it/s, train/loss=27.50]
Epoch 0: | | 221/? [00:51<00:00, 4.28it/s, train/loss=27.50]
Epoch 0: | | 221/? [00:51<00:00, 4.28it/s, train/loss=2.650]
Epoch 0: | | 222/? [00:51<00:00, 4.27it/s, train/loss=2.650]
Epoch 0: | | 222/? [00:51<00:00, 4.27it/s, train/loss=89.30]
Epoch 0: | | 223/? [00:52<00:00, 4.29it/s, train/loss=89.30]
Epoch 0: | | 223/? [00:52<00:00, 4.29it/s, train/loss=2.650]
Epoch 0: | | 224/? [00:52<00:00, 4.28it/s, train/loss=2.650]
Epoch 0: | | 224/? [00:52<00:00, 4.28it/s, train/loss=46.50]
Epoch 0: | | 225/? [00:52<00:00, 4.30it/s, train/loss=46.50]
Epoch 0: | | 225/? [00:52<00:00, 4.30it/s, train/loss=2.650]
Epoch 0: | | 226/? [00:52<00:00, 4.29it/s, train/loss=2.650]
Epoch 0: | | 226/? [00:52<00:00, 4.29it/s, train/loss=24.20]
Epoch 0: | | 227/? [00:52<00:00, 4.31it/s, train/loss=24.20]
Epoch 0: | | 227/? [00:52<00:00, 4.31it/s, train/loss=2.630]
Epoch 0: | | 228/? [00:52<00:00, 4.30it/s, train/loss=2.630]
Epoch 0: | | 228/? [00:52<00:00, 4.30it/s, train/loss=21.20]
Epoch 0: | | 229/? [00:52<00:00, 4.32it/s, train/loss=21.20]
Epoch 0: | | 229/? [00:52<00:00, 4.32it/s, train/loss=2.570]
Epoch 0: | | 230/? [00:53<00:00, 4.32it/s, train/loss=2.570]
Epoch 0: | | 230/? [00:53<00:00, 4.32it/s, train/loss=28.80]
Epoch 0: | | 231/? [00:53<00:00, 4.33it/s, train/loss=28.80]
Epoch 0: | | 231/? [00:53<00:00, 4.33it/s, train/loss=2.490]
Epoch 0: | | 232/? [00:53<00:00, 4.33it/s, train/loss=2.490]
Epoch 0: | | 232/? [00:53<00:00, 4.33it/s, train/loss=18.90]
Epoch 0: | | 233/? [00:53<00:00, 4.34it/s, train/loss=18.90]
Epoch 0: | | 233/? [00:53<00:00, 4.34it/s, train/loss=2.410]
Epoch 0: | | 234/? [00:53<00:00, 4.34it/s, train/loss=2.410]
Epoch 0: | | 234/? [00:53<00:00, 4.34it/s, train/loss=27.70]
Epoch 0: | | 235/? [00:53<00:00, 4.35it/s, train/loss=27.70]
Epoch 0: | | 235/? [00:53<00:00, 4.35it/s, train/loss=2.350]
Epoch 0: | | 236/? [00:54<00:00, 4.35it/s, train/loss=2.350]
Epoch 0: | | 236/? [00:54<00:00, 4.35it/s, train/loss=26.80]
Epoch 0: | | 237/? [00:54<00:00, 4.36it/s, train/loss=26.80]
Epoch 0: | | 237/? [00:54<00:00, 4.36it/s, train/loss=2.300]
Epoch 0: | | 238/? [00:54<00:00, 4.36it/s, train/loss=2.300]
Epoch 0: | | 238/? [00:54<00:00, 4.36it/s, train/loss=21.90]
Epoch 0: | | 239/? [00:54<00:00, 4.38it/s, train/loss=21.90]
Epoch 0: | | 239/? [00:54<00:00, 4.37it/s, train/loss=2.240]
Epoch 0: | | 240/? [00:54<00:00, 4.37it/s, train/loss=2.240]
Epoch 0: | | 240/? [00:54<00:00, 4.37it/s, train/loss=6.910]
Epoch 0: | | 241/? [00:54<00:00, 4.39it/s, train/loss=6.910]
Epoch 0: | | 241/? [00:54<00:00, 4.39it/s, train/loss=2.190]
Epoch 0: | | 242/? [00:55<00:00, 4.38it/s, train/loss=2.190]
Epoch 0: | | 242/? [00:55<00:00, 4.38it/s, train/loss=20.40]
Epoch 0: | | 243/? [00:55<00:00, 4.40it/s, train/loss=20.40]
Epoch 0: | | 243/? [00:55<00:00, 4.40it/s, train/loss=2.140]
Epoch 0: | | 244/? [00:55<00:00, 4.39it/s, train/loss=2.140]
Epoch 0: | | 244/? [00:55<00:00, 4.39it/s, train/loss=27.40]
Epoch 0: | | 245/? [00:55<00:00, 4.41it/s, train/loss=27.40]
Epoch 0: | | 245/? [00:55<00:00, 4.41it/s, train/loss=2.100]
Epoch 0: | | 246/? [00:55<00:00, 4.40it/s, train/loss=2.100]
Epoch 0: | | 246/? [00:55<00:00, 4.40it/s, train/loss=21.10]
Epoch 0: | | 247/? [00:55<00:00, 4.42it/s, train/loss=21.10]
Epoch 0: | | 247/? [00:55<00:00, 4.42it/s, train/loss=2.060]
Epoch 0: | | 248/? [00:56<00:00, 4.41it/s, train/loss=2.060]
Epoch 0: | | 248/? [00:56<00:00, 4.41it/s, train/loss=12.50]
Epoch 0: | | 249/? [00:56<00:00, 4.43it/s, train/loss=12.50]
Epoch 0: | | 249/? [00:56<00:00, 4.43it/s, train/loss=2.020]
Epoch 0: | | 250/? [00:56<00:00, 4.42it/s, train/loss=2.020]
Epoch 0: | | 250/? [00:56<00:00, 4.42it/s, train/loss=24.50]
Epoch 0: | | 251/? [00:56<00:00, 4.43it/s, train/loss=24.50]
Epoch 0: | | 251/? [00:56<00:00, 4.43it/s, train/loss=1.990]
Epoch 0: | | 252/? [00:56<00:00, 4.43it/s, train/loss=1.990]
Epoch 0: | | 252/? [00:56<00:00, 4.43it/s, train/loss=10.80]
Epoch 0: | | 253/? [00:56<00:00, 4.44it/s, train/loss=10.80]
Epoch 0: | | 253/? [00:56<00:00, 4.44it/s, train/loss=1.960]
Epoch 0: | | 254/? [00:57<00:00, 4.44it/s, train/loss=1.960]
Epoch 0: | | 254/? [00:57<00:00, 4.44it/s, train/loss=44.30]
Epoch 0: | | 255/? [00:57<00:00, 4.45it/s, train/loss=44.30]
Epoch 0: | | 255/? [00:57<00:00, 4.45it/s, train/loss=1.930]
Epoch 0: | | 256/? [00:57<00:00, 4.45it/s, train/loss=1.930]
Epoch 0: | | 256/? [00:57<00:00, 4.45it/s, train/loss=34.80]
Epoch 0: | | 257/? [00:57<00:00, 4.46it/s, train/loss=34.80]
Epoch 0: | | 257/? [00:57<00:00, 4.46it/s, train/loss=1.910]
Epoch 0: | | 258/? [00:57<00:00, 4.46it/s, train/loss=1.910]
Epoch 0: | | 258/? [00:57<00:00, 4.46it/s, train/loss=30.50]
Epoch 0: | | 259/? [00:57<00:00, 4.47it/s, train/loss=30.50]
Epoch 0: | | 259/? [00:57<00:00, 4.47it/s, train/loss=1.900]
Epoch 0: | | 260/? [00:58<00:00, 4.47it/s, train/loss=1.900]
Epoch 0: | | 260/? [00:58<00:00, 4.47it/s, train/loss=37.80]
Epoch 0: | | 261/? [00:58<00:00, 4.48it/s, train/loss=37.80]
Epoch 0: | | 261/? [00:58<00:00, 4.48it/s, train/loss=1.890]
Epoch 0: | | 262/? [00:58<00:00, 4.48it/s, train/loss=1.890]
Epoch 0: | | 262/? [00:58<00:00, 4.48it/s, train/loss=24.40]
Epoch 0: | | 263/? [00:58<00:00, 4.49it/s, train/loss=24.40]
Epoch 0: | | 263/? [00:58<00:00, 4.49it/s, train/loss=1.900]
Epoch 0: | | 264/? [00:58<00:00, 4.49it/s, train/loss=1.900]
Epoch 0: | | 264/? [00:58<00:00, 4.49it/s, train/loss=36.50]
Epoch 0: | | 265/? [00:58<00:00, 4.50it/s, train/loss=36.50]
Epoch 0: | | 265/? [00:58<00:00, 4.50it/s, train/loss=1.930]
Epoch 0: | | 266/? [00:59<00:00, 4.50it/s, train/loss=1.930]
Epoch 0: | | 266/? [00:59<00:00, 4.50it/s, train/loss=40.20]
Epoch 0: | | 267/? [00:59<00:00, 4.51it/s, train/loss=40.20]
Epoch 0: | | 267/? [00:59<00:00, 4.51it/s, train/loss=1.960]
Epoch 0: | | 268/? [00:59<00:00, 4.51it/s, train/loss=1.960]
Epoch 0: | | 268/? [00:59<00:00, 4.51it/s, train/loss=15.30]
Epoch 0: | | 269/? [00:59<00:00, 4.52it/s, train/loss=15.30]
Epoch 0: | | 269/? [00:59<00:00, 4.52it/s, train/loss=1.980]
Epoch 0: | | 270/? [00:59<00:00, 4.52it/s, train/loss=1.980]
Epoch 0: | | 270/? [00:59<00:00, 4.52it/s, train/loss=11.80]
Epoch 0: | | 271/? [00:59<00:00, 4.53it/s, train/loss=11.80]
Epoch 0: | | 271/? [00:59<00:00, 4.53it/s, train/loss=1.980]
Epoch 0: | | 272/? [01:00<00:00, 4.53it/s, train/loss=1.980]
Epoch 0: | | 272/? [01:00<00:00, 4.53it/s, train/loss=37.30]
Epoch 0: | | 273/? [01:00<00:00, 4.54it/s, train/loss=37.30]
Epoch 0: | | 273/? [01:00<00:00, 4.54it/s, train/loss=1.930]
Epoch 0: | | 274/? [01:00<00:00, 4.53it/s, train/loss=1.930]
Epoch 0: | | 274/? [01:00<00:00, 4.53it/s, train/loss=20.50]
Epoch 0: | | 275/? [01:00<00:00, 4.55it/s, train/loss=20.50]
Epoch 0: | | 275/? [01:00<00:00, 4.55it/s, train/loss=1.890]
Epoch 0: | | 276/? [01:00<00:00, 4.54it/s, train/loss=1.890]
Epoch 0: | | 276/? [01:00<00:00, 4.54it/s, train/loss=15.60]
Epoch 0: | | 277/? [01:00<00:00, 4.55it/s, train/loss=15.60]
Epoch 0: | | 277/? [01:00<00:00, 4.55it/s, train/loss=1.880]
Epoch 0: | | 278/? [01:01<00:00, 4.54it/s, train/loss=1.880]
Epoch 0: | | 278/? [01:01<00:00, 4.54it/s, train/loss=51.20]
Epoch 0: | | 279/? [01:01<00:00, 4.56it/s, train/loss=51.20]
Epoch 0: | | 279/? [01:01<00:00, 4.56it/s, train/loss=1.880]
Epoch 0: | | 280/? [01:01<00:00, 4.55it/s, train/loss=1.880]
Epoch 0: | | 280/? [01:01<00:00, 4.55it/s, train/loss=22.40]
Epoch 0: | | 281/? [01:01<00:00, 4.56it/s, train/loss=22.40]
Epoch 0: | | 281/? [01:01<00:00, 4.56it/s, train/loss=1.880]
Epoch 0: | | 282/? [01:01<00:00, 4.56it/s, train/loss=1.880]
Epoch 0: | | 282/? [01:01<00:00, 4.56it/s, train/loss=12.20]
Epoch 0: | | 283/? [01:01<00:00, 4.57it/s, train/loss=12.20]
Epoch 0: | | 283/? [01:01<00:00, 4.57it/s, train/loss=1.850]
Epoch 0: | | 284/? [01:02<00:00, 4.57it/s, train/loss=1.850]
Epoch 0: | | 284/? [01:02<00:00, 4.57it/s, train/loss=26.80]
Epoch 0: | | 285/? [01:02<00:00, 4.58it/s, train/loss=26.80]
Epoch 0: | | 285/? [01:02<00:00, 4.58it/s, train/loss=1.800]
Epoch 0: | | 286/? [01:02<00:00, 4.58it/s, train/loss=1.800]
Epoch 0: | | 286/? [01:02<00:00, 4.58it/s, train/loss=19.70]
Epoch 0: | | 287/? [01:02<00:00, 4.59it/s, train/loss=19.70]
Epoch 0: | | 287/? [01:02<00:00, 4.59it/s, train/loss=1.770]
Epoch 0: | | 288/? [01:02<00:00, 4.58it/s, train/loss=1.770]
Epoch 0: | | 288/? [01:02<00:00, 4.58it/s, train/loss=27.50]
Epoch 0: | | 289/? [01:02<00:00, 4.60it/s, train/loss=27.50]
Epoch 0: | | 289/? [01:02<00:00, 4.60it/s, train/loss=1.740]
Epoch 0: | | 290/? [01:03<00:00, 4.59it/s, train/loss=1.740]
Epoch 0: | | 290/? [01:03<00:00, 4.59it/s, train/loss=35.80]
Epoch 0: | | 291/? [01:03<00:00, 4.61it/s, train/loss=35.80]
Epoch 0: | | 291/? [01:03<00:00, 4.61it/s, train/loss=1.740]
Epoch 0: | | 292/? [01:03<00:00, 4.60it/s, train/loss=1.740]
Epoch 0: | | 292/? [01:03<00:00, 4.60it/s, train/loss=28.60]
Epoch 0: | | 293/? [01:03<00:00, 4.61it/s, train/loss=28.60]
Epoch 0: | | 293/? [01:03<00:00, 4.61it/s, train/loss=1.750]
Epoch 0: | | 294/? [01:03<00:00, 4.61it/s, train/loss=1.750]
Epoch 0: | | 294/? [01:03<00:00, 4.61it/s, train/loss=33.70]
Epoch 0: | | 295/? [01:03<00:00, 4.62it/s, train/loss=33.70]
Epoch 0: | | 295/? [01:03<00:00, 4.62it/s, train/loss=1.760]
Epoch 0: | | 296/? [01:04<00:00, 4.62it/s, train/loss=1.760]
Epoch 0: | | 296/? [01:04<00:00, 4.62it/s, train/loss=36.40]
Epoch 0: | | 297/? [01:04<00:00, 4.63it/s, train/loss=36.40]
Epoch 0: | | 297/? [01:04<00:00, 4.63it/s, train/loss=1.760]
Epoch 0: | | 298/? [01:04<00:00, 4.62it/s, train/loss=1.760]
Epoch 0: | | 298/? [01:04<00:00, 4.62it/s, train/loss=9.910]
Epoch 0: | | 299/? [01:04<00:00, 4.64it/s, train/loss=9.910]
Epoch 0: | | 299/? [01:04<00:00, 4.64it/s, train/loss=1.740]
Epoch 0: | | 300/? [01:04<00:00, 4.63it/s, train/loss=1.740]
Epoch 0: | | 300/? [01:04<00:00, 4.63it/s, train/loss=11.90]
Epoch 0: | | 301/? [01:04<00:00, 4.65it/s, train/loss=11.90]
Epoch 0: | | 301/? [01:04<00:00, 4.65it/s, train/loss=1.710]
Epoch 0: | | 302/? [01:05<00:00, 4.64it/s, train/loss=1.710]
Epoch 0: | | 302/? [01:05<00:00, 4.64it/s, train/loss=31.00]
Epoch 0: | | 303/? [01:05<00:00, 4.65it/s, train/loss=31.00]
Epoch 0: | | 303/? [01:05<00:00, 4.65it/s, train/loss=1.710]
Epoch 0: | | 304/? [01:05<00:00, 4.65it/s, train/loss=1.710]
Epoch 0: | | 304/? [01:05<00:00, 4.65it/s, train/loss=23.80]
Epoch 0: | | 305/? [01:05<00:00, 4.66it/s, train/loss=23.80]
Epoch 0: | | 305/? [01:05<00:00, 4.66it/s, train/loss=1.760]
Epoch 0: | | 306/? [01:05<00:00, 4.66it/s, train/loss=1.760]
Epoch 0: | | 306/? [01:05<00:00, 4.66it/s, train/loss=13.10]
Epoch 0: | | 307/? [01:05<00:00, 4.67it/s, train/loss=13.10]
Epoch 0: | | 307/? [01:05<00:00, 4.67it/s, train/loss=1.800]
Epoch 0: | | 308/? [01:06<00:00, 4.67it/s, train/loss=1.800]
Epoch 0: | | 308/? [01:06<00:00, 4.67it/s, train/loss=20.90]
Epoch 0: | | 309/? [01:06<00:00, 4.68it/s, train/loss=20.90]
Epoch 0: | | 309/? [01:06<00:00, 4.68it/s, train/loss=1.770]
Epoch 0: | | 310/? [01:06<00:00, 4.67it/s, train/loss=1.770]
Epoch 0: | | 310/? [01:06<00:00, 4.67it/s, train/loss=36.20]
Epoch 0: | | 311/? [01:06<00:00, 4.69it/s, train/loss=36.20]
Epoch 0: | | 311/? [01:06<00:00, 4.68it/s, train/loss=1.700]
Epoch 0: | | 312/? [01:06<00:00, 4.68it/s, train/loss=1.700]
Epoch 0: | | 312/? [01:06<00:00, 4.68it/s, train/loss=29.00]
Epoch 0: | | 313/? [01:06<00:00, 4.69it/s, train/loss=29.00]
Epoch 0: | | 313/? [01:06<00:00, 4.69it/s, train/loss=1.640]
Epoch 0: | | 314/? [01:06<00:00, 4.69it/s, train/loss=1.640]
Epoch 0: | | 314/? [01:06<00:00, 4.69it/s, train/loss=12.90]
Epoch 0: | | 315/? [01:07<00:00, 4.70it/s, train/loss=12.90]
Epoch 0: | | 315/? [01:07<00:00, 4.70it/s, train/loss=1.620]
Epoch 0: | | 316/? [01:07<00:00, 4.70it/s, train/loss=1.620]
Epoch 0: | | 316/? [01:07<00:00, 4.70it/s, train/loss=19.40]
Epoch 0: | | 317/? [01:07<00:00, 4.71it/s, train/loss=19.40]
Epoch 0: | | 317/? [01:07<00:00, 4.71it/s, train/loss=1.590]
Epoch 0: | | 318/? [01:07<00:00, 4.70it/s, train/loss=1.590]
Epoch 0: | | 318/? [01:07<00:00, 4.70it/s, train/loss=17.20]
Epoch 0: | | 319/? [01:07<00:00, 4.72it/s, train/loss=17.20]
Epoch 0: | | 319/? [01:07<00:00, 4.71it/s, train/loss=1.570]
Epoch 0: | | 320/? [01:07<00:00, 4.71it/s, train/loss=1.570]
Epoch 0: | | 320/? [01:07<00:00, 4.71it/s, train/loss=8.480]
Epoch 0: | | 321/? [01:07<00:00, 4.72it/s, train/loss=8.480]
Epoch 0: | | 321/? [01:07<00:00, 4.72it/s, train/loss=1.620]
Epoch 0: | | 322/? [01:08<00:00, 4.72it/s, train/loss=1.620]
Epoch 0: | | 322/? [01:08<00:00, 4.72it/s, train/loss=20.80]
Epoch 0: | | 323/? [01:08<00:00, 4.73it/s, train/loss=20.80]
Epoch 0: | | 323/? [01:08<00:00, 4.73it/s, train/loss=1.580]
Epoch 0: | | 324/? [01:08<00:00, 4.72it/s, train/loss=1.580]
Epoch 0: | | 324/? [01:08<00:00, 4.72it/s, train/loss=12.70]
Epoch 0: | | 325/? [01:08<00:00, 4.74it/s, train/loss=12.70]
Epoch 0: | | 325/? [01:08<00:00, 4.74it/s, train/loss=1.560]
Epoch 0: | | 326/? [01:08<00:00, 4.73it/s, train/loss=1.560]
Epoch 0: | | 326/? [01:08<00:00, 4.73it/s, train/loss=28.90]
Epoch 0: | | 327/? [01:08<00:00, 4.74it/s, train/loss=28.90]
Epoch 0: | | 327/? [01:08<00:00, 4.74it/s, train/loss=1.540]
Epoch 0: | | 328/? [01:09<00:00, 4.74it/s, train/loss=1.540]
Epoch 0: | | 328/? [01:09<00:00, 4.74it/s, train/loss=24.00]
Epoch 0: | | 329/? [01:09<00:00, 4.75it/s, train/loss=24.00]
Epoch 0: | | 329/? [01:09<00:00, 4.75it/s, train/loss=1.520]
Epoch 0: | | 330/? [01:09<00:00, 4.75it/s, train/loss=1.520]
Epoch 0: | | 330/? [01:09<00:00, 4.75it/s, train/loss=21.20]
Epoch 0: | | 331/? [01:09<00:00, 4.76it/s, train/loss=21.20]
Epoch 0: | | 331/? [01:09<00:00, 4.76it/s, train/loss=1.510]
Epoch 0: | | 332/? [01:09<00:00, 4.75it/s, train/loss=1.510]
Epoch 0: | | 332/? [01:09<00:00, 4.75it/s, train/loss=71.20]
Epoch 0: | | 333/? [01:09<00:00, 4.76it/s, train/loss=71.20]
Epoch 0: | | 333/? [01:09<00:00, 4.76it/s, train/loss=1.500]
Epoch 0: | | 334/? [01:10<00:00, 4.76it/s, train/loss=1.500]
Epoch 0: | | 334/? [01:10<00:00, 4.76it/s, train/loss=15.70]
Epoch 0: | | 335/? [01:10<00:00, 4.77it/s, train/loss=15.70]
Epoch 0: | | 335/? [01:10<00:00, 4.77it/s, train/loss=1.510]
Epoch 0: | | 336/? [01:10<00:00, 4.77it/s, train/loss=1.510]
Epoch 0: | | 336/? [01:10<00:00, 4.77it/s, train/loss=40.90]
Epoch 0: | | 337/? [01:10<00:00, 4.78it/s, train/loss=40.90]
Epoch 0: | | 337/? [01:10<00:00, 4.78it/s, train/loss=1.530]
Epoch 0: | | 338/? [01:10<00:00, 4.77it/s, train/loss=1.530]
Epoch 0: | | 338/? [01:10<00:00, 4.77it/s, train/loss=52.10]
Epoch 0: | | 339/? [01:10<00:00, 4.79it/s, train/loss=52.10]
Epoch 0: | | 339/? [01:10<00:00, 4.79it/s, train/loss=1.570]
Epoch 0: | | 340/? [01:11<00:00, 4.78it/s, train/loss=1.570]
Epoch 0: | | 340/? [01:11<00:00, 4.78it/s, train/loss=13.10]
Epoch 0: | | 341/? [01:11<00:00, 4.79it/s, train/loss=13.10]
Epoch 0: | | 341/? [01:11<00:00, 4.79it/s, train/loss=1.650]
Epoch 0: | | 342/? [01:11<00:00, 4.79it/s, train/loss=1.650]
Epoch 0: | | 342/? [01:11<00:00, 4.79it/s, train/loss=35.70]
Epoch 0: | | 343/? [01:11<00:00, 4.80it/s, train/loss=35.70]
Epoch 0: | | 343/? [01:11<00:00, 4.80it/s, train/loss=1.690]
Epoch 0: | | 344/? [01:11<00:00, 4.79it/s, train/loss=1.690]
Epoch 0: | | 344/? [01:11<00:00, 4.79it/s, train/loss=37.80]
Epoch 0: | | 345/? [01:11<00:00, 4.81it/s, train/loss=37.80]
Epoch 0: | | 345/? [01:11<00:00, 4.81it/s, train/loss=1.700]
Epoch 0: | | 346/? [01:12<00:00, 4.80it/s, train/loss=1.700]
Epoch 0: | | 346/? [01:12<00:00, 4.80it/s, train/loss=14.10]
Epoch 0: | | 347/? [01:12<00:00, 4.81it/s, train/loss=14.10]
Epoch 0: | | 347/? [01:12<00:00, 4.81it/s, train/loss=1.700]
Epoch 0: | | 348/? [01:12<00:00, 4.81it/s, train/loss=1.700]
Epoch 0: | | 348/? [01:12<00:00, 4.81it/s, train/loss=43.30]
Epoch 0: | | 349/? [01:12<00:00, 4.82it/s, train/loss=43.30]
Epoch 0: | | 349/? [01:12<00:00, 4.82it/s, train/loss=1.670]
Epoch 0: | | 350/? [01:12<00:00, 4.81it/s, train/loss=1.670]
Epoch 0: | | 350/? [01:12<00:00, 4.81it/s, train/loss=21.80]
Epoch 0: | | 351/? [01:12<00:00, 4.82it/s, train/loss=21.80]
Epoch 0: | | 351/? [01:12<00:00, 4.82it/s, train/loss=1.620]
Epoch 0: | | 352/? [01:13<00:00, 4.82it/s, train/loss=1.620]
Epoch 0: | | 352/? [01:13<00:00, 4.82it/s, train/loss=38.20]
Epoch 0: | | 353/? [01:13<00:00, 4.83it/s, train/loss=38.20]
Epoch 0: | | 353/? [01:13<00:00, 4.83it/s, train/loss=1.580]
Epoch 0: | | 354/? [01:13<00:00, 4.83it/s, train/loss=1.580]
Epoch 0: | | 354/? [01:13<00:00, 4.83it/s, train/loss=14.50]
Epoch 0: | | 355/? [01:13<00:00, 4.84it/s, train/loss=14.50]
Epoch 0: | | 355/? [01:13<00:00, 4.84it/s, train/loss=1.550]
Epoch 0: | | 356/? [01:13<00:00, 4.83it/s, train/loss=1.550]
Epoch 0: | | 356/? [01:13<00:00, 4.83it/s, train/loss=27.10]
Epoch 0: | | 357/? [01:13<00:00, 4.84it/s, train/loss=27.10]
Epoch 0: | | 357/? [01:13<00:00, 4.84it/s, train/loss=1.530]
Epoch 0: | | 358/? [01:13<00:00, 4.84it/s, train/loss=1.530]
Epoch 0: | | 358/? [01:13<00:00, 4.84it/s, train/loss=22.20]
Epoch 0: | | 359/? [01:14<00:00, 4.85it/s, train/loss=22.20]
Epoch 0: | | 359/? [01:14<00:00, 4.85it/s, train/loss=1.510]
Epoch 0: | | 360/? [01:14<00:00, 4.84it/s, train/loss=1.510]
Epoch 0: | | 360/? [01:14<00:00, 4.84it/s, train/loss=16.60]
Epoch 0: | | 361/? [01:14<00:00, 4.86it/s, train/loss=16.60]
Epoch 0: | | 361/? [01:14<00:00, 4.86it/s, train/loss=1.510]
Epoch 0: | | 362/? [01:14<00:00, 4.85it/s, train/loss=1.510]
Epoch 0: | | 362/? [01:14<00:00, 4.85it/s, train/loss=29.70]
Epoch 0: | | 363/? [01:14<00:00, 4.86it/s, train/loss=29.70]
Epoch 0: | | 363/? [01:14<00:00, 4.86it/s, train/loss=1.500]
Epoch 0: | | 364/? [01:14<00:00, 4.86it/s, train/loss=1.500]
Epoch 0: | | 364/? [01:14<00:00, 4.86it/s, train/loss=34.00]
Epoch 0: | | 365/? [01:14<00:00, 4.87it/s, train/loss=34.00]
Epoch 0: | | 365/? [01:14<00:00, 4.87it/s, train/loss=1.500]
Epoch 0: | | 366/? [01:15<00:00, 4.86it/s, train/loss=1.500]
Epoch 0: | | 366/? [01:15<00:00, 4.86it/s, train/loss=15.00]
Epoch 0: | | 367/? [01:15<00:00, 4.87it/s, train/loss=15.00]
Epoch 0: | | 367/? [01:15<00:00, 4.87it/s, train/loss=1.490]
Epoch 0: | | 368/? [01:15<00:00, 4.86it/s, train/loss=1.490]
Epoch 0: | | 368/? [01:15<00:00, 4.86it/s, train/loss=24.70]
Epoch 0: | | 369/? [01:15<00:00, 4.86it/s, train/loss=24.70]
Epoch 0: | | 369/? [01:15<00:00, 4.86it/s, train/loss=1.630]
Epoch 0: | | 370/? [01:16<00:00, 4.85it/s, train/loss=1.630]
Epoch 0: | | 370/? [01:16<00:00, 4.85it/s, train/loss=30.90]
Epoch 0: | | 371/? [01:16<00:00, 4.86it/s, train/loss=30.90]
Epoch 0: | | 371/? [01:16<00:00, 4.86it/s, train/loss=1.620]
Epoch 0: | | 372/? [01:16<00:00, 4.85it/s, train/loss=1.620]
Epoch 0: | | 372/? [01:16<00:00, 4.85it/s, train/loss=26.20]
Epoch 0: | | 373/? [01:16<00:00, 4.86it/s, train/loss=26.20]
Epoch 0: | | 373/? [01:16<00:00, 4.86it/s, train/loss=1.610]
Epoch 0: | | 374/? [01:17<00:00, 4.85it/s, train/loss=1.610]
Epoch 0: | | 374/? [01:17<00:00, 4.85it/s, train/loss=15.60]
Epoch 0: | | 375/? [01:17<00:00, 4.85it/s, train/loss=15.60]
Epoch 0: | | 375/? [01:17<00:00, 4.85it/s, train/loss=1.600]
Epoch 0: | | 376/? [01:17<00:00, 4.85it/s, train/loss=1.600]
Epoch 0: | | 376/? [01:17<00:00, 4.85it/s, train/loss=30.70]
Epoch 0: | | 377/? [01:17<00:00, 4.86it/s, train/loss=30.70]
Epoch 0: | | 377/? [01:17<00:00, 4.86it/s, train/loss=1.590]
Epoch 0: | | 378/? [01:17<00:00, 4.85it/s, train/loss=1.590]
Epoch 0: | | 378/? [01:17<00:00, 4.85it/s, train/loss=28.90]
Epoch 0: | | 379/? [01:17<00:00, 4.86it/s, train/loss=28.90]
Epoch 0: | | 379/? [01:17<00:00, 4.86it/s, train/loss=1.580]
Epoch 0: | | 380/? [01:18<00:00, 4.86it/s, train/loss=1.580]
Epoch 0: | | 380/? [01:18<00:00, 4.86it/s, train/loss=39.10]
Epoch 0: | | 381/? [01:18<00:00, 4.87it/s, train/loss=39.10]
Epoch 0: | | 381/? [01:18<00:00, 4.87it/s, train/loss=1.600]
Epoch 0: | | 382/? [01:18<00:00, 4.86it/s, train/loss=1.600]
Epoch 0: | | 382/? [01:18<00:00, 4.86it/s, train/loss=20.10]
Epoch 0: | | 383/? [01:18<00:00, 4.87it/s, train/loss=20.10]
Epoch 0: | | 383/? [01:18<00:00, 4.87it/s, train/loss=1.660]
Epoch 0: | | 384/? [01:18<00:00, 4.87it/s, train/loss=1.660]
Epoch 0: | | 384/? [01:18<00:00, 4.87it/s, train/loss=39.30]
Epoch 0: | | 385/? [01:18<00:00, 4.88it/s, train/loss=39.30]
Epoch 0: | | 385/? [01:18<00:00, 4.88it/s, train/loss=1.710]
Epoch 0: | | 386/? [01:19<00:00, 4.87it/s, train/loss=1.710]
Epoch 0: | | 386/? [01:19<00:00, 4.87it/s, train/loss=9.900]
Epoch 0: | | 387/? [01:19<00:00, 4.88it/s, train/loss=9.900]
Epoch 0: | | 387/? [01:19<00:00, 4.88it/s, train/loss=1.710]
Epoch 0: | | 388/? [01:19<00:00, 4.88it/s, train/loss=1.710]
Epoch 0: | | 388/? [01:19<00:00, 4.88it/s, train/loss=27.30]
Epoch 0: | | 389/? [01:19<00:00, 4.89it/s, train/loss=27.30]
Epoch 0: | | 389/? [01:19<00:00, 4.89it/s, train/loss=1.700]
Epoch 0: | | 390/? [01:19<00:00, 4.89it/s, train/loss=1.700]
Epoch 0: | | 390/? [01:19<00:00, 4.89it/s, train/loss=23.70]
Epoch 0: | | 391/? [01:19<00:00, 4.90it/s, train/loss=23.70]
Epoch 0: | | 391/? [01:19<00:00, 4.90it/s, train/loss=1.670]
Epoch 0: | | 392/? [01:20<00:00, 4.89it/s, train/loss=1.670]
Epoch 0: | | 392/? [01:20<00:00, 4.89it/s, train/loss=22.80]
Epoch 0: | | 393/? [01:20<00:00, 4.90it/s, train/loss=22.80]
Epoch 0: | | 393/? [01:20<00:00, 4.90it/s, train/loss=1.640]
Epoch 0: | | 394/? [01:20<00:00, 4.90it/s, train/loss=1.640]
Epoch 0: | | 394/? [01:20<00:00, 4.90it/s, train/loss=26.00]
Epoch 0: | | 395/? [01:20<00:00, 4.91it/s, train/loss=26.00]
Epoch 0: | | 395/? [01:20<00:00, 4.91it/s, train/loss=1.640]
Epoch 0: | | 396/? [01:20<00:00, 4.90it/s, train/loss=1.640]
Epoch 0: | | 396/? [01:20<00:00, 4.90it/s, train/loss=9.660]
Epoch 0: | | 397/? [01:20<00:00, 4.91it/s, train/loss=9.660]
Epoch 0: | | 397/? [01:20<00:00, 4.91it/s, train/loss=1.630]
Epoch 0: | | 398/? [01:21<00:00, 4.91it/s, train/loss=1.630]
Epoch 0: | | 398/? [01:21<00:00, 4.91it/s, train/loss=12.90]
Epoch 0: | | 399/? [01:21<00:00, 4.92it/s, train/loss=12.90]
Epoch 0: | | 399/? [01:21<00:00, 4.92it/s, train/loss=1.610]
Epoch 0: | | 400/? [01:21<00:00, 4.91it/s, train/loss=1.610]
Epoch 0: | | 400/? [01:21<00:00, 4.91it/s, train/loss=37.30]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:08, 4.51it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:08, 4.40it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:08, 4.44it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:08, 4.44it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:01<00:07, 4.45it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:01<00:07, 4.44it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:01<00:07, 4.48it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:01<00:07, 4.47it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:02<00:06, 4.47it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:02<00:06, 4.50it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:02<00:06, 4.50it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:02<00:06, 4.50it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:02<00:05, 4.53it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:03<00:05, 4.52it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:03<00:05, 4.54it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:03<00:05, 4.56it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:03<00:05, 4.58it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:03<00:04, 4.58it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:04<00:04, 4.59it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:04<00:04, 4.60it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:04<00:04, 4.61it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:04<00:03, 4.62it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:04<00:03, 4.61it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:05<00:03, 4.61it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:05<00:03, 4.61it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:05<00:03, 4.62it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:05<00:02, 4.61it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:06<00:02, 4.60it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:06<00:02, 4.60it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:06<00:02, 4.61it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:06<00:01, 4.62it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:06<00:01, 4.63it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:07<00:01, 4.63it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:07<00:01, 4.64it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:07<00:01, 4.64it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:07<00:00, 4.64it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:07<00:00, 4.63it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:08<00:00, 4.62it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:08<00:00, 4.63it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:08<00:00, 4.63it/s][A
[A
Epoch 0: | | 400/? [01:30<00:00, 4.40it/s, train/loss=37.30]
Epoch 0: | | 401/? [01:31<00:00, 4.36it/s, train/loss=37.30]
Epoch 0: | | 401/? [01:31<00:00, 4.36it/s, train/loss=1.570]
Epoch 0: | | 402/? [01:32<00:00, 4.36it/s, train/loss=1.570]
Epoch 0: | | 402/? [01:32<00:00, 4.36it/s, train/loss=12.40]
Epoch 0: | | 403/? [01:32<00:00, 4.37it/s, train/loss=12.40]
Epoch 0: | | 403/? [01:32<00:00, 4.37it/s, train/loss=1.540]
Epoch 0: | | 404/? [01:32<00:00, 4.37it/s, train/loss=1.540]
Epoch 0: | | 404/? [01:32<00:00, 4.37it/s, train/loss=18.20]
Epoch 0: | | 405/? [01:32<00:00, 4.37it/s, train/loss=18.20]
Epoch 0: | | 405/? [01:32<00:00, 4.37it/s, train/loss=1.510]
Epoch 0: | | 406/? [01:32<00:00, 4.37it/s, train/loss=1.510]
Epoch 0: | | 406/? [01:32<00:00, 4.37it/s, train/loss=23.10]
Epoch 0: | | 407/? [01:32<00:00, 4.38it/s, train/loss=23.10]
Epoch 0: | | 407/? [01:32<00:00, 4.38it/s, train/loss=1.500]
Epoch 0: | | 408/? [01:33<00:00, 4.38it/s, train/loss=1.500]
Epoch 0: | | 408/? [01:33<00:00, 4.38it/s, train/loss=16.30]
Epoch 0: | | 409/? [01:33<00:00, 4.39it/s, train/loss=16.30]
Epoch 0: | | 409/? [01:33<00:00, 4.39it/s, train/loss=1.490]
Epoch 0: | | 410/? [01:33<00:00, 4.38it/s, train/loss=1.490]
Epoch 0: | | 410/? [01:33<00:00, 4.38it/s, train/loss=27.70]
Epoch 0: | | 411/? [01:33<00:00, 4.39it/s, train/loss=27.70]
Epoch 0: | | 411/? [01:33<00:00, 4.39it/s, train/loss=1.500]
Epoch 0: | | 412/? [01:33<00:00, 4.39it/s, train/loss=1.500]
Epoch 0: | | 412/? [01:33<00:00, 4.39it/s, train/loss=11.30]
Epoch 0: | | 413/? [01:33<00:00, 4.40it/s, train/loss=11.30]
Epoch 0: | | 413/? [01:33<00:00, 4.40it/s, train/loss=1.490]
Epoch 0: | | 414/? [01:34<00:00, 4.40it/s, train/loss=1.490]
Epoch 0: | | 414/? [01:34<00:00, 4.40it/s, train/loss=11.10]
Epoch 0: | | 415/? [01:34<00:00, 4.41it/s, train/loss=11.10]
Epoch 0: | | 415/? [01:34<00:00, 4.41it/s, train/loss=1.480]
Epoch 0: | | 416/? [01:34<00:00, 4.40it/s, train/loss=1.480]
Epoch 0: | | 416/? [01:34<00:00, 4.40it/s, train/loss=21.90]
Epoch 0: | | 417/? [01:34<00:00, 4.41it/s, train/loss=21.90]
Epoch 0: | | 417/? [01:34<00:00, 4.41it/s, train/loss=1.460]
Epoch 0: | | 418/? [01:34<00:00, 4.41it/s, train/loss=1.460]
Epoch 0: | | 418/? [01:34<00:00, 4.41it/s, train/loss=35.50]
Epoch 0: | | 419/? [01:34<00:00, 4.42it/s, train/loss=35.50]
Epoch 0: | | 419/? [01:34<00:00, 4.42it/s, train/loss=1.440]
Epoch 0: | | 420/? [01:35<00:00, 4.42it/s, train/loss=1.440]
Epoch 0: | | 420/? [01:35<00:00, 4.42it/s, train/loss=40.30]
Epoch 0: | | 421/? [01:35<00:00, 4.43it/s, train/loss=40.30]
Epoch 0: | | 421/? [01:35<00:00, 4.43it/s, train/loss=1.400]
Epoch 0: | | 422/? [01:35<00:00, 4.42it/s, train/loss=1.400]
Epoch 0: | | 422/? [01:35<00:00, 4.42it/s, train/loss=23.00]
Epoch 0: | | 423/? [01:35<00:00, 4.43it/s, train/loss=23.00]
Epoch 0: | | 423/? [01:35<00:00, 4.43it/s, train/loss=1.370]
Epoch 0: | | 424/? [01:35<00:00, 4.43it/s, train/loss=1.370]
Epoch 0: | | 424/? [01:35<00:00, 4.43it/s, train/loss=17.50]
Epoch 0: | | 425/? [01:35<00:00, 4.44it/s, train/loss=17.50]
Epoch 0: | | 425/? [01:35<00:00, 4.44it/s, train/loss=1.360]
Epoch 0: | | 426/? [01:36<00:00, 4.44it/s, train/loss=1.360]
Epoch 0: | | 426/? [01:36<00:00, 4.44it/s, train/loss=26.50]
Epoch 0: | | 427/? [01:36<00:00, 4.45it/s, train/loss=26.50]
Epoch 0: | | 427/? [01:36<00:00, 4.45it/s, train/loss=1.370]
Epoch 0: | | 428/? [01:36<00:00, 4.44it/s, train/loss=1.370]
Epoch 0: | | 428/? [01:36<00:00, 4.44it/s, train/loss=40.60]
Epoch 0: | | 429/? [01:36<00:00, 4.45it/s, train/loss=40.60]
Epoch 0: | | 429/? [01:36<00:00, 4.45it/s, train/loss=1.410]
Epoch 0: | | 430/? [01:36<00:00, 4.45it/s, train/loss=1.410]
Epoch 0: | | 430/? [01:36<00:00, 4.45it/s, train/loss=9.530]
Epoch 0: | | 431/? [01:36<00:00, 4.46it/s, train/loss=9.530]
Epoch 0: | | 431/? [01:36<00:00, 4.46it/s, train/loss=1.460]
Epoch 0: | | 432/? [01:36<00:00, 4.46it/s, train/loss=1.460]
Epoch 0: | | 432/? [01:36<00:00, 4.46it/s, train/loss=10.90]
Epoch 0: | | 433/? [01:36<00:00, 4.46it/s, train/loss=10.90]
Epoch 0: | | 433/? [01:36<00:00, 4.46it/s, train/loss=1.410]
Epoch 0: | | 434/? [01:37<00:00, 4.46it/s, train/loss=1.410]
Epoch 0: | | 434/? [01:37<00:00, 4.46it/s, train/loss=13.10]
Epoch 0: | | 435/? [01:37<00:00, 4.47it/s, train/loss=13.10]
Epoch 0: | | 435/? [01:37<00:00, 4.47it/s, train/loss=1.380]
Epoch 0: | | 436/? [01:37<00:00, 4.47it/s, train/loss=1.380]
Epoch 0: | | 436/? [01:37<00:00, 4.47it/s, train/loss=30.50]
Epoch 0: | | 437/? [01:37<00:00, 4.48it/s, train/loss=30.50]
Epoch 0: | | 437/? [01:37<00:00, 4.48it/s, train/loss=1.340]
Epoch 0: | | 438/? [01:37<00:00, 4.47it/s, train/loss=1.340]
Epoch 0: | | 438/? [01:37<00:00, 4.47it/s, train/loss=19.70]
Epoch 0: | | 439/? [01:37<00:00, 4.48it/s, train/loss=19.70]
Epoch 0: | | 439/? [01:37<00:00, 4.48it/s, train/loss=1.300]
Epoch 0: | | 440/? [01:38<00:00, 4.48it/s, train/loss=1.300]
Epoch 0: | | 440/? [01:38<00:00, 4.48it/s, train/loss=8.380]
Epoch 0: | | 441/? [01:38<00:00, 4.49it/s, train/loss=8.380]
Epoch 0: | | 441/? [01:38<00:00, 4.49it/s, train/loss=1.310]
Epoch 0: | | 442/? [01:38<00:00, 4.49it/s, train/loss=1.310]
Epoch 0: | | 442/? [01:38<00:00, 4.49it/s, train/loss=20.80]
Epoch 0: | | 443/? [01:38<00:00, 4.49it/s, train/loss=20.80]
Epoch 0: | | 443/? [01:38<00:00, 4.49it/s, train/loss=1.340]
Epoch 0: | | 444/? [01:38<00:00, 4.49it/s, train/loss=1.340]
Epoch 0: | | 444/? [01:38<00:00, 4.49it/s, train/loss=19.60]
Epoch 0: | | 445/? [01:38<00:00, 4.50it/s, train/loss=19.60]
Epoch 0: | | 445/? [01:38<00:00, 4.50it/s, train/loss=1.360]
Epoch 0: | | 446/? [01:39<00:00, 4.50it/s, train/loss=1.360]
Epoch 0: | | 446/? [01:39<00:00, 4.50it/s, train/loss=27.50]
Epoch 0: | | 447/? [01:39<00:00, 4.51it/s, train/loss=27.50]
Epoch 0: | | 447/? [01:39<00:00, 4.51it/s, train/loss=1.350]
Epoch 0: | | 448/? [01:39<00:00, 4.50it/s, train/loss=1.350]
Epoch 0: | | 448/? [01:39<00:00, 4.50it/s, train/loss=21.00]
Epoch 0: | | 449/? [01:39<00:00, 4.51it/s, train/loss=21.00]
Epoch 0: | | 449/? [01:39<00:00, 4.51it/s, train/loss=1.310]
Epoch 0: | | 450/? [01:39<00:00, 4.51it/s, train/loss=1.310]
Epoch 0: | | 450/? [01:39<00:00, 4.51it/s, train/loss=23.30]
Epoch 0: | | 451/? [01:39<00:00, 4.52it/s, train/loss=23.30]
Epoch 0: | | 451/? [01:39<00:00, 4.52it/s, train/loss=1.240]
Epoch 0: | | 452/? [01:40<00:00, 4.52it/s, train/loss=1.240]
Epoch 0: | | 452/? [01:40<00:00, 4.52it/s, train/loss=35.10]
Epoch 0: | | 453/? [01:40<00:00, 4.53it/s, train/loss=35.10]
Epoch 0: | | 453/? [01:40<00:00, 4.53it/s, train/loss=1.200]
Epoch 0: | | 454/? [01:40<00:00, 4.52it/s, train/loss=1.200]
Epoch 0: | | 454/? [01:40<00:00, 4.52it/s, train/loss=20.00]
Epoch 0: | | 455/? [01:40<00:00, 4.53it/s, train/loss=20.00]
Epoch 0: | | 455/? [01:40<00:00, 4.53it/s, train/loss=1.200]
Epoch 0: | | 456/? [01:40<00:00, 4.53it/s, train/loss=1.200]
Epoch 0: | | 456/? [01:40<00:00, 4.53it/s, train/loss=33.20]
Epoch 0: | | 457/? [01:40<00:00, 4.54it/s, train/loss=33.20]
Epoch 0: | | 457/? [01:40<00:00, 4.54it/s, train/loss=1.240]
Epoch 0: | | 458/? [01:41<00:00, 4.53it/s, train/loss=1.240]
Epoch 0: | | 458/? [01:41<00:00, 4.53it/s, train/loss=12.90]
Epoch 0: | | 459/? [01:41<00:00, 4.54it/s, train/loss=12.90]
Epoch 0: | | 459/? [01:41<00:00, 4.54it/s, train/loss=1.340]
Epoch 0: | | 460/? [01:41<00:00, 4.54it/s, train/loss=1.340]
Epoch 0: | | 460/? [01:41<00:00, 4.54it/s, train/loss=27.10]
Epoch 0: | | 461/? [01:41<00:00, 4.55it/s, train/loss=27.10]
Epoch 0: | | 461/? [01:41<00:00, 4.55it/s, train/loss=1.450]
Epoch 0: | | 462/? [01:41<00:00, 4.55it/s, train/loss=1.450]
Epoch 0: | | 462/? [01:41<00:00, 4.55it/s, train/loss=14.40]
Epoch 0: | | 463/? [01:41<00:00, 4.55it/s, train/loss=14.40]
Epoch 0: | | 463/? [01:41<00:00, 4.55it/s, train/loss=1.480]
Epoch 0: | | 464/? [01:41<00:00, 4.55it/s, train/loss=1.480]
Epoch 0: | | 464/? [01:41<00:00, 4.55it/s, train/loss=11.30]
Epoch 0: | | 465/? [01:41<00:00, 4.56it/s, train/loss=11.30]
Epoch 0: | | 465/? [01:41<00:00, 4.56it/s, train/loss=1.420]
Epoch 0: | | 466/? [01:42<00:00, 4.56it/s, train/loss=1.420]
Epoch 0: | | 466/? [01:42<00:00, 4.56it/s, train/loss=27.20]
Epoch 0: | | 467/? [01:42<00:00, 4.57it/s, train/loss=27.20]
Epoch 0: | | 467/? [01:42<00:00, 4.57it/s, train/loss=1.320]
Epoch 0: | | 468/? [01:42<00:00, 4.56it/s, train/loss=1.320]
Epoch 0: | | 468/? [01:42<00:00, 4.56it/s, train/loss=30.50]
Epoch 0: | | 469/? [01:42<00:00, 4.57it/s, train/loss=30.50]
Epoch 0: | | 469/? [01:42<00:00, 4.57it/s, train/loss=1.240]
Epoch 0: | | 470/? [01:42<00:00, 4.57it/s, train/loss=1.240]
Epoch 0: | | 470/? [01:42<00:00, 4.57it/s, train/loss=14.90]
Epoch 0: | | 471/? [01:42<00:00, 4.58it/s, train/loss=14.90]
Epoch 0: | | 471/? [01:42<00:00, 4.58it/s, train/loss=1.200]
Epoch 0: | | 472/? [01:43<00:00, 4.57it/s, train/loss=1.200]
Epoch 0: | | 472/? [01:43<00:00, 4.57it/s, train/loss=12.10]
Epoch 0: | | 473/? [01:43<00:00, 4.58it/s, train/loss=12.10]
Epoch 0: | | 473/? [01:43<00:00, 4.58it/s, train/loss=1.180]
Epoch 0: | | 474/? [01:43<00:00, 4.58it/s, train/loss=1.180]
Epoch 0: | | 474/? [01:43<00:00, 4.58it/s, train/loss=41.20]
Epoch 0: | | 475/? [01:43<00:00, 4.59it/s, train/loss=41.20]
Epoch 0: | | 475/? [01:43<00:00, 4.59it/s, train/loss=1.170]
Epoch 0: | | 476/? [01:43<00:00, 4.59it/s, train/loss=1.170]
Epoch 0: | | 476/? [01:43<00:00, 4.59it/s, train/loss=29.90]
Epoch 0: | | 477/? [01:43<00:00, 4.59it/s, train/loss=29.90]
Epoch 0: | | 477/? [01:43<00:00, 4.59it/s, train/loss=1.170]
Epoch 0: | | 478/? [01:44<00:00, 4.59it/s, train/loss=1.170]
Epoch 0: | | 478/? [01:44<00:00, 4.59it/s, train/loss=25.50]
Epoch 0: | | 479/? [01:44<00:00, 4.60it/s, train/loss=25.50]
Epoch 0: | | 479/? [01:44<00:00, 4.60it/s, train/loss=1.160]
Epoch 0: | | 480/? [01:44<00:00, 4.60it/s, train/loss=1.160]
Epoch 0: | | 480/? [01:44<00:00, 4.60it/s, train/loss=8.880]
Epoch 0: | | 481/? [01:44<00:00, 4.60it/s, train/loss=8.880]
Epoch 0: | | 481/? [01:44<00:00, 4.60it/s, train/loss=1.140]
Epoch 0: | | 482/? [01:44<00:00, 4.60it/s, train/loss=1.140]
Epoch 0: | | 482/? [01:44<00:00, 4.60it/s, train/loss=17.90]
Epoch 0: | | 483/? [01:44<00:00, 4.61it/s, train/loss=17.90]
Epoch 0: | | 483/? [01:44<00:00, 4.61it/s, train/loss=1.110]
Epoch 0: | | 484/? [01:45<00:00, 4.61it/s, train/loss=1.110]
Epoch 0: | | 484/? [01:45<00:00, 4.61it/s, train/loss=32.30]
Epoch 0: | | 485/? [01:45<00:00, 4.62it/s, train/loss=32.30]
Epoch 0: | | 485/? [01:45<00:00, 4.62it/s, train/loss=1.080]
Epoch 0: | | 486/? [01:45<00:00, 4.61it/s, train/loss=1.080]
Epoch 0: | | 486/? [01:45<00:00, 4.61it/s, train/loss=22.40]
Epoch 0: | | 487/? [01:45<00:00, 4.62it/s, train/loss=22.40]
Epoch 0: | | 487/? [01:45<00:00, 4.62it/s, train/loss=1.080]
Epoch 0: | | 488/? [01:45<00:00, 4.62it/s, train/loss=1.080]
Epoch 0: | | 488/? [01:45<00:00, 4.62it/s, train/loss=19.40]
Epoch 0: | | 489/? [01:45<00:00, 4.63it/s, train/loss=19.40]
Epoch 0: | | 489/? [01:45<00:00, 4.63it/s, train/loss=1.080]
Epoch 0: | | 490/? [01:45<00:00, 4.62it/s, train/loss=1.080]
Epoch 0: | | 490/? [01:45<00:00, 4.62it/s, train/loss=22.90]
Epoch 0: | | 491/? [01:46<00:00, 4.63it/s, train/loss=22.90]
Epoch 0: | | 491/? [01:46<00:00, 4.63it/s, train/loss=1.080]
Epoch 0: | | 492/? [01:46<00:00, 4.63it/s, train/loss=1.080]
Epoch 0: | | 492/? [01:46<00:00, 4.63it/s, train/loss=24.60]
Epoch 0: | | 493/? [01:46<00:00, 4.64it/s, train/loss=24.60]
Epoch 0: | | 493/? [01:46<00:00, 4.64it/s, train/loss=1.080]
Epoch 0: | | 494/? [01:46<00:00, 4.63it/s, train/loss=1.080]
Epoch 0: | | 494/? [01:46<00:00, 4.63it/s, train/loss=29.80]
Epoch 0: | | 495/? [01:46<00:00, 4.64it/s, train/loss=29.80]
Epoch 0: | | 495/? [01:46<00:00, 4.64it/s, train/loss=1.100]
Epoch 0: | | 496/? [01:46<00:00, 4.64it/s, train/loss=1.100]
Epoch 0: | | 496/? [01:46<00:00, 4.64it/s, train/loss=31.80]
Epoch 0: | | 497/? [01:46<00:00, 4.65it/s, train/loss=31.80]
Epoch 0: | | 497/? [01:46<00:00, 4.65it/s, train/loss=1.130]
Epoch 0: | | 498/? [01:47<00:00, 4.64it/s, train/loss=1.130]
Epoch 0: | | 498/? [01:47<00:00, 4.64it/s, train/loss=11.90]
Epoch 0: | | 499/? [01:47<00:00, 4.65it/s, train/loss=11.90]
Epoch 0: | | 499/? [01:47<00:00, 4.65it/s, train/loss=1.140]
Epoch 0: | | 500/? [01:47<00:00, 4.65it/s, train/loss=1.140]
Epoch 0: | | 500/? [01:47<00:00, 4.65it/s, train/loss=31.60]
Epoch 0: | | 501/? [01:47<00:00, 4.66it/s, train/loss=31.60]
Epoch 0: | | 501/? [01:47<00:00, 4.66it/s, train/loss=1.140]
Epoch 0: | | 502/? [01:47<00:00, 4.65it/s, train/loss=1.140]
Epoch 0: | | 502/? [01:47<00:00, 4.65it/s, train/loss=56.30]
Epoch 0: | | 503/? [01:47<00:00, 4.66it/s, train/loss=56.30]
Epoch 0: | | 503/? [01:47<00:00, 4.66it/s, train/loss=1.150]
Epoch 0: | | 504/? [01:48<00:00, 4.66it/s, train/loss=1.150]
Epoch 0: | | 504/? [01:48<00:00, 4.66it/s, train/loss=45.80]
Epoch 0: | | 505/? [01:48<00:00, 4.67it/s, train/loss=45.80]
Epoch 0: | | 505/? [01:48<00:00, 4.67it/s, train/loss=1.150]
Epoch 0: | | 506/? [01:48<00:00, 4.66it/s, train/loss=1.150]
Epoch 0: | | 506/? [01:48<00:00, 4.66it/s, train/loss=10.50]
Epoch 0: | | 507/? [01:48<00:00, 4.67it/s, train/loss=10.50]
Epoch 0: | | 507/? [01:48<00:00, 4.67it/s, train/loss=1.150]
Epoch 0: | | 508/? [01:48<00:00, 4.67it/s, train/loss=1.150]
Epoch 0: | | 508/? [01:48<00:00, 4.67it/s, train/loss=33.40]
Epoch 0: | | 509/? [01:48<00:00, 4.68it/s, train/loss=33.40]
Epoch 0: | | 509/? [01:48<00:00, 4.68it/s, train/loss=1.140]
Epoch 0: | | 510/? [01:49<00:00, 4.67it/s, train/loss=1.140]
Epoch 0: | | 510/? [01:49<00:00, 4.67it/s, train/loss=16.90]
Epoch 0: | | 511/? [01:49<00:00, 4.68it/s, train/loss=16.90]
Epoch 0: | | 511/? [01:49<00:00, 4.68it/s, train/loss=1.140]
Epoch 0: | | 512/? [01:49<00:00, 4.68it/s, train/loss=1.140]
Epoch 0: | | 512/? [01:49<00:00, 4.68it/s, train/loss=26.30]
Epoch 0: | | 513/? [01:49<00:00, 4.69it/s, train/loss=26.30]
Epoch 0: | | 513/? [01:49<00:00, 4.69it/s, train/loss=1.150]
Epoch 0: | | 514/? [01:49<00:00, 4.69it/s, train/loss=1.150]
Epoch 0: | | 514/? [01:49<00:00, 4.68it/s, train/loss=15.90]
Epoch 0: | | 515/? [01:49<00:00, 4.69it/s, train/loss=15.90]
Epoch 0: | | 515/? [01:49<00:00, 4.69it/s, train/loss=1.170]
Epoch 0: | | 516/? [01:50<00:00, 4.69it/s, train/loss=1.170]
Epoch 0: | | 516/? [01:50<00:00, 4.69it/s, train/loss=29.20]
Epoch 0: | | 517/? [01:50<00:00, 4.70it/s, train/loss=29.20]
Epoch 0: | | 517/? [01:50<00:00, 4.70it/s, train/loss=1.210]
Epoch 0: | | 518/? [01:50<00:00, 4.69it/s, train/loss=1.210]
Epoch 0: | | 518/? [01:50<00:00, 4.69it/s, train/loss=35.40]
Epoch 0: | | 519/? [01:50<00:00, 4.70it/s, train/loss=35.40]
Epoch 0: | | 519/? [01:50<00:00, 4.70it/s, train/loss=1.210]
Epoch 0: | | 520/? [01:50<00:00, 4.70it/s, train/loss=1.210]
Epoch 0: | | 520/? [01:50<00:00, 4.70it/s, train/loss=31.80]
Epoch 0: | | 521/? [01:50<00:00, 4.71it/s, train/loss=31.80]
Epoch 0: | | 521/? [01:50<00:00, 4.71it/s, train/loss=1.160]
Epoch 0: | | 522/? [01:50<00:00, 4.70it/s, train/loss=1.160]
Epoch 0: | | 522/? [01:50<00:00, 4.70it/s, train/loss=28.70]
Epoch 0: | | 523/? [01:50<00:00, 4.71it/s, train/loss=28.70]
Epoch 0: | | 523/? [01:50<00:00, 4.71it/s, train/loss=1.140]
Epoch 0: | | 524/? [01:51<00:00, 4.71it/s, train/loss=1.140]
Epoch 0: | | 524/? [01:51<00:00, 4.71it/s, train/loss=26.10]
Epoch 0: | | 525/? [01:51<00:00, 4.72it/s, train/loss=26.10]
Epoch 0: | | 525/? [01:51<00:00, 4.72it/s, train/loss=1.160]
Epoch 0: | | 526/? [01:51<00:00, 4.71it/s, train/loss=1.160]
Epoch 0: | | 526/? [01:51<00:00, 4.71it/s, train/loss=21.50]
Epoch 0: | | 527/? [01:51<00:00, 4.72it/s, train/loss=21.50]
Epoch 0: | | 527/? [01:51<00:00, 4.72it/s, train/loss=1.210]
Epoch 0: | | 528/? [01:51<00:00, 4.72it/s, train/loss=1.210]
Epoch 0: | | 528/? [01:51<00:00, 4.72it/s, train/loss=27.90]
Epoch 0: | | 529/? [01:51<00:00, 4.73it/s, train/loss=27.90]
Epoch 0: | | 529/? [01:51<00:00, 4.73it/s, train/loss=1.250]
Epoch 0: | | 530/? [01:52<00:00, 4.72it/s, train/loss=1.250]
Epoch 0: | | 530/? [01:52<00:00, 4.72it/s, train/loss=14.70]
Epoch 0: | | 531/? [01:52<00:00, 4.73it/s, train/loss=14.70]
Epoch 0: | | 531/? [01:52<00:00, 4.73it/s, train/loss=1.250]
Epoch 0: | | 532/? [01:52<00:00, 4.73it/s, train/loss=1.250]
Epoch 0: | | 532/? [01:52<00:00, 4.73it/s, train/loss=23.20]
Epoch 0: | | 533/? [01:52<00:00, 4.74it/s, train/loss=23.20]
Epoch 0: | | 533/? [01:52<00:00, 4.74it/s, train/loss=1.240]
Epoch 0: | | 534/? [01:52<00:00, 4.73it/s, train/loss=1.240]
Epoch 0: | | 534/? [01:52<00:00, 4.73it/s, train/loss=12.80]
Epoch 0: | | 535/? [01:52<00:00, 4.74it/s, train/loss=12.80]
Epoch 0: | | 535/? [01:52<00:00, 4.74it/s, train/loss=1.230]
Epoch 0: | | 536/? [01:53<00:00, 4.74it/s, train/loss=1.230]
Epoch 0: | | 536/? [01:53<00:00, 4.74it/s, train/loss=44.10]
Epoch 0: | | 537/? [01:53<00:00, 4.75it/s, train/loss=44.10]
Epoch 0: | | 537/? [01:53<00:00, 4.75it/s, train/loss=1.210]
Epoch 0: | | 538/? [01:53<00:00, 4.74it/s, train/loss=1.210]
Epoch 0: | | 538/? [01:53<00:00, 4.74it/s, train/loss=16.80]
Epoch 0: | | 539/? [01:53<00:00, 4.75it/s, train/loss=16.80]
Epoch 0: | | 539/? [01:53<00:00, 4.75it/s, train/loss=1.200]
Epoch 0: | | 540/? [01:53<00:00, 4.75it/s, train/loss=1.200]
Epoch 0: | | 540/? [01:53<00:00, 4.75it/s, train/loss=16.80]
Epoch 0: | | 541/? [01:53<00:00, 4.76it/s, train/loss=16.80]
Epoch 0: | | 541/? [01:53<00:00, 4.76it/s, train/loss=1.190]
Epoch 0: | | 542/? [01:54<00:00, 4.75it/s, train/loss=1.190]
Epoch 0: | | 542/? [01:54<00:00, 4.75it/s, train/loss=17.30]
Epoch 0: | | 543/? [01:54<00:00, 4.76it/s, train/loss=17.30]
Epoch 0: | | 543/? [01:54<00:00, 4.76it/s, train/loss=1.170]
Epoch 0: | | 544/? [01:54<00:00, 4.76it/s, train/loss=1.170]
Epoch 0: | | 544/? [01:54<00:00, 4.76it/s, train/loss=12.40]
Epoch 0: | | 545/? [01:54<00:00, 4.76it/s, train/loss=12.40]
Epoch 0: | | 545/? [01:54<00:00, 4.76it/s, train/loss=1.170]
Epoch 0: | | 546/? [01:54<00:00, 4.76it/s, train/loss=1.170]
Epoch 0: | | 546/? [01:54<00:00, 4.76it/s, train/loss=25.30]
Epoch 0: | | 547/? [01:54<00:00, 4.76it/s, train/loss=25.30]
Epoch 0: | | 547/? [01:54<00:00, 4.76it/s, train/loss=1.150]
Epoch 0: | | 548/? [01:55<00:00, 4.76it/s, train/loss=1.150]
Epoch 0: | | 548/? [01:55<00:00, 4.76it/s, train/loss=25.90]
Epoch 0: | | 549/? [01:55<00:00, 4.76it/s, train/loss=25.90]
Epoch 0: | | 549/? [01:55<00:00, 4.76it/s, train/loss=1.110]
Epoch 0: | | 550/? [01:55<00:00, 4.76it/s, train/loss=1.110]
Epoch 0: | | 550/? [01:55<00:00, 4.76it/s, train/loss=17.80]
Epoch 0: | | 551/? [01:55<00:00, 4.77it/s, train/loss=17.80]
Epoch 0: | | 551/? [01:55<00:00, 4.77it/s, train/loss=1.070]
Epoch 0: | | 552/? [01:55<00:00, 4.77it/s, train/loss=1.070]
Epoch 0: | | 552/? [01:55<00:00, 4.77it/s, train/loss=36.40]
Epoch 0: | | 553/? [01:55<00:00, 4.77it/s, train/loss=36.40]
Epoch 0: | | 553/? [01:55<00:00, 4.77it/s, train/loss=1.030]
Epoch 0: | | 554/? [01:56<00:00, 4.77it/s, train/loss=1.030]
Epoch 0: | | 554/? [01:56<00:00, 4.77it/s, train/loss=16.90]
Epoch 0: | | 555/? [01:56<00:00, 4.78it/s, train/loss=16.90]
Epoch 0: | | 555/? [01:56<00:00, 4.78it/s, train/loss=1.020]
Epoch 0: | | 556/? [01:56<00:00, 4.77it/s, train/loss=1.020]
Epoch 0: | | 556/? [01:56<00:00, 4.77it/s, train/loss=20.60]
Epoch 0: | | 557/? [01:56<00:00, 4.78it/s, train/loss=20.60]
Epoch 0: | | 557/? [01:56<00:00, 4.78it/s, train/loss=1.010]
Epoch 0: | | 558/? [01:56<00:00, 4.78it/s, train/loss=1.010]
Epoch 0: | | 558/? [01:56<00:00, 4.78it/s, train/loss=28.10]
Epoch 0: | | 559/? [01:56<00:00, 4.78it/s, train/loss=28.10]
Epoch 0: | | 559/? [01:56<00:00, 4.78it/s, train/loss=1.020]
Epoch 0: | | 560/? [01:57<00:00, 4.77it/s, train/loss=1.020]
Epoch 0: | | 560/? [01:57<00:00, 4.77it/s, train/loss=37.20]
Epoch 0: | | 561/? [01:57<00:00, 4.78it/s, train/loss=37.20]
Epoch 0: | | 561/? [01:57<00:00, 4.78it/s, train/loss=1.030]
Epoch 0: | | 562/? [01:57<00:00, 4.77it/s, train/loss=1.030]
Epoch 0: | | 562/? [01:57<00:00, 4.77it/s, train/loss=10.80]
Epoch 0: | | 563/? [01:57<00:00, 4.78it/s, train/loss=10.80]
Epoch 0: | | 563/? [01:57<00:00, 4.78it/s, train/loss=1.050]
Epoch 0: | | 564/? [01:58<00:00, 4.77it/s, train/loss=1.050]
Epoch 0: | | 564/? [01:58<00:00, 4.77it/s, train/loss=23.20]
Epoch 0: | | 565/? [01:58<00:00, 4.77it/s, train/loss=23.20]
Epoch 0: | | 565/? [01:58<00:00, 4.77it/s, train/loss=1.080]
Epoch 0: | | 566/? [01:58<00:00, 4.77it/s, train/loss=1.080]
Epoch 0: | | 566/? [01:58<00:00, 4.77it/s, train/loss=23.40]
Epoch 0: | | 567/? [01:58<00:00, 4.77it/s, train/loss=23.40]
Epoch 0: | | 567/? [01:58<00:00, 4.77it/s, train/loss=1.130]
Epoch 0: | | 568/? [01:59<00:00, 4.77it/s, train/loss=1.130]
Epoch 0: | | 568/? [01:59<00:00, 4.77it/s, train/loss=53.80]
Epoch 0: | | 569/? [01:59<00:00, 4.77it/s, train/loss=53.80]
Epoch 0: | | 569/? [01:59<00:00, 4.77it/s, train/loss=1.140]
Epoch 0: | | 570/? [01:59<00:00, 4.77it/s, train/loss=1.140]
Epoch 0: | | 570/? [01:59<00:00, 4.77it/s, train/loss=18.30]
Epoch 0: | | 571/? [01:59<00:00, 4.77it/s, train/loss=18.30]
Epoch 0: | | 571/? [01:59<00:00, 4.77it/s, train/loss=1.120]
Epoch 0: | | 572/? [02:00<00:00, 4.76it/s, train/loss=1.120]
Epoch 0: | | 572/? [02:00<00:00, 4.76it/s, train/loss=11.50]
Epoch 0: | | 573/? [02:00<00:00, 4.77it/s, train/loss=11.50]
Epoch 0: | | 573/? [02:00<00:00, 4.77it/s, train/loss=1.090]
Epoch 0: | | 574/? [02:00<00:00, 4.76it/s, train/loss=1.090]
Epoch 0: | | 574/? [02:00<00:00, 4.76it/s, train/loss=15.20]
Epoch 0: | | 575/? [02:00<00:00, 4.77it/s, train/loss=15.20]
Epoch 0: | | 575/? [02:00<00:00, 4.77it/s, train/loss=1.060]
Epoch 0: | | 576/? [02:00<00:00, 4.76it/s, train/loss=1.060]
Epoch 0: | | 576/? [02:00<00:00, 4.76it/s, train/loss=33.00]
Epoch 0: | | 577/? [02:01<00:00, 4.77it/s, train/loss=33.00]
Epoch 0: | | 577/? [02:01<00:00, 4.77it/s, train/loss=1.060]
Epoch 0: | | 578/? [02:01<00:00, 4.76it/s, train/loss=1.060]
Epoch 0: | | 578/? [02:01<00:00, 4.76it/s, train/loss=21.20]
Epoch 0: | | 579/? [02:01<00:00, 4.76it/s, train/loss=21.20]
Epoch 0: | | 579/? [02:01<00:00, 4.76it/s, train/loss=1.090]
Epoch 0: | | 580/? [02:01<00:00, 4.76it/s, train/loss=1.090]
Epoch 0: | | 580/? [02:01<00:00, 4.76it/s, train/loss=83.40]
Epoch 0: | | 581/? [02:02<00:00, 4.76it/s, train/loss=83.40]
Epoch 0: | | 581/? [02:02<00:00, 4.76it/s, train/loss=1.160]
Epoch 0: | | 582/? [02:02<00:00, 4.76it/s, train/loss=1.160]
Epoch 0: | | 582/? [02:02<00:00, 4.76it/s, train/loss=19.10]
Epoch 0: | | 583/? [02:02<00:00, 4.76it/s, train/loss=19.10]
Epoch 0: | | 583/? [02:02<00:00, 4.76it/s, train/loss=1.240]
Epoch 0: | | 584/? [02:02<00:00, 4.75it/s, train/loss=1.240]
Epoch 0: | | 584/? [02:02<00:00, 4.75it/s, train/loss=60.20]
Epoch 0: | | 585/? [02:02<00:00, 4.76it/s, train/loss=60.20]
Epoch 0: | | 585/? [02:02<00:00, 4.76it/s, train/loss=1.230]
Epoch 0: | | 586/? [02:03<00:00, 4.75it/s, train/loss=1.230]
Epoch 0: | | 586/? [02:03<00:00, 4.75it/s, train/loss=21.30]
Epoch 0: | | 587/? [02:03<00:00, 4.76it/s, train/loss=21.30]
Epoch 0: | | 587/? [02:03<00:00, 4.76it/s, train/loss=1.210]
Epoch 0: | | 588/? [02:03<00:00, 4.75it/s, train/loss=1.210]
Epoch 0: | | 588/? [02:03<00:00, 4.75it/s, train/loss=32.10]
Epoch 0: | | 589/? [02:03<00:00, 4.76it/s, train/loss=32.10]
Epoch 0: | | 589/? [02:03<00:00, 4.76it/s, train/loss=1.240]
Epoch 0: | | 590/? [02:04<00:00, 4.75it/s, train/loss=1.240]
Epoch 0: | | 590/? [02:04<00:00, 4.75it/s, train/loss=28.90]
Epoch 0: | | 591/? [02:04<00:00, 4.76it/s, train/loss=28.90]
Epoch 0: | | 591/? [02:04<00:00, 4.76it/s, train/loss=1.270]
Epoch 0: | | 592/? [02:04<00:00, 4.75it/s, train/loss=1.270]
Epoch 0: | | 592/? [02:04<00:00, 4.75it/s, train/loss=12.50]
Epoch 0: | | 593/? [02:04<00:00, 4.76it/s, train/loss=12.50]
Epoch 0: | | 593/? [02:04<00:00, 4.76it/s, train/loss=1.260]
Epoch 0: | | 594/? [02:04<00:00, 4.76it/s, train/loss=1.260]
Epoch 0: | | 594/? [02:04<00:00, 4.76it/s, train/loss=24.00]
Epoch 0: | | 595/? [02:04<00:00, 4.77it/s, train/loss=24.00]
Epoch 0: | | 595/? [02:04<00:00, 4.77it/s, train/loss=1.230]
Epoch 0: | | 596/? [02:05<00:00, 4.76it/s, train/loss=1.230]
Epoch 0: | | 596/? [02:05<00:00, 4.76it/s, train/loss=15.00]
Epoch 0: | | 597/? [02:05<00:00, 4.77it/s, train/loss=15.00]
Epoch 0: | | 597/? [02:05<00:00, 4.77it/s, train/loss=1.210]
Epoch 0: | | 598/? [02:05<00:00, 4.77it/s, train/loss=1.210]
Epoch 0: | | 598/? [02:05<00:00, 4.77it/s, train/loss=10.30]
Epoch 0: | | 599/? [02:05<00:00, 4.77it/s, train/loss=10.30]
Epoch 0: | | 599/? [02:05<00:00, 4.77it/s, train/loss=1.200]
Epoch 0: | | 600/? [02:05<00:00, 4.77it/s, train/loss=1.200]
Epoch 0: | | 600/? [02:05<00:00, 4.77it/s, train/loss=21.10]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:06, 5.79it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:06, 5.50it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:06, 5.39it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:06, 5.34it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:06, 5.42it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:01<00:06, 5.44it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:01<00:06, 5.47it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:01<00:05, 5.50it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:01<00:05, 5.53it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:01<00:05, 5.57it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:01<00:05, 5.60it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:02<00:04, 5.62it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:02<00:04, 5.60it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:02<00:04, 5.58it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:02<00:04, 5.55it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:02<00:04, 5.53it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:03<00:04, 5.51it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:03<00:04, 5.49it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:03<00:03, 5.48it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:03<00:03, 5.47it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:03<00:03, 5.46it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:04<00:03, 5.46it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:04<00:03, 5.47it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:04<00:02, 5.46it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:04<00:02, 5.46it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:04<00:02, 5.46it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:04<00:02, 5.45it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:05<00:02, 5.45it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:05<00:02, 5.45it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:05<00:01, 5.45it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:05<00:01, 5.45it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:05<00:01, 5.46it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:06<00:01, 5.46it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:06<00:01, 5.48it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:06<00:00, 5.49it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:06<00:00, 5.48it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:06<00:00, 5.48it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:06<00:00, 5.49it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:07<00:00, 5.50it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:07<00:00, 5.51it/s][A
[A
Epoch 0: | | 600/? [02:13<00:00, 4.48it/s, train/loss=21.10]
Epoch 0: | | 601/? [02:14<00:00, 4.47it/s, train/loss=21.10]
Epoch 0: | | 601/? [02:14<00:00, 4.47it/s, train/loss=1.190]
Epoch 0: | | 602/? [02:14<00:00, 4.47it/s, train/loss=1.190]
Epoch 0: | | 602/? [02:14<00:00, 4.47it/s, train/loss=34.40]
Epoch 0: | | 603/? [02:14<00:00, 4.48it/s, train/loss=34.40]
Epoch 0: | | 603/? [02:14<00:00, 4.48it/s, train/loss=1.200]
Epoch 0: | | 604/? [02:14<00:00, 4.47it/s, train/loss=1.200]
Epoch 0: | | 604/? [02:14<00:00, 4.47it/s, train/loss=17.70]
Epoch 0: | | 605/? [02:15<00:00, 4.48it/s, train/loss=17.70]
Epoch 0: | | 605/? [02:15<00:00, 4.48it/s, train/loss=1.220]
Epoch 0: | | 606/? [02:15<00:00, 4.48it/s, train/loss=1.220]
Epoch 0: | | 606/? [02:15<00:00, 4.48it/s, train/loss=21.60]
Epoch 0: | | 607/? [02:15<00:00, 4.49it/s, train/loss=21.60]
Epoch 0: | | 607/? [02:15<00:00, 4.49it/s, train/loss=1.190]
Epoch 0: | | 608/? [02:15<00:00, 4.48it/s, train/loss=1.190]
Epoch 0: | | 608/? [02:15<00:00, 4.48it/s, train/loss=21.10]
Epoch 0: | | 609/? [02:15<00:00, 4.49it/s, train/loss=21.10]
Epoch 0: | | 609/? [02:15<00:00, 4.49it/s, train/loss=1.120]
Epoch 0: | | 610/? [02:15<00:00, 4.49it/s, train/loss=1.120]
Epoch 0: | | 610/? [02:15<00:00, 4.49it/s, train/loss=23.20]
Epoch 0: | | 611/? [02:15<00:00, 4.49it/s, train/loss=23.20]
Epoch 0: | | 611/? [02:15<00:00, 4.49it/s, train/loss=1.070]
Epoch 0: | | 612/? [02:16<00:00, 4.49it/s, train/loss=1.070]
Epoch 0: | | 612/? [02:16<00:00, 4.49it/s, train/loss=24.80]
Epoch 0: | | 613/? [02:16<00:00, 4.50it/s, train/loss=24.80]
Epoch 0: | | 613/? [02:16<00:00, 4.50it/s, train/loss=1.040]
Epoch 0: | | 614/? [02:16<00:00, 4.50it/s, train/loss=1.040]
Epoch 0: | | 614/? [02:16<00:00, 4.50it/s, train/loss=12.10]
Epoch 0: | | 615/? [02:16<00:00, 4.50it/s, train/loss=12.10]
Epoch 0: | | 615/? [02:16<00:00, 4.50it/s, train/loss=1.030]
Epoch 0: | | 616/? [02:16<00:00, 4.50it/s, train/loss=1.030]
Epoch 0: | | 616/? [02:16<00:00, 4.50it/s, train/loss=43.70]
Epoch 0: | | 617/? [02:16<00:00, 4.51it/s, train/loss=43.70]
Epoch 0: | | 617/? [02:16<00:00, 4.51it/s, train/loss=1.050]
Epoch 0: | | 618/? [02:17<00:00, 4.51it/s, train/loss=1.050]
Epoch 0: | | 618/? [02:17<00:00, 4.51it/s, train/loss=19.50]
Epoch 0: | | 619/? [02:17<00:00, 4.51it/s, train/loss=19.50]
Epoch 0: | | 619/? [02:17<00:00, 4.51it/s, train/loss=1.090]
Epoch 0: | | 620/? [02:17<00:00, 4.51it/s, train/loss=1.090]
Epoch 0: | | 620/? [02:17<00:00, 4.51it/s, train/loss=31.00]
Epoch 0: | | 621/? [02:17<00:00, 4.52it/s, train/loss=31.00]
Epoch 0: | | 621/? [02:17<00:00, 4.52it/s, train/loss=1.130]
Epoch 0: | | 622/? [02:17<00:00, 4.52it/s, train/loss=1.130]
Epoch 0: | | 622/? [02:17<00:00, 4.52it/s, train/loss=18.60]
Epoch 0: | | 623/? [02:17<00:00, 4.52it/s, train/loss=18.60]
Epoch 0: | | 623/? [02:17<00:00, 4.52it/s, train/loss=1.170]
Epoch 0: | | 624/? [02:18<00:00, 4.52it/s, train/loss=1.170]
Epoch 0: | | 624/? [02:18<00:00, 4.52it/s, train/loss=16.00]
Epoch 0: | | 625/? [02:18<00:00, 4.53it/s, train/loss=16.00]
Epoch 0: | | 625/? [02:18<00:00, 4.53it/s, train/loss=1.190]
Epoch 0: | | 626/? [02:18<00:00, 4.52it/s, train/loss=1.190]
Epoch 0: | | 626/? [02:18<00:00, 4.52it/s, train/loss=38.30]
Epoch 0: | | 627/? [02:18<00:00, 4.53it/s, train/loss=38.30]
Epoch 0: | | 627/? [02:18<00:00, 4.53it/s, train/loss=1.220]
Epoch 0: | | 628/? [02:18<00:00, 4.53it/s, train/loss=1.220]
Epoch 0: | | 628/? [02:18<00:00, 4.53it/s, train/loss=27.00]
Epoch 0: | | 629/? [02:18<00:00, 4.53it/s, train/loss=27.00]
Epoch 0: | | 629/? [02:18<00:00, 4.53it/s, train/loss=1.220]
Epoch 0: | | 630/? [02:18<00:00, 4.53it/s, train/loss=1.220]
Epoch 0: | | 630/? [02:18<00:00, 4.53it/s, train/loss=23.60]
Epoch 0: | | 631/? [02:19<00:00, 4.54it/s, train/loss=23.60]
Epoch 0: | | 631/? [02:19<00:00, 4.54it/s, train/loss=1.170]
Epoch 0: | | 632/? [02:19<00:00, 4.54it/s, train/loss=1.170]
Epoch 0: | | 632/? [02:19<00:00, 4.54it/s, train/loss=9.630]
Epoch 0: | | 633/? [02:19<00:00, 4.54it/s, train/loss=9.630]
Epoch 0: | | 633/? [02:19<00:00, 4.54it/s, train/loss=1.140]
Epoch 0: | | 634/? [02:19<00:00, 4.54it/s, train/loss=1.140]
Epoch 0: | | 634/? [02:19<00:00, 4.54it/s, train/loss=78.00]
Epoch 0: | | 635/? [02:19<00:00, 4.55it/s, train/loss=78.00]
Epoch 0: | | 635/? [02:19<00:00, 4.55it/s, train/loss=1.120]
Epoch 0: | | 636/? [02:19<00:00, 4.55it/s, train/loss=1.120]
Epoch 0: | | 636/? [02:19<00:00, 4.55it/s, train/loss=11.30]
Epoch 0: | | 637/? [02:19<00:00, 4.55it/s, train/loss=11.30]
Epoch 0: | | 637/? [02:19<00:00, 4.55it/s, train/loss=1.110]
Epoch 0: | | 638/? [02:20<00:00, 4.55it/s, train/loss=1.110]
Epoch 0: | | 638/? [02:20<00:00, 4.55it/s, train/loss=18.90]
Epoch 0: | | 639/? [02:20<00:00, 4.56it/s, train/loss=18.90]
Epoch 0: | | 639/? [02:20<00:00, 4.56it/s, train/loss=1.110]
Epoch 0: | | 640/? [02:20<00:00, 4.55it/s, train/loss=1.110]
Epoch 0: | | 640/? [02:20<00:00, 4.55it/s, train/loss=26.10]
Epoch 0: | | 641/? [02:20<00:00, 4.56it/s, train/loss=26.10]
Epoch 0: | | 641/? [02:20<00:00, 4.56it/s, train/loss=1.100]
Epoch 0: | | 642/? [02:21<00:00, 4.55it/s, train/loss=1.100]
Epoch 0: | | 642/? [02:21<00:00, 4.55it/s, train/loss=14.20]
Epoch 0: | | 643/? [02:21<00:00, 4.56it/s, train/loss=14.20]
Epoch 0: | | 643/? [02:21<00:00, 4.56it/s, train/loss=1.080]
Epoch 0: | | 644/? [02:21<00:00, 4.55it/s, train/loss=1.080]
Epoch 0: | | 644/? [02:21<00:00, 4.55it/s, train/loss=40.70]
Epoch 0: | | 645/? [02:21<00:00, 4.56it/s, train/loss=40.70]
Epoch 0: | | 645/? [02:21<00:00, 4.56it/s, train/loss=1.070]
Epoch 0: | | 646/? [02:21<00:00, 4.55it/s, train/loss=1.070]
Epoch 0: | | 646/? [02:21<00:00, 4.55it/s, train/loss=32.30]
Epoch 0: | | 647/? [02:21<00:00, 4.56it/s, train/loss=32.30]
Epoch 0: | | 647/? [02:21<00:00, 4.56it/s, train/loss=1.080]
Epoch 0: | | 648/? [02:22<00:00, 4.56it/s, train/loss=1.080]
Epoch 0: | | 648/? [02:22<00:00, 4.56it/s, train/loss=38.60]
Epoch 0: | | 649/? [02:22<00:00, 4.56it/s, train/loss=38.60]
Epoch 0: | | 649/? [02:22<00:00, 4.56it/s, train/loss=1.080]
Epoch 0: | | 650/? [02:22<00:00, 4.56it/s, train/loss=1.080]
Epoch 0: | | 650/? [02:22<00:00, 4.56it/s, train/loss=26.00]
Epoch 0: | | 651/? [02:22<00:00, 4.57it/s, train/loss=26.00]
Epoch 0: | | 651/? [02:22<00:00, 4.57it/s, train/loss=1.080]
Epoch 0: | | 652/? [02:22<00:00, 4.57it/s, train/loss=1.080]
Epoch 0: | | 652/? [02:22<00:00, 4.57it/s, train/loss=40.00]
Epoch 0: | | 653/? [02:22<00:00, 4.57it/s, train/loss=40.00]
Epoch 0: | | 653/? [02:22<00:00, 4.57it/s, train/loss=1.080]
Epoch 0: | | 654/? [02:23<00:00, 4.57it/s, train/loss=1.080]
Epoch 0: | | 654/? [02:23<00:00, 4.57it/s, train/loss=32.60]
Epoch 0: | | 655/? [02:23<00:00, 4.58it/s, train/loss=32.60]
Epoch 0: | | 655/? [02:23<00:00, 4.58it/s, train/loss=1.110]
Epoch 0: | | 656/? [02:23<00:00, 4.57it/s, train/loss=1.110]
Epoch 0: | | 656/? [02:23<00:00, 4.57it/s, train/loss=13.30]
Epoch 0: | | 657/? [02:23<00:00, 4.58it/s, train/loss=13.30]
Epoch 0: | | 657/? [02:23<00:00, 4.58it/s, train/loss=1.140]
Epoch 0: | | 658/? [02:23<00:00, 4.58it/s, train/loss=1.140]
Epoch 0: | | 658/? [02:23<00:00, 4.58it/s, train/loss=41.00]
Epoch 0: | | 659/? [02:23<00:00, 4.58it/s, train/loss=41.00]
Epoch 0: | | 659/? [02:23<00:00, 4.58it/s, train/loss=1.150]
Epoch 0: | | 660/? [02:24<00:00, 4.58it/s, train/loss=1.150]
Epoch 0: | | 660/? [02:24<00:00, 4.58it/s, train/loss=13.90]
Epoch 0: | | 661/? [02:24<00:00, 4.59it/s, train/loss=13.90]
Epoch 0: | | 661/? [02:24<00:00, 4.59it/s, train/loss=1.170]
Epoch 0: | | 662/? [02:24<00:00, 4.59it/s, train/loss=1.170]
Epoch 0: | | 662/? [02:24<00:00, 4.59it/s, train/loss=81.40]
Epoch 0: | | 663/? [02:24<00:00, 4.59it/s, train/loss=81.40]
Epoch 0: | | 663/? [02:24<00:00, 4.59it/s, train/loss=1.220]
Epoch 0: | | 664/? [02:24<00:00, 4.59it/s, train/loss=1.220]
Epoch 0: | | 664/? [02:24<00:00, 4.59it/s, train/loss=12.20]
Epoch 0: | | 665/? [02:24<00:00, 4.60it/s, train/loss=12.20]
Epoch 0: | | 665/? [02:24<00:00, 4.60it/s, train/loss=1.240]
Epoch 0: | | 666/? [02:24<00:00, 4.59it/s, train/loss=1.240]
Epoch 0: | | 666/? [02:24<00:00, 4.59it/s, train/loss=26.10]
Epoch 0: | | 667/? [02:24<00:00, 4.60it/s, train/loss=26.10]
Epoch 0: | | 667/? [02:24<00:00, 4.60it/s, train/loss=1.150]
Epoch 0: | | 668/? [02:25<00:00, 4.60it/s, train/loss=1.150]
Epoch 0: | | 668/? [02:25<00:00, 4.60it/s, train/loss=38.30]
Epoch 0: | | 669/? [02:25<00:00, 4.60it/s, train/loss=38.30]
Epoch 0: | | 669/? [02:25<00:00, 4.60it/s, train/loss=1.090]
Epoch 0: | | 670/? [02:25<00:00, 4.60it/s, train/loss=1.090]
Epoch 0: | | 670/? [02:25<00:00, 4.60it/s, train/loss=25.60]
Epoch 0: | | 671/? [02:25<00:00, 4.61it/s, train/loss=25.60]
Epoch 0: | | 671/? [02:25<00:00, 4.61it/s, train/loss=1.060]
Epoch 0: | | 672/? [02:25<00:00, 4.61it/s, train/loss=1.060]
Epoch 0: | | 672/? [02:25<00:00, 4.61it/s, train/loss=14.40]
Epoch 0: | | 673/? [02:25<00:00, 4.61it/s, train/loss=14.40]
Epoch 0: | | 673/? [02:25<00:00, 4.61it/s, train/loss=1.060]
Epoch 0: | | 674/? [02:26<00:00, 4.61it/s, train/loss=1.060]
Epoch 0: | | 674/? [02:26<00:00, 4.61it/s, train/loss=20.00]
Epoch 0: | | 675/? [02:26<00:00, 4.62it/s, train/loss=20.00]
Epoch 0: | | 675/? [02:26<00:00, 4.62it/s, train/loss=1.060]
Epoch 0: | | 676/? [02:26<00:00, 4.61it/s, train/loss=1.060]
Epoch 0: | | 676/? [02:26<00:00, 4.61it/s, train/loss=18.30]
Epoch 0: | | 677/? [02:26<00:00, 4.62it/s, train/loss=18.30]
Epoch 0: | | 677/? [02:26<00:00, 4.62it/s, train/loss=1.060]
Epoch 0: | | 678/? [02:26<00:00, 4.62it/s, train/loss=1.060]
Epoch 0: | | 678/? [02:26<00:00, 4.62it/s, train/loss=46.40]
Epoch 0: | | 679/? [02:26<00:00, 4.62it/s, train/loss=46.40]
Epoch 0: | | 679/? [02:26<00:00, 4.62it/s, train/loss=1.050]
Epoch 0: | | 680/? [02:27<00:00, 4.62it/s, train/loss=1.050]
Epoch 0: | | 680/? [02:27<00:00, 4.62it/s, train/loss=14.70]
Epoch 0: | | 681/? [02:27<00:00, 4.63it/s, train/loss=14.70]
Epoch 0: | | 681/? [02:27<00:00, 4.63it/s, train/loss=1.050]
Epoch 0: | | 682/? [02:27<00:00, 4.63it/s, train/loss=1.050]
Epoch 0: | | 682/? [02:27<00:00, 4.63it/s, train/loss=29.90]
Epoch 0: | | 683/? [02:27<00:00, 4.63it/s, train/loss=29.90]
Epoch 0: | | 683/? [02:27<00:00, 4.63it/s, train/loss=1.050]
Epoch 0: | | 684/? [02:27<00:00, 4.63it/s, train/loss=1.050]
Epoch 0: | | 684/? [02:27<00:00, 4.63it/s, train/loss=20.00]
Epoch 0: | | 685/? [02:27<00:00, 4.64it/s, train/loss=20.00]
Epoch 0: | | 685/? [02:27<00:00, 4.64it/s, train/loss=1.030]
Epoch 0: | | 686/? [02:28<00:00, 4.63it/s, train/loss=1.030]
Epoch 0: | | 686/? [02:28<00:00, 4.63it/s, train/loss=23.60]
Epoch 0: | | 687/? [02:28<00:00, 4.64it/s, train/loss=23.60]
Epoch 0: | | 687/? [02:28<00:00, 4.64it/s, train/loss=1.010]
Epoch 0: | | 688/? [02:28<00:00, 4.64it/s, train/loss=1.010]
Epoch 0: | | 688/? [02:28<00:00, 4.64it/s, train/loss=18.60]
Epoch 0: | | 689/? [02:28<00:00, 4.64it/s, train/loss=18.60]
Epoch 0: | | 689/? [02:28<00:00, 4.64it/s, train/loss=0.995]
Epoch 0: | | 690/? [02:28<00:00, 4.64it/s, train/loss=0.995]
Epoch 0: | | 690/? [02:28<00:00, 4.64it/s, train/loss=21.90]
Epoch 0: | | 691/? [02:28<00:00, 4.65it/s, train/loss=21.90]
Epoch 0: | | 691/? [02:28<00:00, 4.65it/s, train/loss=0.975]
Epoch 0: | | 692/? [02:28<00:00, 4.65it/s, train/loss=0.975]
Epoch 0: | | 692/? [02:28<00:00, 4.65it/s, train/loss=37.90]
Epoch 0: | | 693/? [02:28<00:00, 4.65it/s, train/loss=37.90]
Epoch 0: | | 693/? [02:28<00:00, 4.65it/s, train/loss=0.958]
Epoch 0: | | 694/? [02:29<00:00, 4.65it/s, train/loss=0.958]
Epoch 0: | | 694/? [02:29<00:00, 4.65it/s, train/loss=23.10]
Epoch 0: | | 695/? [02:29<00:00, 4.66it/s, train/loss=23.10]
Epoch 0: | | 695/? [02:29<00:00, 4.66it/s, train/loss=0.954]
Epoch 0: | | 696/? [02:29<00:00, 4.65it/s, train/loss=0.954]
Epoch 0: | | 696/? [02:29<00:00, 4.65it/s, train/loss=32.60]
Epoch 0: | | 697/? [02:29<00:00, 4.66it/s, train/loss=32.60]
Epoch 0: | | 697/? [02:29<00:00, 4.66it/s, train/loss=0.965]
Epoch 0: | | 698/? [02:29<00:00, 4.66it/s, train/loss=0.965]
Epoch 0: | | 698/? [02:29<00:00, 4.66it/s, train/loss=23.20]
Epoch 0: | | 699/? [02:29<00:00, 4.66it/s, train/loss=23.20]
Epoch 0: | | 699/? [02:29<00:00, 4.66it/s, train/loss=0.967]
Epoch 0: | | 700/? [02:30<00:00, 4.66it/s, train/loss=0.967]
Epoch 0: | | 700/? [02:30<00:00, 4.66it/s, train/loss=41.20]
Epoch 0: | | 701/? [02:30<00:00, 4.67it/s, train/loss=41.20]
Epoch 0: | | 701/? [02:30<00:00, 4.67it/s, train/loss=0.955]
Epoch 0: | | 702/? [02:30<00:00, 4.67it/s, train/loss=0.955]
Epoch 0: | | 702/? [02:30<00:00, 4.67it/s, train/loss=24.60]
Epoch 0: | | 703/? [02:30<00:00, 4.67it/s, train/loss=24.60]
Epoch 0: | | 703/? [02:30<00:00, 4.67it/s, train/loss=0.931]
Epoch 0: | | 704/? [02:30<00:00, 4.67it/s, train/loss=0.931]
Epoch 0: | | 704/? [02:30<00:00, 4.67it/s, train/loss=8.580]
Epoch 0: | | 705/? [02:30<00:00, 4.68it/s, train/loss=8.580]
Epoch 0: | | 705/? [02:30<00:00, 4.68it/s, train/loss=0.905]
Epoch 0: | | 706/? [02:31<00:00, 4.67it/s, train/loss=0.905]
Epoch 0: | | 706/? [02:31<00:00, 4.67it/s, train/loss=20.60]
Epoch 0: | | 707/? [02:31<00:00, 4.68it/s, train/loss=20.60]
Epoch 0: | | 707/? [02:31<00:00, 4.68it/s, train/loss=0.894]
Epoch 0: | | 708/? [02:31<00:00, 4.68it/s, train/loss=0.894]
Epoch 0: | | 708/? [02:31<00:00, 4.68it/s, train/loss=23.60]
Epoch 0: | | 709/? [02:31<00:00, 4.68it/s, train/loss=23.60]
Epoch 0: | | 709/? [02:31<00:00, 4.68it/s, train/loss=0.883]
Epoch 0: | | 710/? [02:31<00:00, 4.68it/s, train/loss=0.883]
Epoch 0: | | 710/? [02:31<00:00, 4.68it/s, train/loss=14.50]
Epoch 0: | | 711/? [02:31<00:00, 4.68it/s, train/loss=14.50]
Epoch 0: | | 711/? [02:31<00:00, 4.68it/s, train/loss=0.874]
Epoch 0: | | 712/? [02:32<00:00, 4.68it/s, train/loss=0.874]
Epoch 0: | | 712/? [02:32<00:00, 4.68it/s, train/loss=16.80]
Epoch 0: | | 713/? [02:32<00:00, 4.68it/s, train/loss=16.80]
Epoch 0: | | 713/? [02:32<00:00, 4.68it/s, train/loss=0.883]
Epoch 0: | | 714/? [02:32<00:00, 4.68it/s, train/loss=0.883]
Epoch 0: | | 714/? [02:32<00:00, 4.68it/s, train/loss=28.60]
Epoch 0: | | 715/? [02:32<00:00, 4.68it/s, train/loss=28.60]
Epoch 0: | | 715/? [02:32<00:00, 4.68it/s, train/loss=0.896]
Epoch 0: | | 716/? [02:33<00:00, 4.68it/s, train/loss=0.896]
Epoch 0: | | 716/? [02:33<00:00, 4.68it/s, train/loss=13.50]
Epoch 0: | | 717/? [02:33<00:00, 4.68it/s, train/loss=13.50]
Epoch 0: | | 717/? [02:33<00:00, 4.68it/s, train/loss=0.912]
Epoch 0: | | 718/? [02:33<00:00, 4.68it/s, train/loss=0.912]
Epoch 0: | | 718/? [02:33<00:00, 4.68it/s, train/loss=24.30]
Epoch 0: | | 719/? [02:33<00:00, 4.69it/s, train/loss=24.30]
Epoch 0: | | 719/? [02:33<00:00, 4.69it/s, train/loss=0.939]
Epoch 0: | | 720/? [02:33<00:00, 4.68it/s, train/loss=0.939]
Epoch 0: | | 720/? [02:33<00:00, 4.68it/s, train/loss=27.00]
Epoch 0: | | 721/? [02:33<00:00, 4.69it/s, train/loss=27.00]
Epoch 0: | | 721/? [02:33<00:00, 4.69it/s, train/loss=0.974]
Epoch 0: | | 722/? [02:34<00:00, 4.69it/s, train/loss=0.974]
Epoch 0: | | 722/? [02:34<00:00, 4.69it/s, train/loss=36.20]
Epoch 0: | | 723/? [02:34<00:00, 4.69it/s, train/loss=36.20]
Epoch 0: | | 723/? [02:34<00:00, 4.69it/s, train/loss=0.974]
Epoch 0: | | 724/? [02:34<00:00, 4.69it/s, train/loss=0.974]
Epoch 0: | | 724/? [02:34<00:00, 4.69it/s, train/loss=20.80]
Epoch 0: | | 725/? [02:34<00:00, 4.70it/s, train/loss=20.80]
Epoch 0: | | 725/? [02:34<00:00, 4.70it/s, train/loss=0.970]
Epoch 0: | | 726/? [02:34<00:00, 4.69it/s, train/loss=0.970]
Epoch 0: | | 726/? [02:34<00:00, 4.69it/s, train/loss=20.00]
Epoch 0: | | 727/? [02:34<00:00, 4.70it/s, train/loss=20.00]
Epoch 0: | | 727/? [02:34<00:00, 4.70it/s, train/loss=0.968]
Epoch 0: | | 728/? [02:34<00:00, 4.70it/s, train/loss=0.968]
Epoch 0: | | 728/? [02:34<00:00, 4.70it/s, train/loss=12.10]
Epoch 0: | | 729/? [02:34<00:00, 4.70it/s, train/loss=12.10]
Epoch 0: | | 729/? [02:34<00:00, 4.70it/s, train/loss=0.960]
Epoch 0: | | 730/? [02:35<00:00, 4.70it/s, train/loss=0.960]
Epoch 0: | | 730/? [02:35<00:00, 4.70it/s, train/loss=19.20]
Epoch 0: | | 731/? [02:35<00:00, 4.71it/s, train/loss=19.20]
Epoch 0: | | 731/? [02:35<00:00, 4.71it/s, train/loss=0.948]
Epoch 0: | | 732/? [02:35<00:00, 4.71it/s, train/loss=0.948]
Epoch 0: | | 732/? [02:35<00:00, 4.71it/s, train/loss=18.60]
Epoch 0: | | 733/? [02:35<00:00, 4.71it/s, train/loss=18.60]
Epoch 0: | | 733/? [02:35<00:00, 4.71it/s, train/loss=0.951]
Epoch 0: | | 734/? [02:35<00:00, 4.71it/s, train/loss=0.951]
Epoch 0: | | 734/? [02:35<00:00, 4.71it/s, train/loss=12.20]
Epoch 0: | | 735/? [02:35<00:00, 4.71it/s, train/loss=12.20]
Epoch 0: | | 735/? [02:35<00:00, 4.71it/s, train/loss=0.977]
Epoch 0: | | 736/? [02:36<00:00, 4.71it/s, train/loss=0.977]
Epoch 0: | | 736/? [02:36<00:00, 4.71it/s, train/loss=37.10]
Epoch 0: | | 737/? [02:36<00:00, 4.72it/s, train/loss=37.10]
Epoch 0: | | 737/? [02:36<00:00, 4.72it/s, train/loss=1.170]
Epoch 0: | | 738/? [02:36<00:00, 4.72it/s, train/loss=1.170]
Epoch 0: | | 738/? [02:36<00:00, 4.72it/s, train/loss=22.80]
Epoch 0: | | 739/? [02:36<00:00, 4.72it/s, train/loss=22.80]
Epoch 0: | | 739/? [02:36<00:00, 4.72it/s, train/loss=1.210]
Epoch 0: | | 740/? [02:36<00:00, 4.72it/s, train/loss=1.210]
Epoch 0: | | 740/? [02:36<00:00, 4.72it/s, train/loss=29.60]
Epoch 0: | | 741/? [02:36<00:00, 4.72it/s, train/loss=29.60]
Epoch 0: | | 741/? [02:36<00:00, 4.72it/s, train/loss=1.210]
Epoch 0: | | 742/? [02:37<00:00, 4.72it/s, train/loss=1.210]
Epoch 0: | | 742/? [02:37<00:00, 4.72it/s, train/loss=35.50]
Epoch 0: | | 743/? [02:37<00:00, 4.73it/s, train/loss=35.50]
Epoch 0: | | 743/? [02:37<00:00, 4.73it/s, train/loss=1.200]
Epoch 0: | | 744/? [02:37<00:00, 4.73it/s, train/loss=1.200]
Epoch 0: | | 744/? [02:37<00:00, 4.73it/s, train/loss=42.00]
Epoch 0: | | 745/? [02:37<00:00, 4.73it/s, train/loss=42.00]
Epoch 0: | | 745/? [02:37<00:00, 4.73it/s, train/loss=1.180]
Epoch 0: | | 746/? [02:37<00:00, 4.73it/s, train/loss=1.180]
Epoch 0: | | 746/? [02:37<00:00, 4.73it/s, train/loss=34.50]
Epoch 0: | | 747/? [02:37<00:00, 4.74it/s, train/loss=34.50]
Epoch 0: | | 747/? [02:37<00:00, 4.74it/s, train/loss=1.170]
Epoch 0: | | 748/? [02:38<00:00, 4.73it/s, train/loss=1.170]
Epoch 0: | | 748/? [02:38<00:00, 4.73it/s, train/loss=29.70]
Epoch 0: | | 749/? [02:38<00:00, 4.74it/s, train/loss=29.70]
Epoch 0: | | 749/? [02:38<00:00, 4.74it/s, train/loss=1.180]
Epoch 0: | | 750/? [02:38<00:00, 4.74it/s, train/loss=1.180]
Epoch 0: | | 750/? [02:38<00:00, 4.74it/s, train/loss=29.00]
Epoch 0: | | 751/? [02:38<00:00, 4.74it/s, train/loss=29.00]
Epoch 0: | | 751/? [02:38<00:00, 4.74it/s, train/loss=1.190]
Epoch 0: | | 752/? [02:38<00:00, 4.74it/s, train/loss=1.190]
Epoch 0: | | 752/? [02:38<00:00, 4.74it/s, train/loss=17.00]
Epoch 0: | | 753/? [02:38<00:00, 4.75it/s, train/loss=17.00]
Epoch 0: | | 753/? [02:38<00:00, 4.75it/s, train/loss=1.210]
Epoch 0: | | 754/? [02:38<00:00, 4.74it/s, train/loss=1.210]
Epoch 0: | | 754/? [02:38<00:00, 4.74it/s, train/loss=7.800]
Epoch 0: | | 755/? [02:38<00:00, 4.75it/s, train/loss=7.800]
Epoch 0: | | 755/? [02:38<00:00, 4.75it/s, train/loss=1.220]
Epoch 0: | | 756/? [02:39<00:00, 4.75it/s, train/loss=1.220]
Epoch 0: | | 756/? [02:39<00:00, 4.75it/s, train/loss=35.00]
Epoch 0: | | 757/? [02:39<00:00, 4.75it/s, train/loss=35.00]
Epoch 0: | | 757/? [02:39<00:00, 4.75it/s, train/loss=1.220]
Epoch 0: | | 758/? [02:39<00:00, 4.75it/s, train/loss=1.220]
Epoch 0: | | 758/? [02:39<00:00, 4.75it/s, train/loss=15.80]
Epoch 0: | | 759/? [02:39<00:00, 4.76it/s, train/loss=15.80]
Epoch 0: | | 759/? [02:39<00:00, 4.76it/s, train/loss=1.210]
Epoch 0: | | 760/? [02:39<00:00, 4.75it/s, train/loss=1.210]
Epoch 0: | | 760/? [02:39<00:00, 4.75it/s, train/loss=19.90]
Epoch 0: | | 761/? [02:39<00:00, 4.76it/s, train/loss=19.90]
Epoch 0: | | 761/? [02:39<00:00, 4.76it/s, train/loss=1.190]
Epoch 0: | | 762/? [02:40<00:00, 4.76it/s, train/loss=1.190]
Epoch 0: | | 762/? [02:40<00:00, 4.76it/s, train/loss=27.10]
Epoch 0: | | 763/? [02:40<00:00, 4.76it/s, train/loss=27.10]
Epoch 0: | | 763/? [02:40<00:00, 4.76it/s, train/loss=1.160]
Epoch 0: | | 764/? [02:40<00:00, 4.76it/s, train/loss=1.160]
Epoch 0: | | 764/? [02:40<00:00, 4.76it/s, train/loss=19.60]
Epoch 0: | | 765/? [02:40<00:00, 4.77it/s, train/loss=19.60]
Epoch 0: | | 765/? [02:40<00:00, 4.77it/s, train/loss=1.150]
Epoch 0: | | 766/? [02:40<00:00, 4.76it/s, train/loss=1.150]
Epoch 0: | | 766/? [02:40<00:00, 4.76it/s, train/loss=23.80]
Epoch 0: | | 767/? [02:40<00:00, 4.77it/s, train/loss=23.80]
Epoch 0: | | 767/? [02:40<00:00, 4.77it/s, train/loss=1.170]
Epoch 0: | | 768/? [02:41<00:00, 4.77it/s, train/loss=1.170]
Epoch 0: | | 768/? [02:41<00:00, 4.77it/s, train/loss=35.60]
Epoch 0: | | 769/? [02:41<00:00, 4.77it/s, train/loss=35.60]
Epoch 0: | | 769/? [02:41<00:00, 4.77it/s, train/loss=1.140]
Epoch 0: | | 770/? [02:41<00:00, 4.77it/s, train/loss=1.140]
Epoch 0: | | 770/? [02:41<00:00, 4.77it/s, train/loss=41.80]
Epoch 0: | | 771/? [02:41<00:00, 4.78it/s, train/loss=41.80]
Epoch 0: | | 771/? [02:41<00:00, 4.78it/s, train/loss=1.090]
Epoch 0: | | 772/? [02:41<00:00, 4.77it/s, train/loss=1.090]
Epoch 0: | | 772/? [02:41<00:00, 4.77it/s, train/loss=15.80]
Epoch 0: | | 773/? [02:41<00:00, 4.78it/s, train/loss=15.80]
Epoch 0: | | 773/? [02:41<00:00, 4.78it/s, train/loss=1.070]
Epoch 0: | | 774/? [02:42<00:00, 4.78it/s, train/loss=1.070]
Epoch 0: | | 774/? [02:42<00:00, 4.78it/s, train/loss=16.30]
Epoch 0: | | 775/? [02:42<00:00, 4.78it/s, train/loss=16.30]
Epoch 0: | | 775/? [02:42<00:00, 4.78it/s, train/loss=1.070]
Epoch 0: | | 776/? [02:42<00:00, 4.78it/s, train/loss=1.070]
Epoch 0: | | 776/? [02:42<00:00, 4.78it/s, train/loss=22.50]
Epoch 0: | | 777/? [02:42<00:00, 4.79it/s, train/loss=22.50]
Epoch 0: | | 777/? [02:42<00:00, 4.79it/s, train/loss=1.070]
Epoch 0: | | 778/? [02:42<00:00, 4.78it/s, train/loss=1.070]
Epoch 0: | | 778/? [02:42<00:00, 4.78it/s, train/loss=15.30]
Epoch 0: | | 779/? [02:42<00:00, 4.78it/s, train/loss=15.30]
Epoch 0: | | 779/? [02:42<00:00, 4.78it/s, train/loss=1.080]
Epoch 0: | | 780/? [02:43<00:00, 4.78it/s, train/loss=1.080]
Epoch 0: | | 780/? [02:43<00:00, 4.78it/s, train/loss=7.950]
Epoch 0: | | 781/? [02:43<00:00, 4.78it/s, train/loss=7.950]
Epoch 0: | | 781/? [02:43<00:00, 4.78it/s, train/loss=1.080]
Epoch 0: | | 782/? [02:43<00:00, 4.78it/s, train/loss=1.080]
Epoch 0: | | 782/? [02:43<00:00, 4.78it/s, train/loss=11.60]
Epoch 0: | | 783/? [02:43<00:00, 4.79it/s, train/loss=11.60]
Epoch 0: | | 783/? [02:43<00:00, 4.79it/s, train/loss=1.090]
Epoch 0: | | 784/? [02:43<00:00, 4.78it/s, train/loss=1.090]
Epoch 0: | | 784/? [02:43<00:00, 4.78it/s, train/loss=52.90]
Epoch 0: | | 785/? [02:43<00:00, 4.79it/s, train/loss=52.90]
Epoch 0: | | 785/? [02:43<00:00, 4.79it/s, train/loss=1.100]
Epoch 0: | | 786/? [02:44<00:00, 4.79it/s, train/loss=1.100]
Epoch 0: | | 786/? [02:44<00:00, 4.79it/s, train/loss=25.70]
Epoch 0: | | 787/? [02:44<00:00, 4.79it/s, train/loss=25.70]
Epoch 0: | | 787/? [02:44<00:00, 4.79it/s, train/loss=1.110]
Epoch 0: | | 788/? [02:44<00:00, 4.79it/s, train/loss=1.110]
Epoch 0: | | 788/? [02:44<00:00, 4.79it/s, train/loss=15.70]
Epoch 0: | | 789/? [02:44<00:00, 4.79it/s, train/loss=15.70]
Epoch 0: | | 789/? [02:44<00:00, 4.79it/s, train/loss=1.110]
Epoch 0: | | 790/? [02:44<00:00, 4.79it/s, train/loss=1.110]
Epoch 0: | | 790/? [02:44<00:00, 4.79it/s, train/loss=15.20]
Epoch 0: | | 791/? [02:44<00:00, 4.80it/s, train/loss=15.20]
Epoch 0: | | 791/? [02:44<00:00, 4.80it/s, train/loss=1.100]
Epoch 0: | | 792/? [02:45<00:00, 4.79it/s, train/loss=1.100]
Epoch 0: | | 792/? [02:45<00:00, 4.79it/s, train/loss=21.60]
Epoch 0: | | 793/? [02:45<00:00, 4.80it/s, train/loss=21.60]
Epoch 0: | | 793/? [02:45<00:00, 4.80it/s, train/loss=1.090]
Epoch 0: | | 794/? [02:45<00:00, 4.80it/s, train/loss=1.090]
Epoch 0: | | 794/? [02:45<00:00, 4.80it/s, train/loss=11.20]
Epoch 0: | | 795/? [02:45<00:00, 4.80it/s, train/loss=11.20]
Epoch 0: | | 795/? [02:45<00:00, 4.80it/s, train/loss=1.090]
Epoch 0: | | 796/? [02:45<00:00, 4.80it/s, train/loss=1.090]
Epoch 0: | | 796/? [02:45<00:00, 4.80it/s, train/loss=8.000]
Epoch 0: | | 797/? [02:45<00:00, 4.80it/s, train/loss=8.000]
Epoch 0: | | 797/? [02:45<00:00, 4.80it/s, train/loss=1.060]
Epoch 0: | | 798/? [02:46<00:00, 4.80it/s, train/loss=1.060]
Epoch 0: | | 798/? [02:46<00:00, 4.80it/s, train/loss=19.90]
Epoch 0: | | 799/? [02:46<00:00, 4.81it/s, train/loss=19.90]
Epoch 0: | | 799/? [02:46<00:00, 4.81it/s, train/loss=1.020]
Epoch 0: | | 800/? [02:46<00:00, 4.81it/s, train/loss=1.020]
Epoch 0: | | 800/? [02:46<00:00, 4.81it/s, train/loss=19.30]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:06, 6.44it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:05, 6.56it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:05, 6.62it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:05, 6.57it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:05, 6.47it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:05, 6.49it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:01<00:05, 6.51it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:01<00:04, 6.51it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:01<00:04, 6.53it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:01<00:04, 6.56it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:01<00:04, 6.57it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:04, 6.58it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:04, 6.59it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:02<00:03, 6.61it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:02<00:03, 6.61it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:02<00:03, 6.56it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:02<00:03, 6.52it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:02<00:03, 6.49it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:02<00:03, 6.47it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:03<00:03, 6.48it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:03<00:02, 6.48it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:03<00:02, 6.49it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:03<00:02, 6.51it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:03<00:02, 6.52it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:03<00:02, 6.53it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:03<00:02, 6.54it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:04<00:01, 6.56it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:04<00:01, 6.57it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:04<00:01, 6.57it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:04<00:01, 6.57it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:04<00:01, 6.58it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:04<00:01, 6.59it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:05<00:01, 6.60it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:05<00:00, 6.60it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:05<00:00, 6.59it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:05<00:00, 6.60it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:05<00:00, 6.60it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:05<00:00, 6.58it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:05<00:00, 6.59it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:06<00:00, 6.59it/s][A
[A
Epoch 0: | | 800/? [02:53<00:00, 4.60it/s, train/loss=19.30]
`Trainer.fit` stopped: `max_steps=800` reached.
Epoch 0: | | 800/? [02:53<00:00, 4.60it/s, train/loss=19.30]
Epoch 0: | | 800/? [02:53<00:00, 4.60it/s, train/loss=19.30]
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load depth /src/outputs/image_depth.png torch.Size([1, 128, 128])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Testing: | | 0/? [00:00<?, ?it/s]
Testing: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 1%| | 1/120 [00:00<00:18, 6.41it/s]
Testing DataLoader 0: 2%|▏ | 2/120 [00:00<00:18, 6.53it/s]
Testing DataLoader 0: 2%|▎ | 3/120 [00:00<00:18, 6.50it/s]
Testing DataLoader 0: 3%|▎ | 4/120 [00:00<00:17, 6.57it/s]
Testing DataLoader 0: 4%|▍ | 5/120 [00:00<00:17, 6.61it/s]
Testing DataLoader 0: 5%|▌ | 6/120 [00:00<00:17, 6.63it/s]
Testing DataLoader 0: 6%|▌ | 7/120 [00:01<00:17, 6.64it/s]
Testing DataLoader 0: 7%|▋ | 8/120 [00:01<00:16, 6.65it/s]
Testing DataLoader 0: 8%|▊ | 9/120 [00:01<00:16, 6.66it/s]
Testing DataLoader 0: 8%|▊ | 10/120 [00:01<00:16, 6.65it/s]
Testing DataLoader 0: 9%|▉ | 11/120 [00:01<00:16, 6.65it/s]
Testing DataLoader 0: 10%|█ | 12/120 [00:01<00:16, 6.63it/s]
Testing DataLoader 0: 11%|█ | 13/120 [00:01<00:16, 6.65it/s]
Testing DataLoader 0: 12%|█▏ | 14/120 [00:02<00:16, 6.62it/s]
Testing DataLoader 0: 12%|█▎ | 15/120 [00:02<00:15, 6.60it/s]
Testing DataLoader 0: 13%|█▎ | 16/120 [00:02<00:15, 6.61it/s]
Testing DataLoader 0: 14%|█▍ | 17/120 [00:02<00:15, 6.61it/s]
Testing DataLoader 0: 15%|█▌ | 18/120 [00:02<00:15, 6.61it/s]
Testing DataLoader 0: 16%|█▌ | 19/120 [00:02<00:15, 6.60it/s]
Testing DataLoader 0: 17%|█▋ | 20/120 [00:03<00:15, 6.60it/s]
Testing DataLoader 0: 18%|█▊ | 21/120 [00:03<00:14, 6.61it/s]
Testing DataLoader 0: 18%|█▊ | 22/120 [00:03<00:14, 6.61it/s]
Testing DataLoader 0: 19%|█▉ | 23/120 [00:03<00:14, 6.60it/s]
Testing DataLoader 0: 20%|██ | 24/120 [00:03<00:14, 6.58it/s]
Testing DataLoader 0: 21%|██ | 25/120 [00:03<00:14, 6.57it/s]
Testing DataLoader 0: 22%|██▏ | 26/120 [00:03<00:14, 6.56it/s]
Testing DataLoader 0: 22%|██▎ | 27/120 [00:04<00:14, 6.55it/s]
Testing DataLoader 0: 23%|██▎ | 28/120 [00:04<00:14, 6.55it/s]
Testing DataLoader 0: 24%|██▍ | 29/120 [00:04<00:13, 6.55it/s]
Testing DataLoader 0: 25%|██▌ | 30/120 [00:04<00:13, 6.54it/s]
Testing DataLoader 0: 26%|██▌ | 31/120 [00:04<00:13, 6.55it/s]
Testing DataLoader 0: 27%|██▋ | 32/120 [00:04<00:13, 6.53it/s]
Testing DataLoader 0: 28%|██▊ | 33/120 [00:05<00:13, 6.54it/s]
Testing DataLoader 0: 28%|██▊ | 34/120 [00:05<00:13, 6.55it/s]
Testing DataLoader 0: 29%|██▉ | 35/120 [00:05<00:12, 6.55it/s]
Testing DataLoader 0: 30%|███ | 36/120 [00:05<00:12, 6.55it/s]
Testing DataLoader 0: 31%|███ | 37/120 [00:05<00:12, 6.56it/s]
Testing DataLoader 0: 32%|███▏ | 38/120 [00:05<00:12, 6.56it/s]
Testing DataLoader 0: 32%|███▎ | 39/120 [00:05<00:12, 6.57it/s]
Testing DataLoader 0: 33%|███▎ | 40/120 [00:06<00:12, 6.57it/s]
Testing DataLoader 0: 34%|███▍ | 41/120 [00:06<00:12, 6.57it/s]
Testing DataLoader 0: 35%|███▌ | 42/120 [00:06<00:11, 6.57it/s]
Testing DataLoader 0: 36%|███▌ | 43/120 [00:06<00:11, 6.56it/s]
Testing DataLoader 0: 37%|███▋ | 44/120 [00:06<00:11, 6.57it/s]
Testing DataLoader 0: 38%|███▊ | 45/120 [00:06<00:11, 6.57it/s]
Testing DataLoader 0: 38%|███▊ | 46/120 [00:06<00:11, 6.57it/s]
Testing DataLoader 0: 39%|███▉ | 47/120 [00:07<00:11, 6.57it/s]
Testing DataLoader 0: 40%|████ | 48/120 [00:07<00:10, 6.58it/s]
Testing DataLoader 0: 41%|████ | 49/120 [00:07<00:10, 6.58it/s]
Testing DataLoader 0: 42%|████▏ | 50/120 [00:07<00:10, 6.59it/s]
Testing DataLoader 0: 42%|████▎ | 51/120 [00:07<00:10, 6.59it/s]
Testing DataLoader 0: 43%|████▎ | 52/120 [00:07<00:10, 6.59it/s]
Testing DataLoader 0: 44%|████▍ | 53/120 [00:08<00:10, 6.59it/s]
Testing DataLoader 0: 45%|████▌ | 54/120 [00:08<00:10, 6.59it/s]
Testing DataLoader 0: 46%|████▌ | 55/120 [00:08<00:09, 6.60it/s]
Testing DataLoader 0: 47%|████▋ | 56/120 [00:08<00:09, 6.60it/s]
Testing DataLoader 0: 48%|████▊ | 57/120 [00:08<00:09, 6.60it/s]
Testing DataLoader 0: 48%|████▊ | 58/120 [00:08<00:09, 6.60it/s]
Testing DataLoader 0: 49%|████▉ | 59/120 [00:08<00:09, 6.61it/s]
Testing DataLoader 0: 50%|█████ | 60/120 [00:09<00:09, 6.61it/s]
Testing DataLoader 0: 51%|█████ | 61/120 [00:09<00:08, 6.61it/s]
Testing DataLoader 0: 52%|█████▏ | 62/120 [00:09<00:08, 6.61it/s]
Testing DataLoader 0: 52%|█████▎ | 63/120 [00:09<00:08, 6.61it/s]
Testing DataLoader 0: 53%|█████▎ | 64/120 [00:09<00:08, 6.62it/s]
Testing DataLoader 0: 54%|█████▍ | 65/120 [00:09<00:08, 6.62it/s]
Testing DataLoader 0: 55%|█████▌ | 66/120 [00:09<00:08, 6.62it/s]
Testing DataLoader 0: 56%|█████▌ | 67/120 [00:10<00:08, 6.62it/s]
Testing DataLoader 0: 57%|█████▋ | 68/120 [00:10<00:07, 6.62it/s]
Testing DataLoader 0: 57%|█████▊ | 69/120 [00:10<00:07, 6.62it/s]
Testing DataLoader 0: 58%|█████▊ | 70/120 [00:10<00:07, 6.63it/s]
Testing DataLoader 0: 59%|█████▉ | 71/120 [00:10<00:07, 6.63it/s]
Testing DataLoader 0: 60%|██████ | 72/120 [00:10<00:07, 6.63it/s]
Testing DataLoader 0: 61%|██████ | 73/120 [00:10<00:07, 6.64it/s]
Testing DataLoader 0: 62%|██████▏ | 74/120 [00:11<00:06, 6.63it/s]
Testing DataLoader 0: 62%|██████▎ | 75/120 [00:11<00:06, 6.62it/s]
Testing DataLoader 0: 63%|██████▎ | 76/120 [00:11<00:06, 6.61it/s]
Testing DataLoader 0: 64%|██████▍ | 77/120 [00:11<00:06, 6.60it/s]
Testing DataLoader 0: 65%|██████▌ | 78/120 [00:11<00:06, 6.59it/s]
Testing DataLoader 0: 66%|██████▌ | 79/120 [00:11<00:06, 6.59it/s]
Testing DataLoader 0: 67%|██████▋ | 80/120 [00:12<00:06, 6.59it/s]
Testing DataLoader 0: 68%|██████▊ | 81/120 [00:12<00:05, 6.59it/s]
Testing DataLoader 0: 68%|██████▊ | 82/120 [00:12<00:05, 6.58it/s]
Testing DataLoader 0: 69%|██████▉ | 83/120 [00:12<00:05, 6.58it/s]
Testing DataLoader 0: 70%|███████ | 84/120 [00:12<00:05, 6.59it/s]
Testing DataLoader 0: 71%|███████ | 85/120 [00:12<00:05, 6.59it/s]
Testing DataLoader 0: 72%|███████▏ | 86/120 [00:13<00:05, 6.59it/s]
Testing DataLoader 0: 72%|███████▎ | 87/120 [00:13<00:05, 6.59it/s]
Testing DataLoader 0: 73%|███████▎ | 88/120 [00:13<00:04, 6.60it/s]
Testing DataLoader 0: 74%|███████▍ | 89/120 [00:13<00:04, 6.60it/s]
Testing DataLoader 0: 75%|███████▌ | 90/120 [00:13<00:04, 6.60it/s]
Testing DataLoader 0: 76%|███████▌ | 91/120 [00:13<00:04, 6.60it/s]
Testing DataLoader 0: 77%|███████▋ | 92/120 [00:13<00:04, 6.60it/s]
Testing DataLoader 0: 78%|███████▊ | 93/120 [00:14<00:04, 6.61it/s]
Testing DataLoader 0: 78%|███████▊ | 94/120 [00:14<00:03, 6.61it/s]
Testing DataLoader 0: 79%|███████▉ | 95/120 [00:14<00:03, 6.60it/s]
Testing DataLoader 0: 80%|████████ | 96/120 [00:14<00:03, 6.60it/s]
Testing DataLoader 0: 81%|████████ | 97/120 [00:14<00:03, 6.60it/s]
Testing DataLoader 0: 82%|████████▏ | 98/120 [00:14<00:03, 6.61it/s]
Testing DataLoader 0: 82%|████████▎ | 99/120 [00:14<00:03, 6.61it/s]
Testing DataLoader 0: 83%|████████▎ | 100/120 [00:15<00:03, 6.61it/s]
Testing DataLoader 0: 84%|████████▍ | 101/120 [00:15<00:02, 6.61it/s]
Testing DataLoader 0: 85%|████████▌ | 102/120 [00:15<00:02, 6.61it/s]
Testing DataLoader 0: 86%|████████▌ | 103/120 [00:15<00:02, 6.61it/s]
Testing DataLoader 0: 87%|████████▋ | 104/120 [00:15<00:02, 6.61it/s]
Testing DataLoader 0: 88%|████████▊ | 105/120 [00:15<00:02, 6.62it/s]
Testing DataLoader 0: 88%|████████▊ | 106/120 [00:16<00:02, 6.62it/s]
Testing DataLoader 0: 89%|████████▉ | 107/120 [00:16<00:01, 6.62it/s]
Testing DataLoader 0: 90%|█████████ | 108/120 [00:16<00:01, 6.62it/s]
Testing DataLoader 0: 91%|█████████ | 109/120 [00:16<00:01, 6.62it/s]
Testing DataLoader 0: 92%|█████████▏| 110/120 [00:16<00:01, 6.62it/s]
Testing DataLoader 0: 92%|█████████▎| 111/120 [00:16<00:01, 6.62it/s]
Testing DataLoader 0: 93%|█████████▎| 112/120 [00:16<00:01, 6.62it/s]
Testing DataLoader 0: 94%|█████████▍| 113/120 [00:17<00:01, 6.62it/s]
Testing DataLoader 0: 95%|█████████▌| 114/120 [00:17<00:00, 6.61it/s]
Testing DataLoader 0: 96%|█████████▌| 115/120 [00:17<00:00, 6.61it/s]
Testing DataLoader 0: 97%|█████████▋| 116/120 [00:17<00:00, 6.61it/s]
Testing DataLoader 0: 98%|█████████▊| 117/120 [00:17<00:00, 6.61it/s]
Testing DataLoader 0: 98%|█████████▊| 118/120 [00:17<00:00, 6.61it/s]
Testing DataLoader 0: 99%|█████████▉| 119/120 [00:18<00:00, 6.61it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:18<00:00, 6.60it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:19<00:00, 6.17it/s]
Test results saved to outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/save
Running step 3: geometry refinement
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-geometry',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-geometry',
'resume': None,
'seed': 0,
'system': {'stage': 'geometry', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'deep-floyd-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'prompt': 'A green leafy plant in a striped terracotta pot', 'use_perp_neg': True}, 'guidance_type': 'deep-floyd-guidance', 'guidance': {'pretrained_model_name_or_path': 'DeepFloyd/IF-I-XL-v1.0', 'guidance_scale': 5.0, 'min_step_percent': 0.02, 'max_step_percent': 0.5}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'accumulate', 'no_diff_steps': 0, 'guidance_eval': 0, 'n_rgb': 4}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_sds': 0.1, 'lambda_3d_sds': 0.1, 'lambda_rgb': 1000.0, 'lambda_mask': 100.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_normal_consistency': 10.0, 'lambda_laplacian_smoothness': 0.0}, 'optimizer': {'name': 'Adam', 'args': {'lr': 0.005, 'betas': [0.9, 0.99], 'eps': 1e-15}}, 'geometry_convert_from': 'outputs/dreamcraft3d-coarse-neus/replicate_user@20240222-134422/ckpts/last.ckpt'},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-134756',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32},
'trial_dir': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756',
'trial_name': 'replicate_user@20240222-134756',
'use_timestamp': True}
Initializing geometry from a given checkpoint ...
Loading Deep Floyd ...
Couldn't connect to the Hub: 401 Client Error. (Request ID: Root=1-65d7509e-6347b4da73b31fa229296b6e;25483ae6-ebc7-4a7b-ac33-672d284154c2)
Cannot access gated repo for url https://huggingface.co/api/models/DeepFloyd/IF-I-XL-v1.0.
Repo model DeepFloyd/IF-I-XL-v1.0 is gated. You must be authenticated to access it..
Will try to load from local cache.
Loading pipeline components...: 0%| | 0/3 [00:00<?, ?it/s]
Loading pipeline components...: 33%|███▎ | 1/3 [00:00<00:00, 5.14it/s]
Loading pipeline components...: 100%|██████████| 3/3 [00:00<00:00, 13.15it/s]
Loaded Deep Floyd!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name | Type | Params
----------------------------------------------------
0 | geometry | TetrahedraSDFGrid | 13.7 M
1 | material | NoMaterial | 0
2 | background | SolidColorBackground | 0
3 | renderer | NVDiffRasterizer | 0
----------------------------------------------------
13.7 M Trainable params
0 Non-trainable params
13.7 M Total params
54.847 Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/save
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
Training: | | 0/? [00:00<?, ?it/s]
Training: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 1/? [00:00<00:00, 7.59it/s]
Epoch 0: | | 1/? [00:00<00:00, 7.51it/s, train/loss=21.80]
Epoch 0: | | 2/? [00:00<00:00, 3.74it/s, train/loss=21.80]
Epoch 0: | | 2/? [00:00<00:00, 3.73it/s, train/loss=32.90]
Epoch 0: | | 3/? [00:00<00:00, 3.50it/s, train/loss=32.90]
Epoch 0: | | 3/? [00:00<00:00, 3.49it/s, train/loss=48.70]
Epoch 0: | | 4/? [00:01<00:00, 3.36it/s, train/loss=48.70]
Epoch 0: | | 4/? [00:01<00:00, 3.36it/s, train/loss=23.90]
Epoch 0: | | 5/? [00:01<00:00, 3.28it/s, train/loss=23.90]
Epoch 0: | | 5/? [00:01<00:00, 3.28it/s, train/loss=35.10]
Epoch 0: | | 6/? [00:01<00:00, 3.26it/s, train/loss=35.10]
Epoch 0: | | 6/? [00:01<00:00, 3.25it/s, train/loss=23.40]
Epoch 0: | | 7/? [00:02<00:00, 3.22it/s, train/loss=23.40]
Epoch 0: | | 7/? [00:02<00:00, 3.22it/s, train/loss=15.90]
Epoch 0: | | 8/? [00:02<00:00, 3.21it/s, train/loss=15.90]
Epoch 0: | | 8/? [00:02<00:00, 3.21it/s, train/loss=19.40]
Epoch 0: | | 9/? [00:02<00:00, 3.19it/s, train/loss=19.40]
Epoch 0: | | 9/? [00:02<00:00, 3.18it/s, train/loss=31.50]
Epoch 0: | | 10/? [00:03<00:00, 3.18it/s, train/loss=31.50]
Epoch 0: | | 10/? [00:03<00:00, 3.18it/s, train/loss=13.20]
Epoch 0: | | 11/? [00:03<00:00, 3.17it/s, train/loss=13.20]
Epoch 0: | | 11/? [00:03<00:00, 3.17it/s, train/loss=19.80]
Epoch 0: | | 12/? [00:03<00:00, 3.17it/s, train/loss=19.80]
Epoch 0: | | 12/? [00:03<00:00, 3.17it/s, train/loss=42.70]
Epoch 0: | | 13/? [00:04<00:00, 3.15it/s, train/loss=42.70]
Epoch 0: | | 13/? [00:04<00:00, 3.15it/s, train/loss=59.50]
Epoch 0: | | 14/? [00:04<00:00, 3.15it/s, train/loss=59.50]
Epoch 0: | | 14/? [00:04<00:00, 3.15it/s, train/loss=20.30]
Epoch 0: | | 15/? [00:04<00:00, 3.15it/s, train/loss=20.30]
Epoch 0: | | 15/? [00:04<00:00, 3.15it/s, train/loss=17.40]
Epoch 0: | | 16/? [00:05<00:00, 3.15it/s, train/loss=17.40]
Epoch 0: | | 16/? [00:05<00:00, 3.14it/s, train/loss=34.70]
Epoch 0: | | 17/? [00:05<00:00, 3.14it/s, train/loss=34.70]
Epoch 0: | | 17/? [00:05<00:00, 3.14it/s, train/loss=23.60]
Epoch 0: | | 18/? [00:05<00:00, 3.14it/s, train/loss=23.60]
Epoch 0: | | 18/? [00:05<00:00, 3.13it/s, train/loss=14.50]
Epoch 0: | | 19/? [00:06<00:00, 3.13it/s, train/loss=14.50]
Epoch 0: | | 19/? [00:06<00:00, 3.13it/s, train/loss=26.20]
Epoch 0: | | 20/? [00:06<00:00, 3.13it/s, train/loss=26.20]
Epoch 0: | | 20/? [00:06<00:00, 3.13it/s, train/loss=38.50]
Epoch 0: | | 21/? [00:06<00:00, 3.12it/s, train/loss=38.50]
Epoch 0: | | 21/? [00:06<00:00, 3.12it/s, train/loss=43.40]
Epoch 0: | | 22/? [00:07<00:00, 3.12it/s, train/loss=43.40]
Epoch 0: | | 22/? [00:07<00:00, 3.12it/s, train/loss=31.60]
Epoch 0: | | 23/? [00:07<00:00, 3.12it/s, train/loss=31.60]
Epoch 0: | | 23/? [00:07<00:00, 3.12it/s, train/loss=82.20]
Epoch 0: | | 24/? [00:07<00:00, 3.12it/s, train/loss=82.20]
Epoch 0: | | 24/? [00:07<00:00, 3.12it/s, train/loss=9.930]
Epoch 0: | | 25/? [00:08<00:00, 3.11it/s, train/loss=9.930]
Epoch 0: | | 25/? [00:08<00:00, 3.11it/s, train/loss=35.30]
Epoch 0: | | 26/? [00:08<00:00, 3.11it/s, train/loss=35.30]
Epoch 0: | | 26/? [00:08<00:00, 3.11it/s, train/loss=20.50]
Epoch 0: | | 27/? [00:08<00:00, 3.11it/s, train/loss=20.50]
Epoch 0: | | 27/? [00:08<00:00, 3.11it/s, train/loss=31.80]
Epoch 0: | | 28/? [00:08<00:00, 3.11it/s, train/loss=31.80]
Epoch 0: | | 28/? [00:08<00:00, 3.11it/s, train/loss=24.90]
Epoch 0: | | 29/? [00:09<00:00, 3.11it/s, train/loss=24.90]
Epoch 0: | | 29/? [00:09<00:00, 3.11it/s, train/loss=51.90]
Epoch 0: | | 30/? [00:09<00:00, 3.11it/s, train/loss=51.90]
Epoch 0: | | 30/? [00:09<00:00, 3.11it/s, train/loss=20.80]
Epoch 0: | | 31/? [00:09<00:00, 3.11it/s, train/loss=20.80]
Epoch 0: | | 31/? [00:09<00:00, 3.11it/s, train/loss=20.10]
Epoch 0: | | 32/? [00:10<00:00, 3.11it/s, train/loss=20.10]
Epoch 0: | | 32/? [00:10<00:00, 3.11it/s, train/loss=24.10]
Epoch 0: | | 33/? [00:10<00:00, 3.11it/s, train/loss=24.10]
Epoch 0: | | 33/? [00:10<00:00, 3.11it/s, train/loss=40.80]
Epoch 0: | | 34/? [00:10<00:00, 3.11it/s, train/loss=40.80]
Epoch 0: | | 34/? [00:10<00:00, 3.11it/s, train/loss=10.70]
Epoch 0: | | 35/? [00:11<00:00, 3.11it/s, train/loss=10.70]
Epoch 0: | | 35/? [00:11<00:00, 3.11it/s, train/loss=20.80]
Epoch 0: | | 36/? [00:11<00:00, 3.11it/s, train/loss=20.80]
Epoch 0: | | 36/? [00:11<00:00, 3.11it/s, train/loss=20.80]
Epoch 0: | | 37/? [00:11<00:00, 3.11it/s, train/loss=20.80]
Epoch 0: | | 37/? [00:11<00:00, 3.11it/s, train/loss=35.00]
Epoch 0: | | 38/? [00:12<00:00, 3.11it/s, train/loss=35.00]
Epoch 0: | | 38/? [00:12<00:00, 3.11it/s, train/loss=15.10]
Epoch 0: | | 39/? [00:12<00:00, 3.11it/s, train/loss=15.10]
Epoch 0: | | 39/? [00:12<00:00, 3.11it/s, train/loss=8.780]
Epoch 0: | | 40/? [00:12<00:00, 3.11it/s, train/loss=8.780]
Epoch 0: | | 40/? [00:12<00:00, 3.11it/s, train/loss=19.80]
Epoch 0: | | 41/? [00:13<00:00, 3.10it/s, train/loss=19.80]
Epoch 0: | | 41/? [00:13<00:00, 3.10it/s, train/loss=30.00]
Epoch 0: | | 42/? [00:13<00:00, 3.11it/s, train/loss=30.00]
Epoch 0: | | 42/? [00:13<00:00, 3.11it/s, train/loss=17.70]
Epoch 0: | | 43/? [00:13<00:00, 3.11it/s, train/loss=17.70]
Epoch 0: | | 43/? [00:13<00:00, 3.11it/s, train/loss=8.890]
Epoch 0: | | 44/? [00:14<00:00, 3.11it/s, train/loss=8.890]
Epoch 0: | | 44/? [00:14<00:00, 3.11it/s, train/loss=10.90]
Epoch 0: | | 45/? [00:14<00:00, 3.11it/s, train/loss=10.90]
Epoch 0: | | 45/? [00:14<00:00, 3.11it/s, train/loss=24.40]
Epoch 0: | | 46/? [00:14<00:00, 3.11it/s, train/loss=24.40]
Epoch 0: | | 46/? [00:14<00:00, 3.11it/s, train/loss=39.40]
Epoch 0: | | 47/? [00:15<00:00, 3.10it/s, train/loss=39.40]
Epoch 0: | | 47/? [00:15<00:00, 3.10it/s, train/loss=31.50]
Epoch 0: | | 48/? [00:15<00:00, 3.10it/s, train/loss=31.50]
Epoch 0: | | 48/? [00:15<00:00, 3.10it/s, train/loss=21.20]
Epoch 0: | | 49/? [00:15<00:00, 3.10it/s, train/loss=21.20]
Epoch 0: | | 49/? [00:15<00:00, 3.10it/s, train/loss=35.10]
Epoch 0: | | 50/? [00:16<00:00, 3.10it/s, train/loss=35.10]
Epoch 0: | | 50/? [00:16<00:00, 3.10it/s, train/loss=30.50]
Epoch 0: | | 51/? [00:16<00:00, 3.10it/s, train/loss=30.50]
Epoch 0: | | 51/? [00:16<00:00, 3.10it/s, train/loss=11.50]
Epoch 0: | | 52/? [00:16<00:00, 3.10it/s, train/loss=11.50]
Epoch 0: | | 52/? [00:16<00:00, 3.10it/s, train/loss=31.30]
Epoch 0: | | 53/? [00:17<00:00, 3.10it/s, train/loss=31.30]
Epoch 0: | | 53/? [00:17<00:00, 3.10it/s, train/loss=50.10]
Epoch 0: | | 54/? [00:17<00:00, 3.10it/s, train/loss=50.10]
Epoch 0: | | 54/? [00:17<00:00, 3.10it/s, train/loss=11.20]
Epoch 0: | | 55/? [00:17<00:00, 3.10it/s, train/loss=11.20]
Epoch 0: | | 55/? [00:17<00:00, 3.10it/s, train/loss=26.00]
Epoch 0: | | 56/? [00:18<00:00, 3.10it/s, train/loss=26.00]
Epoch 0: | | 56/? [00:18<00:00, 3.10it/s, train/loss=25.00]
Epoch 0: | | 57/? [00:18<00:00, 3.10it/s, train/loss=25.00]
Epoch 0: | | 57/? [00:18<00:00, 3.10it/s, train/loss=22.20]
Epoch 0: | | 58/? [00:18<00:00, 3.10it/s, train/loss=22.20]
Epoch 0: | | 58/? [00:18<00:00, 3.10it/s, train/loss=14.50]
Epoch 0: | | 59/? [00:19<00:00, 3.10it/s, train/loss=14.50]
Epoch 0: | | 59/? [00:19<00:00, 3.10it/s, train/loss=16.70]
Epoch 0: | | 60/? [00:19<00:00, 3.10it/s, train/loss=16.70]
Epoch 0: | | 60/? [00:19<00:00, 3.10it/s, train/loss=37.50]
Epoch 0: | | 61/? [00:19<00:00, 3.10it/s, train/loss=37.50]
Epoch 0: | | 61/? [00:19<00:00, 3.10it/s, train/loss=36.60]
Epoch 0: | | 62/? [00:20<00:00, 3.10it/s, train/loss=36.60]
Epoch 0: | | 62/? [00:20<00:00, 3.10it/s, train/loss=62.90]
Epoch 0: | | 63/? [00:20<00:00, 3.10it/s, train/loss=62.90]
Epoch 0: | | 63/? [00:20<00:00, 3.10it/s, train/loss=31.40]
Epoch 0: | | 64/? [00:20<00:00, 3.10it/s, train/loss=31.40]
Epoch 0: | | 64/? [00:20<00:00, 3.10it/s, train/loss=23.80]
Epoch 0: | | 65/? [00:20<00:00, 3.10it/s, train/loss=23.80]
Epoch 0: | | 65/? [00:20<00:00, 3.10it/s, train/loss=32.90]
Epoch 0: | | 66/? [00:21<00:00, 3.10it/s, train/loss=32.90]
Epoch 0: | | 66/? [00:21<00:00, 3.10it/s, train/loss=23.90]
Epoch 0: | | 67/? [00:21<00:00, 3.10it/s, train/loss=23.90]
Epoch 0: | | 67/? [00:21<00:00, 3.10it/s, train/loss=14.50]
Epoch 0: | | 68/? [00:21<00:00, 3.10it/s, train/loss=14.50]
Epoch 0: | | 68/? [00:21<00:00, 3.10it/s, train/loss=29.40]
Epoch 0: | | 69/? [00:22<00:00, 3.10it/s, train/loss=29.40]
Epoch 0: | | 69/? [00:22<00:00, 3.10it/s, train/loss=38.10]
Epoch 0: | | 70/? [00:22<00:00, 3.10it/s, train/loss=38.10]
Epoch 0: | | 70/? [00:22<00:00, 3.10it/s, train/loss=39.80]
Epoch 0: | | 71/? [00:22<00:00, 3.10it/s, train/loss=39.80]
Epoch 0: | | 71/? [00:22<00:00, 3.10it/s, train/loss=22.10]
Epoch 0: | | 72/? [00:23<00:00, 3.10it/s, train/loss=22.10]
Epoch 0: | | 72/? [00:23<00:00, 3.10it/s, train/loss=25.50]
Epoch 0: | | 73/? [00:23<00:00, 3.10it/s, train/loss=25.50]
Epoch 0: | | 73/? [00:23<00:00, 3.10it/s, train/loss=25.70]
Epoch 0: | | 74/? [00:23<00:00, 3.10it/s, train/loss=25.70]
Epoch 0: | | 74/? [00:23<00:00, 3.10it/s, train/loss=18.70]
Epoch 0: | | 75/? [00:24<00:00, 3.10it/s, train/loss=18.70]
Epoch 0: | | 75/? [00:24<00:00, 3.10it/s, train/loss=25.40]
Epoch 0: | | 76/? [00:24<00:00, 3.10it/s, train/loss=25.40]
Epoch 0: | | 76/? [00:24<00:00, 3.10it/s, train/loss=22.10]
Epoch 0: | | 77/? [00:24<00:00, 3.10it/s, train/loss=22.10]
Epoch 0: | | 77/? [00:24<00:00, 3.10it/s, train/loss=33.50]
Epoch 0: | | 78/? [00:25<00:00, 3.08it/s, train/loss=33.50]
Epoch 0: | | 78/? [00:25<00:00, 3.08it/s, train/loss=13.40]
Epoch 0: | | 79/? [00:25<00:00, 3.06it/s, train/loss=13.40]
Epoch 0: | | 79/? [00:25<00:00, 3.06it/s, train/loss=9.540]
Epoch 0: | | 80/? [00:26<00:00, 3.05it/s, train/loss=9.540]
Epoch 0: | | 80/? [00:26<00:00, 3.05it/s, train/loss=13.70]
Epoch 0: | | 81/? [00:26<00:00, 3.04it/s, train/loss=13.70]
Epoch 0: | | 81/? [00:26<00:00, 3.04it/s, train/loss=32.00]
Epoch 0: | | 82/? [00:26<00:00, 3.04it/s, train/loss=32.00]
Epoch 0: | | 82/? [00:26<00:00, 3.04it/s, train/loss=23.60]
Epoch 0: | | 83/? [00:27<00:00, 3.05it/s, train/loss=23.60]
Epoch 0: | | 83/? [00:27<00:00, 3.05it/s, train/loss=27.50]
Epoch 0: | | 84/? [00:27<00:00, 3.05it/s, train/loss=27.50]
Epoch 0: | | 84/? [00:27<00:00, 3.05it/s, train/loss=41.20]
Epoch 0: | | 85/? [00:27<00:00, 3.04it/s, train/loss=41.20]
Epoch 0: | | 85/? [00:27<00:00, 3.04it/s, train/loss=31.90]
Epoch 0: | | 86/? [00:28<00:00, 3.05it/s, train/loss=31.90]
Epoch 0: | | 86/? [00:28<00:00, 3.05it/s, train/loss=10.30]
Epoch 0: | | 87/? [00:28<00:00, 3.05it/s, train/loss=10.30]
Epoch 0: | | 87/? [00:28<00:00, 3.05it/s, train/loss=30.40]
Epoch 0: | | 88/? [00:28<00:00, 3.05it/s, train/loss=30.40]
Epoch 0: | | 88/? [00:28<00:00, 3.05it/s, train/loss=27.20]
Epoch 0: | | 89/? [00:29<00:00, 3.05it/s, train/loss=27.20]
Epoch 0: | | 89/? [00:29<00:00, 3.05it/s, train/loss=36.90]
Epoch 0: | | 90/? [00:29<00:00, 3.04it/s, train/loss=36.90]
Epoch 0: | | 90/? [00:29<00:00, 3.04it/s, train/loss=15.30]
Epoch 0: | | 91/? [00:29<00:00, 3.04it/s, train/loss=15.30]
Epoch 0: | | 91/? [00:29<00:00, 3.04it/s, train/loss=25.40]
Epoch 0: | | 92/? [00:30<00:00, 3.04it/s, train/loss=25.40]
Epoch 0: | | 92/? [00:30<00:00, 3.04it/s, train/loss=18.00]
Epoch 0: | | 93/? [00:30<00:00, 3.04it/s, train/loss=18.00]
Epoch 0: | | 93/? [00:30<00:00, 3.04it/s, train/loss=30.60]
Epoch 0: | | 94/? [00:30<00:00, 3.04it/s, train/loss=30.60]
Epoch 0: | | 94/? [00:30<00:00, 3.04it/s, train/loss=22.00]
Epoch 0: | | 95/? [00:31<00:00, 3.04it/s, train/loss=22.00]
Epoch 0: | | 95/? [00:31<00:00, 3.04it/s, train/loss=13.20]
Epoch 0: | | 96/? [00:31<00:00, 3.05it/s, train/loss=13.20]
Epoch 0: | | 96/? [00:31<00:00, 3.05it/s, train/loss=28.90]
Epoch 0: | | 97/? [00:31<00:00, 3.04it/s, train/loss=28.90]
Epoch 0: | | 97/? [00:31<00:00, 3.04it/s, train/loss=43.10]
Epoch 0: | | 98/? [00:32<00:00, 3.04it/s, train/loss=43.10]
Epoch 0: | | 98/? [00:32<00:00, 3.04it/s, train/loss=24.10]
Epoch 0: | | 99/? [00:32<00:00, 3.04it/s, train/loss=24.10]
Epoch 0: | | 99/? [00:32<00:00, 3.04it/s, train/loss=35.90]
Epoch 0: | | 100/? [00:32<00:00, 3.04it/s, train/loss=35.90]
Epoch 0: | | 100/? [00:32<00:00, 3.04it/s, train/loss=54.40]
Epoch 0: | | 101/? [00:33<00:00, 3.04it/s, train/loss=54.40]
Epoch 0: | | 101/? [00:33<00:00, 3.04it/s, train/loss=39.20]
Epoch 0: | | 102/? [00:33<00:00, 3.02it/s, train/loss=39.20]
Epoch 0: | | 102/? [00:33<00:00, 3.02it/s, train/loss=26.30]
Epoch 0: | | 103/? [00:34<00:00, 3.01it/s, train/loss=26.30]
Epoch 0: | | 103/? [00:34<00:00, 3.01it/s, train/loss=11.30]
Epoch 0: | | 104/? [00:34<00:00, 3.00it/s, train/loss=11.30]
Epoch 0: | | 104/? [00:34<00:00, 3.00it/s, train/loss=16.80]
Epoch 0: | | 105/? [00:35<00:00, 2.99it/s, train/loss=16.80]
Epoch 0: | | 105/? [00:35<00:00, 2.99it/s, train/loss=28.70]
Epoch 0: | | 106/? [00:35<00:00, 2.98it/s, train/loss=28.70]
Epoch 0: | | 106/? [00:35<00:00, 2.98it/s, train/loss=24.10]
Epoch 0: | | 107/? [00:36<00:00, 2.97it/s, train/loss=24.10]
Epoch 0: | | 107/? [00:36<00:00, 2.97it/s, train/loss=25.80]
Epoch 0: | | 108/? [00:36<00:00, 2.95it/s, train/loss=25.80]
Epoch 0: | | 108/? [00:36<00:00, 2.95it/s, train/loss=35.10]
Epoch 0: | | 109/? [00:37<00:00, 2.94it/s, train/loss=35.10]
Epoch 0: | | 109/? [00:37<00:00, 2.94it/s, train/loss=34.00]
Epoch 0: | | 110/? [00:37<00:00, 2.95it/s, train/loss=34.00]
Epoch 0: | | 110/? [00:37<00:00, 2.95it/s, train/loss=10.00]
Epoch 0: | | 111/? [00:37<00:00, 2.95it/s, train/loss=10.00]
Epoch 0: | | 111/? [00:37<00:00, 2.95it/s, train/loss=18.90]
Epoch 0: | | 112/? [00:37<00:00, 2.95it/s, train/loss=18.90]
Epoch 0: | | 112/? [00:37<00:00, 2.95it/s, train/loss=16.30]
Epoch 0: | | 113/? [00:38<00:00, 2.95it/s, train/loss=16.30]
Epoch 0: | | 113/? [00:38<00:00, 2.95it/s, train/loss=26.50]
Epoch 0: | | 114/? [00:38<00:00, 2.95it/s, train/loss=26.50]
Epoch 0: | | 114/? [00:38<00:00, 2.95it/s, train/loss=23.80]
Epoch 0: | | 115/? [00:38<00:00, 2.95it/s, train/loss=23.80]
Epoch 0: | | 115/? [00:38<00:00, 2.95it/s, train/loss=19.70]
Epoch 0: | | 116/? [00:39<00:00, 2.95it/s, train/loss=19.70]
Epoch 0: | | 116/? [00:39<00:00, 2.95it/s, train/loss=28.20]
Epoch 0: | | 117/? [00:39<00:00, 2.95it/s, train/loss=28.20]
Epoch 0: | | 117/? [00:39<00:00, 2.95it/s, train/loss=26.90]
Epoch 0: | | 118/? [00:39<00:00, 2.95it/s, train/loss=26.90]
Epoch 0: | | 118/? [00:39<00:00, 2.95it/s, train/loss=12.40]
Epoch 0: | | 119/? [00:40<00:00, 2.95it/s, train/loss=12.40]
Epoch 0: | | 119/? [00:40<00:00, 2.95it/s, train/loss=25.70]
Epoch 0: | | 120/? [00:40<00:00, 2.96it/s, train/loss=25.70]
Epoch 0: | | 120/? [00:40<00:00, 2.96it/s, train/loss=15.50]
Epoch 0: | | 121/? [00:40<00:00, 2.96it/s, train/loss=15.50]
Epoch 0: | | 121/? [00:40<00:00, 2.96it/s, train/loss=33.20]
Epoch 0: | | 122/? [00:41<00:00, 2.96it/s, train/loss=33.20]
Epoch 0: | | 122/? [00:41<00:00, 2.96it/s, train/loss=29.20]
Epoch 0: | | 123/? [00:41<00:00, 2.96it/s, train/loss=29.20]
Epoch 0: | | 123/? [00:41<00:00, 2.96it/s, train/loss=14.80]
Epoch 0: | | 124/? [00:41<00:00, 2.96it/s, train/loss=14.80]
Epoch 0: | | 124/? [00:41<00:00, 2.96it/s, train/loss=19.00]
Epoch 0: | | 125/? [00:42<00:00, 2.96it/s, train/loss=19.00]
Epoch 0: | | 125/? [00:42<00:00, 2.96it/s, train/loss=35.50]
Epoch 0: | | 126/? [00:42<00:00, 2.96it/s, train/loss=35.50]
Epoch 0: | | 126/? [00:42<00:00, 2.96it/s, train/loss=30.20]
Epoch 0: | | 127/? [00:42<00:00, 2.96it/s, train/loss=30.20]
Epoch 0: | | 127/? [00:42<00:00, 2.96it/s, train/loss=11.70]
Epoch 0: | | 128/? [00:43<00:00, 2.96it/s, train/loss=11.70]
Epoch 0: | | 128/? [00:43<00:00, 2.96it/s, train/loss=33.50]
Epoch 0: | | 129/? [00:43<00:00, 2.96it/s, train/loss=33.50]
Epoch 0: | | 129/? [00:43<00:00, 2.96it/s, train/loss=21.60]
Epoch 0: | | 130/? [00:43<00:00, 2.96it/s, train/loss=21.60]
Epoch 0: | | 130/? [00:43<00:00, 2.96it/s, train/loss=31.00]
Epoch 0: | | 131/? [00:44<00:00, 2.96it/s, train/loss=31.00]
Epoch 0: | | 131/? [00:44<00:00, 2.96it/s, train/loss=7.040]
Epoch 0: | | 132/? [00:44<00:00, 2.96it/s, train/loss=7.040]
Epoch 0: | | 132/? [00:44<00:00, 2.96it/s, train/loss=18.30]
Epoch 0: | | 133/? [00:44<00:00, 2.96it/s, train/loss=18.30]
Epoch 0: | | 133/? [00:44<00:00, 2.96it/s, train/loss=50.90]
Epoch 0: | | 134/? [00:45<00:00, 2.96it/s, train/loss=50.90]
Epoch 0: | | 134/? [00:45<00:00, 2.96it/s, train/loss=36.30]
Epoch 0: | | 135/? [00:45<00:00, 2.96it/s, train/loss=36.30]
Epoch 0: | | 135/? [00:45<00:00, 2.96it/s, train/loss=16.50]
Epoch 0: | | 136/? [00:45<00:00, 2.96it/s, train/loss=16.50]
Epoch 0: | | 136/? [00:45<00:00, 2.96it/s, train/loss=37.00]
Epoch 0: | | 137/? [00:46<00:00, 2.96it/s, train/loss=37.00]
Epoch 0: | | 137/? [00:46<00:00, 2.96it/s, train/loss=30.50]
Epoch 0: | | 138/? [00:46<00:00, 2.96it/s, train/loss=30.50]
Epoch 0: | | 138/? [00:46<00:00, 2.96it/s, train/loss=9.030]
Epoch 0: | | 139/? [00:46<00:00, 2.96it/s, train/loss=9.030]
Epoch 0: | | 139/? [00:46<00:00, 2.96it/s, train/loss=64.00]
Epoch 0: | | 140/? [00:47<00:00, 2.97it/s, train/loss=64.00]
Epoch 0: | | 140/? [00:47<00:00, 2.97it/s, train/loss=21.90]
Epoch 0: | | 141/? [00:47<00:00, 2.97it/s, train/loss=21.90]
Epoch 0: | | 141/? [00:47<00:00, 2.97it/s, train/loss=20.40]
Epoch 0: | | 142/? [00:47<00:00, 2.97it/s, train/loss=20.40]
Epoch 0: | | 142/? [00:47<00:00, 2.97it/s, train/loss=23.60]
Epoch 0: | | 143/? [00:48<00:00, 2.97it/s, train/loss=23.60]
Epoch 0: | | 143/? [00:48<00:00, 2.97it/s, train/loss=9.380]
Epoch 0: | | 144/? [00:48<00:00, 2.97it/s, train/loss=9.380]
Epoch 0: | | 144/? [00:48<00:00, 2.97it/s, train/loss=28.20]
Epoch 0: | | 145/? [00:48<00:00, 2.97it/s, train/loss=28.20]
Epoch 0: | | 145/? [00:48<00:00, 2.97it/s, train/loss=49.70]
Epoch 0: | | 146/? [00:49<00:00, 2.97it/s, train/loss=49.70]
Epoch 0: | | 146/? [00:49<00:00, 2.97it/s, train/loss=22.60]
Epoch 0: | | 147/? [00:49<00:00, 2.97it/s, train/loss=22.60]
Epoch 0: | | 147/? [00:49<00:00, 2.97it/s, train/loss=31.20]
Epoch 0: | | 148/? [00:49<00:00, 2.97it/s, train/loss=31.20]
Epoch 0: | | 148/? [00:49<00:00, 2.97it/s, train/loss=12.40]
Epoch 0: | | 149/? [00:50<00:00, 2.97it/s, train/loss=12.40]
Epoch 0: | | 149/? [00:50<00:00, 2.97it/s, train/loss=26.90]
Epoch 0: | | 150/? [00:50<00:00, 2.97it/s, train/loss=26.90]
Epoch 0: | | 150/? [00:50<00:00, 2.97it/s, train/loss=29.40]
Epoch 0: | | 151/? [00:50<00:00, 2.97it/s, train/loss=29.40]
Epoch 0: | | 151/? [00:50<00:00, 2.97it/s, train/loss=15.90]
Epoch 0: | | 152/? [00:51<00:00, 2.97it/s, train/loss=15.90]
Epoch 0: | | 152/? [00:51<00:00, 2.97it/s, train/loss=34.20]
Epoch 0: | | 153/? [00:51<00:00, 2.97it/s, train/loss=34.20]
Epoch 0: | | 153/? [00:51<00:00, 2.97it/s, train/loss=27.00]
Epoch 0: | | 154/? [00:51<00:00, 2.97it/s, train/loss=27.00]
Epoch 0: | | 154/? [00:51<00:00, 2.97it/s, train/loss=20.90]
Epoch 0: | | 155/? [00:52<00:00, 2.97it/s, train/loss=20.90]
Epoch 0: | | 155/? [00:52<00:00, 2.97it/s, train/loss=28.60]
Epoch 0: | | 156/? [00:52<00:00, 2.97it/s, train/loss=28.60]
Epoch 0: | | 156/? [00:52<00:00, 2.97it/s, train/loss=15.00]
Epoch 0: | | 157/? [00:52<00:00, 2.97it/s, train/loss=15.00]
Epoch 0: | | 157/? [00:52<00:00, 2.97it/s, train/loss=18.70]
Epoch 0: | | 158/? [00:53<00:00, 2.98it/s, train/loss=18.70]
Epoch 0: | | 158/? [00:53<00:00, 2.98it/s, train/loss=21.40]
Epoch 0: | | 159/? [00:53<00:00, 2.98it/s, train/loss=21.40]
Epoch 0: | | 159/? [00:53<00:00, 2.98it/s, train/loss=37.80]
Epoch 0: | | 160/? [00:53<00:00, 2.98it/s, train/loss=37.80]
Epoch 0: | | 160/? [00:53<00:00, 2.98it/s, train/loss=16.10]
Epoch 0: | | 161/? [00:54<00:00, 2.98it/s, train/loss=16.10]
Epoch 0: | | 161/? [00:54<00:00, 2.98it/s, train/loss=29.40]
Epoch 0: | | 162/? [00:54<00:00, 2.98it/s, train/loss=29.40]
Epoch 0: | | 162/? [00:54<00:00, 2.98it/s, train/loss=27.00]
Epoch 0: | | 163/? [00:54<00:00, 2.98it/s, train/loss=27.00]
Epoch 0: | | 163/? [00:54<00:00, 2.98it/s, train/loss=30.00]
Epoch 0: | | 164/? [00:55<00:00, 2.98it/s, train/loss=30.00]
Epoch 0: | | 164/? [00:55<00:00, 2.98it/s, train/loss=23.00]
Epoch 0: | | 165/? [00:55<00:00, 2.98it/s, train/loss=23.00]
Epoch 0: | | 165/? [00:55<00:00, 2.98it/s, train/loss=19.30]
Epoch 0: | | 166/? [00:55<00:00, 2.98it/s, train/loss=19.30]
Epoch 0: | | 166/? [00:55<00:00, 2.98it/s, train/loss=7.840]
Epoch 0: | | 167/? [00:56<00:00, 2.98it/s, train/loss=7.840]
Epoch 0: | | 167/? [00:56<00:00, 2.98it/s, train/loss=23.30]
Epoch 0: | | 168/? [00:56<00:00, 2.98it/s, train/loss=23.30]
Epoch 0: | | 168/? [00:56<00:00, 2.98it/s, train/loss=28.90]
Epoch 0: | | 169/? [00:56<00:00, 2.98it/s, train/loss=28.90]
Epoch 0: | | 169/? [00:56<00:00, 2.98it/s, train/loss=41.70]
Epoch 0: | | 170/? [00:57<00:00, 2.98it/s, train/loss=41.70]
Epoch 0: | | 170/? [00:57<00:00, 2.98it/s, train/loss=25.60]
Epoch 0: | | 171/? [00:57<00:00, 2.98it/s, train/loss=25.60]
Epoch 0: | | 171/? [00:57<00:00, 2.98it/s, train/loss=9.550]
Epoch 0: | | 172/? [00:57<00:00, 2.98it/s, train/loss=9.550]
Epoch 0: | | 172/? [00:57<00:00, 2.98it/s, train/loss=8.980]
Epoch 0: | | 173/? [00:58<00:00, 2.98it/s, train/loss=8.980]
Epoch 0: | | 173/? [00:58<00:00, 2.98it/s, train/loss=41.40]
Epoch 0: | | 174/? [00:58<00:00, 2.97it/s, train/loss=41.40]
Epoch 0: | | 174/? [00:58<00:00, 2.97it/s, train/loss=14.10]
Epoch 0: | | 175/? [00:58<00:00, 2.97it/s, train/loss=14.10]
Epoch 0: | | 175/? [00:58<00:00, 2.97it/s, train/loss=42.50]
Epoch 0: | | 176/? [00:59<00:00, 2.97it/s, train/loss=42.50]
Epoch 0: | | 176/? [00:59<00:00, 2.97it/s, train/loss=18.90]
Epoch 0: | | 177/? [00:59<00:00, 2.97it/s, train/loss=18.90]
Epoch 0: | | 177/? [00:59<00:00, 2.97it/s, train/loss=52.70]
Epoch 0: | | 178/? [00:59<00:00, 2.97it/s, train/loss=52.70]
Epoch 0: | | 178/? [00:59<00:00, 2.97it/s, train/loss=21.30]
Epoch 0: | | 179/? [01:00<00:00, 2.97it/s, train/loss=21.30]
Epoch 0: | | 179/? [01:00<00:00, 2.97it/s, train/loss=26.90]
Epoch 0: | | 180/? [01:00<00:00, 2.97it/s, train/loss=26.90]
Epoch 0: | | 180/? [01:00<00:00, 2.97it/s, train/loss=43.90]
Epoch 0: | | 181/? [01:00<00:00, 2.97it/s, train/loss=43.90]
Epoch 0: | | 181/? [01:00<00:00, 2.97it/s, train/loss=30.30]
Epoch 0: | | 182/? [01:01<00:00, 2.97it/s, train/loss=30.30]
Epoch 0: | | 182/? [01:01<00:00, 2.97it/s, train/loss=14.80]
Epoch 0: | | 183/? [01:01<00:00, 2.97it/s, train/loss=14.80]
Epoch 0: | | 183/? [01:01<00:00, 2.97it/s, train/loss=9.860]
Epoch 0: | | 184/? [01:01<00:00, 2.97it/s, train/loss=9.860]
Epoch 0: | | 184/? [01:01<00:00, 2.97it/s, train/loss=40.60]
Epoch 0: | | 185/? [01:02<00:00, 2.97it/s, train/loss=40.60]
Epoch 0: | | 185/? [01:02<00:00, 2.97it/s, train/loss=17.30]
Epoch 0: | | 186/? [01:02<00:00, 2.97it/s, train/loss=17.30]
Epoch 0: | | 186/? [01:02<00:00, 2.97it/s, train/loss=17.20]
Epoch 0: | | 187/? [01:02<00:00, 2.97it/s, train/loss=17.20]
Epoch 0: | | 187/? [01:02<00:00, 2.97it/s, train/loss=30.70]
Epoch 0: | | 188/? [01:03<00:00, 2.97it/s, train/loss=30.70]
Epoch 0: | | 188/? [01:03<00:00, 2.97it/s, train/loss=30.50]
Epoch 0: | | 189/? [01:03<00:00, 2.97it/s, train/loss=30.50]
Epoch 0: | | 189/? [01:03<00:00, 2.97it/s, train/loss=34.40]
Epoch 0: | | 190/? [01:03<00:00, 2.97it/s, train/loss=34.40]
Epoch 0: | | 190/? [01:03<00:00, 2.97it/s, train/loss=18.50]
Epoch 0: | | 191/? [01:04<00:00, 2.97it/s, train/loss=18.50]
Epoch 0: | | 191/? [01:04<00:00, 2.97it/s, train/loss=10.70]
Epoch 0: | | 192/? [01:04<00:00, 2.98it/s, train/loss=10.70]
Epoch 0: | | 192/? [01:04<00:00, 2.98it/s, train/loss=10.90]
Epoch 0: | | 193/? [01:04<00:00, 2.98it/s, train/loss=10.90]
Epoch 0: | | 193/? [01:04<00:00, 2.98it/s, train/loss=42.30]
Epoch 0: | | 194/? [01:05<00:00, 2.98it/s, train/loss=42.30]
Epoch 0: | | 194/? [01:05<00:00, 2.98it/s, train/loss=15.00]
Epoch 0: | | 195/? [01:05<00:00, 2.98it/s, train/loss=15.00]
Epoch 0: | | 195/? [01:05<00:00, 2.98it/s, train/loss=24.30]
Epoch 0: | | 196/? [01:05<00:00, 2.98it/s, train/loss=24.30]
Epoch 0: | | 196/? [01:05<00:00, 2.98it/s, train/loss=23.80]
Epoch 0: | | 197/? [01:06<00:00, 2.98it/s, train/loss=23.80]
Epoch 0: | | 197/? [01:06<00:00, 2.98it/s, train/loss=23.20]
Epoch 0: | | 198/? [01:06<00:00, 2.98it/s, train/loss=23.20]
Epoch 0: | | 198/? [01:06<00:00, 2.98it/s, train/loss=9.060]
Epoch 0: | | 199/? [01:06<00:00, 2.98it/s, train/loss=9.060]
Epoch 0: | | 199/? [01:06<00:00, 2.98it/s, train/loss=24.10]
Epoch 0: | | 200/? [01:07<00:00, 2.98it/s, train/loss=24.10]
Epoch 0: | | 200/? [01:07<00:00, 2.98it/s, train/loss=19.50]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:03, 9.75it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:03, 10.64it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:03, 10.96it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:03, 11.13it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:03, 11.22it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:03, 11.32it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:02, 11.34it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:02, 11.39it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:02, 11.38it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:02, 11.46it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:02, 11.53it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:02, 11.59it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:02, 11.56it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 11.57it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 11.60it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 11.61it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:01, 11.63it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:01<00:01, 11.64it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:01<00:01, 11.65it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:01<00:01, 11.66it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:01<00:01, 11.65it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:01<00:01, 11.67it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:01<00:01, 11.68it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 11.66it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 11.65it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 11.64it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 11.64it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:02<00:01, 11.63it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:02<00:00, 11.65it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:02<00:00, 11.67it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:02<00:00, 11.67it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:02<00:00, 11.66it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:02<00:00, 11.67it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:02<00:00, 11.66it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 11.64it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:03<00:00, 11.62it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:03<00:00, 11.60it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:03<00:00, 11.59it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:03<00:00, 11.58it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.57it/s][A
[A
Epoch 0: | | 200/? [01:14<00:00, 2.70it/s, train/loss=19.50]
Epoch 0: | | 201/? [01:15<00:00, 2.68it/s, train/loss=19.50]
Epoch 0: | | 201/? [01:15<00:00, 2.68it/s, train/loss=18.40]
Epoch 0: | | 202/? [01:15<00:00, 2.68it/s, train/loss=18.40]
Epoch 0: | | 202/? [01:15<00:00, 2.68it/s, train/loss=21.90]
Epoch 0: | | 203/? [01:15<00:00, 2.68it/s, train/loss=21.90]
Epoch 0: | | 203/? [01:15<00:00, 2.68it/s, train/loss=24.70]
Epoch 0: | | 204/? [01:16<00:00, 2.68it/s, train/loss=24.70]
Epoch 0: | | 204/? [01:16<00:00, 2.68it/s, train/loss=20.40]
Epoch 0: | | 205/? [01:16<00:00, 2.68it/s, train/loss=20.40]
Epoch 0: | | 205/? [01:16<00:00, 2.68it/s, train/loss=24.10]
Epoch 0: | | 206/? [01:16<00:00, 2.68it/s, train/loss=24.10]
Epoch 0: | | 206/? [01:16<00:00, 2.68it/s, train/loss=29.90]
Epoch 0: | | 207/? [01:17<00:00, 2.68it/s, train/loss=29.90]
Epoch 0: | | 207/? [01:17<00:00, 2.68it/s, train/loss=9.750]
Epoch 0: | | 208/? [01:17<00:00, 2.68it/s, train/loss=9.750]
Epoch 0: | | 208/? [01:17<00:00, 2.68it/s, train/loss=20.60]
Epoch 0: | | 209/? [01:17<00:00, 2.68it/s, train/loss=20.60]
Epoch 0: | | 209/? [01:17<00:00, 2.68it/s, train/loss=31.50]
Epoch 0: | | 210/? [01:18<00:00, 2.69it/s, train/loss=31.50]
Epoch 0: | | 210/? [01:18<00:00, 2.69it/s, train/loss=26.50]
Epoch 0: | | 211/? [01:18<00:00, 2.69it/s, train/loss=26.50]
Epoch 0: | | 211/? [01:18<00:00, 2.69it/s, train/loss=44.80]
Epoch 0: | | 212/? [01:18<00:00, 2.69it/s, train/loss=44.80]
Epoch 0: | | 212/? [01:18<00:00, 2.69it/s, train/loss=12.50]
Epoch 0: | | 213/? [01:19<00:00, 2.69it/s, train/loss=12.50]
Epoch 0: | | 213/? [01:19<00:00, 2.69it/s, train/loss=22.50]
Epoch 0: | | 214/? [01:19<00:00, 2.69it/s, train/loss=22.50]
Epoch 0: | | 214/? [01:19<00:00, 2.69it/s, train/loss=22.90]
Epoch 0: | | 215/? [01:19<00:00, 2.69it/s, train/loss=22.90]
Epoch 0: | | 215/? [01:19<00:00, 2.69it/s, train/loss=12.00]
Epoch 0: | | 216/? [01:20<00:00, 2.70it/s, train/loss=12.00]
Epoch 0: | | 216/? [01:20<00:00, 2.70it/s, train/loss=22.50]
Epoch 0: | | 217/? [01:20<00:00, 2.70it/s, train/loss=22.50]
Epoch 0: | | 217/? [01:20<00:00, 2.70it/s, train/loss=22.90]
Epoch 0: | | 218/? [01:20<00:00, 2.70it/s, train/loss=22.90]
Epoch 0: | | 218/? [01:20<00:00, 2.70it/s, train/loss=26.30]
Epoch 0: | | 219/? [01:21<00:00, 2.70it/s, train/loss=26.30]
Epoch 0: | | 219/? [01:21<00:00, 2.70it/s, train/loss=12.70]
Epoch 0: | | 220/? [01:21<00:00, 2.70it/s, train/loss=12.70]
Epoch 0: | | 220/? [01:21<00:00, 2.70it/s, train/loss=12.20]
Epoch 0: | | 221/? [01:21<00:00, 2.70it/s, train/loss=12.20]
Epoch 0: | | 221/? [01:21<00:00, 2.70it/s, train/loss=33.90]
Epoch 0: | | 222/? [01:22<00:00, 2.70it/s, train/loss=33.90]
Epoch 0: | | 222/? [01:22<00:00, 2.70it/s, train/loss=21.90]
Epoch 0: | | 223/? [01:22<00:00, 2.70it/s, train/loss=21.90]
Epoch 0: | | 223/? [01:22<00:00, 2.70it/s, train/loss=9.470]
Epoch 0: | | 224/? [01:22<00:00, 2.70it/s, train/loss=9.470]
Epoch 0: | | 224/? [01:22<00:00, 2.70it/s, train/loss=29.10]
Epoch 0: | | 225/? [01:23<00:00, 2.70it/s, train/loss=29.10]
Epoch 0: | | 225/? [01:23<00:00, 2.70it/s, train/loss=34.40]
Epoch 0: | | 226/? [01:23<00:00, 2.71it/s, train/loss=34.40]
Epoch 0: | | 226/? [01:23<00:00, 2.71it/s, train/loss=17.00]
Epoch 0: | | 227/? [01:23<00:00, 2.71it/s, train/loss=17.00]
Epoch 0: | | 227/? [01:23<00:00, 2.71it/s, train/loss=23.90]
Epoch 0: | | 228/? [01:24<00:00, 2.71it/s, train/loss=23.90]
Epoch 0: | | 228/? [01:24<00:00, 2.71it/s, train/loss=12.90]
Epoch 0: | | 229/? [01:24<00:00, 2.70it/s, train/loss=12.90]
Epoch 0: | | 229/? [01:24<00:00, 2.70it/s, train/loss=27.10]
Epoch 0: | | 230/? [01:25<00:00, 2.70it/s, train/loss=27.10]
Epoch 0: | | 230/? [01:25<00:00, 2.70it/s, train/loss=18.10]
Epoch 0: | | 231/? [01:25<00:00, 2.70it/s, train/loss=18.10]
Epoch 0: | | 231/? [01:25<00:00, 2.70it/s, train/loss=23.10]
Epoch 0: | | 232/? [01:25<00:00, 2.70it/s, train/loss=23.10]
Epoch 0: | | 232/? [01:25<00:00, 2.70it/s, train/loss=32.00]
Epoch 0: | | 233/? [01:26<00:00, 2.70it/s, train/loss=32.00]
Epoch 0: | | 233/? [01:26<00:00, 2.70it/s, train/loss=39.00]
Epoch 0: | | 234/? [01:26<00:00, 2.70it/s, train/loss=39.00]
Epoch 0: | | 234/? [01:26<00:00, 2.70it/s, train/loss=17.50]
Epoch 0: | | 235/? [01:27<00:00, 2.70it/s, train/loss=17.50]
Epoch 0: | | 235/? [01:27<00:00, 2.70it/s, train/loss=27.30]
Epoch 0: | | 236/? [01:27<00:00, 2.70it/s, train/loss=27.30]
Epoch 0: | | 236/? [01:27<00:00, 2.70it/s, train/loss=17.20]
Epoch 0: | | 237/? [01:27<00:00, 2.70it/s, train/loss=17.20]
Epoch 0: | | 237/? [01:27<00:00, 2.70it/s, train/loss=21.60]
Epoch 0: | | 238/? [01:28<00:00, 2.70it/s, train/loss=21.60]
Epoch 0: | | 238/? [01:28<00:00, 2.70it/s, train/loss=27.00]
Epoch 0: | | 239/? [01:28<00:00, 2.70it/s, train/loss=27.00]
Epoch 0: | | 239/? [01:28<00:00, 2.70it/s, train/loss=24.70]
Epoch 0: | | 240/? [01:28<00:00, 2.71it/s, train/loss=24.70]
Epoch 0: | | 240/? [01:28<00:00, 2.71it/s, train/loss=19.30]
Epoch 0: | | 241/? [01:29<00:00, 2.71it/s, train/loss=19.30]
Epoch 0: | | 241/? [01:29<00:00, 2.71it/s, train/loss=31.30]
Epoch 0: | | 242/? [01:29<00:00, 2.71it/s, train/loss=31.30]
Epoch 0: | | 242/? [01:29<00:00, 2.71it/s, train/loss=33.00]
Epoch 0: | | 243/? [01:29<00:00, 2.71it/s, train/loss=33.00]
Epoch 0: | | 243/? [01:29<00:00, 2.71it/s, train/loss=36.70]
Epoch 0: | | 244/? [01:29<00:00, 2.71it/s, train/loss=36.70]
Epoch 0: | | 244/? [01:29<00:00, 2.71it/s, train/loss=11.30]
Epoch 0: | | 245/? [01:30<00:00, 2.71it/s, train/loss=11.30]
Epoch 0: | | 245/? [01:30<00:00, 2.71it/s, train/loss=29.30]
Epoch 0: | | 246/? [01:30<00:00, 2.71it/s, train/loss=29.30]
Epoch 0: | | 246/? [01:30<00:00, 2.71it/s, train/loss=29.50]
Epoch 0: | | 247/? [01:30<00:00, 2.72it/s, train/loss=29.50]
Epoch 0: | | 247/? [01:30<00:00, 2.71it/s, train/loss=38.30]
Epoch 0: | | 248/? [01:31<00:00, 2.72it/s, train/loss=38.30]
Epoch 0: | | 248/? [01:31<00:00, 2.72it/s, train/loss=31.60]
Epoch 0: | | 249/? [01:31<00:00, 2.72it/s, train/loss=31.60]
Epoch 0: | | 249/? [01:31<00:00, 2.72it/s, train/loss=25.80]
Epoch 0: | | 250/? [01:31<00:00, 2.72it/s, train/loss=25.80]
Epoch 0: | | 250/? [01:31<00:00, 2.72it/s, train/loss=22.20]
Epoch 0: | | 251/? [01:32<00:00, 2.72it/s, train/loss=22.20]
Epoch 0: | | 251/? [01:32<00:00, 2.72it/s, train/loss=20.50]
Epoch 0: | | 252/? [01:32<00:00, 2.72it/s, train/loss=20.50]
Epoch 0: | | 252/? [01:32<00:00, 2.72it/s, train/loss=12.90]
Epoch 0: | | 253/? [01:32<00:00, 2.72it/s, train/loss=12.90]
Epoch 0: | | 253/? [01:32<00:00, 2.72it/s, train/loss=34.50]
Epoch 0: | | 254/? [01:33<00:00, 2.72it/s, train/loss=34.50]
Epoch 0: | | 254/? [01:33<00:00, 2.72it/s, train/loss=21.40]
Epoch 0: | | 255/? [01:33<00:00, 2.72it/s, train/loss=21.40]
Epoch 0: | | 255/? [01:33<00:00, 2.72it/s, train/loss=20.10]
Epoch 0: | | 256/? [01:33<00:00, 2.73it/s, train/loss=20.10]
Epoch 0: | | 256/? [01:33<00:00, 2.73it/s, train/loss=9.920]
Epoch 0: | | 257/? [01:34<00:00, 2.73it/s, train/loss=9.920]
Epoch 0: | | 257/? [01:34<00:00, 2.73it/s, train/loss=26.10]
Epoch 0: | | 258/? [01:34<00:00, 2.73it/s, train/loss=26.10]
Epoch 0: | | 258/? [01:34<00:00, 2.73it/s, train/loss=22.30]
Epoch 0: | | 259/? [01:34<00:00, 2.73it/s, train/loss=22.30]
Epoch 0: | | 259/? [01:34<00:00, 2.73it/s, train/loss=22.70]
Epoch 0: | | 260/? [01:35<00:00, 2.73it/s, train/loss=22.70]
Epoch 0: | | 260/? [01:35<00:00, 2.73it/s, train/loss=10.50]
Epoch 0: | | 261/? [01:35<00:00, 2.73it/s, train/loss=10.50]
Epoch 0: | | 261/? [01:35<00:00, 2.73it/s, train/loss=19.80]
Epoch 0: | | 262/? [01:35<00:00, 2.73it/s, train/loss=19.80]
Epoch 0: | | 262/? [01:35<00:00, 2.73it/s, train/loss=26.50]
Epoch 0: | | 263/? [01:36<00:00, 2.73it/s, train/loss=26.50]
Epoch 0: | | 263/? [01:36<00:00, 2.73it/s, train/loss=15.90]
Epoch 0: | | 264/? [01:36<00:00, 2.73it/s, train/loss=15.90]
Epoch 0: | | 264/? [01:36<00:00, 2.73it/s, train/loss=83.00]
Epoch 0: | | 265/? [01:36<00:00, 2.73it/s, train/loss=83.00]
Epoch 0: | | 265/? [01:36<00:00, 2.73it/s, train/loss=19.80]
Epoch 0: | | 266/? [01:37<00:00, 2.74it/s, train/loss=19.80]
Epoch 0: | | 266/? [01:37<00:00, 2.74it/s, train/loss=27.80]
Epoch 0: | | 267/? [01:37<00:00, 2.74it/s, train/loss=27.80]
Epoch 0: | | 267/? [01:37<00:00, 2.74it/s, train/loss=12.90]
Epoch 0: | | 268/? [01:37<00:00, 2.74it/s, train/loss=12.90]
Epoch 0: | | 268/? [01:37<00:00, 2.74it/s, train/loss=37.60]
Epoch 0: | | 269/? [01:38<00:00, 2.74it/s, train/loss=37.60]
Epoch 0: | | 269/? [01:38<00:00, 2.74it/s, train/loss=18.00]
Epoch 0: | | 270/? [01:38<00:00, 2.74it/s, train/loss=18.00]
Epoch 0: | | 270/? [01:38<00:00, 2.74it/s, train/loss=30.10]
Epoch 0: | | 271/? [01:38<00:00, 2.74it/s, train/loss=30.10]
Epoch 0: | | 271/? [01:38<00:00, 2.74it/s, train/loss=26.90]
Epoch 0: | | 272/? [01:39<00:00, 2.74it/s, train/loss=26.90]
Epoch 0: | | 272/? [01:39<00:00, 2.74it/s, train/loss=24.70]
Epoch 0: | | 273/? [01:39<00:00, 2.74it/s, train/loss=24.70]
Epoch 0: | | 273/? [01:39<00:00, 2.74it/s, train/loss=30.30]
Epoch 0: | | 274/? [01:40<00:00, 2.73it/s, train/loss=30.30]
Epoch 0: | | 274/? [01:40<00:00, 2.73it/s, train/loss=23.30]
Epoch 0: | | 275/? [01:40<00:00, 2.74it/s, train/loss=23.30]
Epoch 0: | | 275/? [01:40<00:00, 2.74it/s, train/loss=19.70]
Epoch 0: | | 276/? [01:40<00:00, 2.74it/s, train/loss=19.70]
Epoch 0: | | 276/? [01:40<00:00, 2.74it/s, train/loss=25.70]
Epoch 0: | | 277/? [01:41<00:00, 2.74it/s, train/loss=25.70]
Epoch 0: | | 277/? [01:41<00:00, 2.74it/s, train/loss=43.30]
Epoch 0: | | 278/? [01:41<00:00, 2.74it/s, train/loss=43.30]
Epoch 0: | | 278/? [01:41<00:00, 2.74it/s, train/loss=29.50]
Epoch 0: | | 279/? [01:41<00:00, 2.74it/s, train/loss=29.50]
Epoch 0: | | 279/? [01:41<00:00, 2.74it/s, train/loss=25.80]
Epoch 0: | | 280/? [01:42<00:00, 2.74it/s, train/loss=25.80]
Epoch 0: | | 280/? [01:42<00:00, 2.74it/s, train/loss=73.00]
Epoch 0: | | 281/? [01:42<00:00, 2.74it/s, train/loss=73.00]
Epoch 0: | | 281/? [01:42<00:00, 2.74it/s, train/loss=34.10]
Epoch 0: | | 282/? [01:42<00:00, 2.74it/s, train/loss=34.10]
Epoch 0: | | 282/? [01:42<00:00, 2.74it/s, train/loss=16.80]
Epoch 0: | | 283/? [01:43<00:00, 2.74it/s, train/loss=16.80]
Epoch 0: | | 283/? [01:43<00:00, 2.74it/s, train/loss=23.70]
Epoch 0: | | 284/? [01:43<00:00, 2.73it/s, train/loss=23.70]
Epoch 0: | | 284/? [01:43<00:00, 2.73it/s, train/loss=42.90]
Epoch 0: | | 285/? [01:44<00:00, 2.74it/s, train/loss=42.90]
Epoch 0: | | 285/? [01:44<00:00, 2.73it/s, train/loss=18.10]
Epoch 0: | | 286/? [01:44<00:00, 2.74it/s, train/loss=18.10]
Epoch 0: | | 286/? [01:44<00:00, 2.74it/s, train/loss=16.30]
Epoch 0: | | 287/? [01:44<00:00, 2.74it/s, train/loss=16.30]
Epoch 0: | | 287/? [01:44<00:00, 2.74it/s, train/loss=24.40]
Epoch 0: | | 288/? [01:45<00:00, 2.74it/s, train/loss=24.40]
Epoch 0: | | 288/? [01:45<00:00, 2.74it/s, train/loss=18.90]
Epoch 0: | | 289/? [01:45<00:00, 2.74it/s, train/loss=18.90]
Epoch 0: | | 289/? [01:45<00:00, 2.74it/s, train/loss=29.20]
Epoch 0: | | 290/? [01:45<00:00, 2.74it/s, train/loss=29.20]
Epoch 0: | | 290/? [01:45<00:00, 2.74it/s, train/loss=15.30]
Epoch 0: | | 291/? [01:46<00:00, 2.74it/s, train/loss=15.30]
Epoch 0: | | 291/? [01:46<00:00, 2.74it/s, train/loss=48.50]
Epoch 0: | | 292/? [01:46<00:00, 2.74it/s, train/loss=48.50]
Epoch 0: | | 292/? [01:46<00:00, 2.74it/s, train/loss=17.30]
Epoch 0: | | 293/? [01:46<00:00, 2.74it/s, train/loss=17.30]
Epoch 0: | | 293/? [01:46<00:00, 2.74it/s, train/loss=32.00]
Epoch 0: | | 294/? [01:47<00:00, 2.74it/s, train/loss=32.00]
Epoch 0: | | 294/? [01:47<00:00, 2.74it/s, train/loss=15.80]
Epoch 0: | | 295/? [01:47<00:00, 2.74it/s, train/loss=15.80]
Epoch 0: | | 295/? [01:47<00:00, 2.74it/s, train/loss=11.20]
Epoch 0: | | 296/? [01:48<00:00, 2.74it/s, train/loss=11.20]
Epoch 0: | | 296/? [01:48<00:00, 2.74it/s, train/loss=13.20]
Epoch 0: | | 297/? [01:48<00:00, 2.74it/s, train/loss=13.20]
Epoch 0: | | 297/? [01:48<00:00, 2.74it/s, train/loss=17.20]
Epoch 0: | | 298/? [01:48<00:00, 2.74it/s, train/loss=17.20]
Epoch 0: | | 298/? [01:48<00:00, 2.74it/s, train/loss=16.80]
Epoch 0: | | 299/? [01:49<00:00, 2.74it/s, train/loss=16.80]
Epoch 0: | | 299/? [01:49<00:00, 2.74it/s, train/loss=20.00]
Epoch 0: | | 300/? [01:49<00:00, 2.74it/s, train/loss=20.00]
Epoch 0: | | 300/? [01:49<00:00, 2.74it/s, train/loss=17.50]
Epoch 0: | | 301/? [01:49<00:00, 2.74it/s, train/loss=17.50]
Epoch 0: | | 301/? [01:49<00:00, 2.74it/s, train/loss=31.60]
Epoch 0: | | 302/? [01:50<00:00, 2.74it/s, train/loss=31.60]
Epoch 0: | | 302/? [01:50<00:00, 2.74it/s, train/loss=17.70]
Epoch 0: | | 303/? [01:50<00:00, 2.74it/s, train/loss=17.70]
Epoch 0: | | 303/? [01:50<00:00, 2.74it/s, train/loss=6.190]
Epoch 0: | | 304/? [01:50<00:00, 2.74it/s, train/loss=6.190]
Epoch 0: | | 304/? [01:50<00:00, 2.74it/s, train/loss=22.80]
Epoch 0: | | 305/? [01:51<00:00, 2.74it/s, train/loss=22.80]
Epoch 0: | | 305/? [01:51<00:00, 2.74it/s, train/loss=20.90]
Epoch 0: | | 306/? [01:51<00:00, 2.74it/s, train/loss=20.90]
Epoch 0: | | 306/? [01:51<00:00, 2.74it/s, train/loss=26.30]
Epoch 0: | | 307/? [01:51<00:00, 2.74it/s, train/loss=26.30]
Epoch 0: | | 307/? [01:51<00:00, 2.74it/s, train/loss=24.20]
Epoch 0: | | 308/? [01:52<00:00, 2.74it/s, train/loss=24.20]
Epoch 0: | | 308/? [01:52<00:00, 2.74it/s, train/loss=14.50]
Epoch 0: | | 309/? [01:52<00:00, 2.74it/s, train/loss=14.50]
Epoch 0: | | 309/? [01:52<00:00, 2.74it/s, train/loss=28.30]
Epoch 0: | | 310/? [01:52<00:00, 2.74it/s, train/loss=28.30]
Epoch 0: | | 310/? [01:52<00:00, 2.74it/s, train/loss=28.40]
Epoch 0: | | 311/? [01:53<00:00, 2.74it/s, train/loss=28.40]
Epoch 0: | | 311/? [01:53<00:00, 2.74it/s, train/loss=25.70]
Epoch 0: | | 312/? [01:53<00:00, 2.75it/s, train/loss=25.70]
Epoch 0: | | 312/? [01:53<00:00, 2.75it/s, train/loss=43.80]
Epoch 0: | | 313/? [01:53<00:00, 2.75it/s, train/loss=43.80]
Epoch 0: | | 313/? [01:53<00:00, 2.75it/s, train/loss=20.80]
Epoch 0: | | 314/? [01:54<00:00, 2.75it/s, train/loss=20.80]
Epoch 0: | | 314/? [01:54<00:00, 2.75it/s, train/loss=41.50]
Epoch 0: | | 315/? [01:54<00:00, 2.75it/s, train/loss=41.50]
Epoch 0: | | 315/? [01:54<00:00, 2.75it/s, train/loss=18.30]
Epoch 0: | | 316/? [01:54<00:00, 2.75it/s, train/loss=18.30]
Epoch 0: | | 316/? [01:54<00:00, 2.75it/s, train/loss=16.40]
Epoch 0: | | 317/? [01:55<00:00, 2.75it/s, train/loss=16.40]
Epoch 0: | | 317/? [01:55<00:00, 2.75it/s, train/loss=21.20]
Epoch 0: | | 318/? [01:55<00:00, 2.75it/s, train/loss=21.20]
Epoch 0: | | 318/? [01:55<00:00, 2.75it/s, train/loss=32.10]
Epoch 0: | | 319/? [01:55<00:00, 2.75it/s, train/loss=32.10]
Epoch 0: | | 319/? [01:55<00:00, 2.75it/s, train/loss=21.10]
Epoch 0: | | 320/? [01:56<00:00, 2.75it/s, train/loss=21.10]
Epoch 0: | | 320/? [01:56<00:00, 2.75it/s, train/loss=17.00]
Epoch 0: | | 321/? [01:56<00:00, 2.75it/s, train/loss=17.00]
Epoch 0: | | 321/? [01:56<00:00, 2.75it/s, train/loss=23.70]
Epoch 0: | | 322/? [01:56<00:00, 2.75it/s, train/loss=23.70]
Epoch 0: | | 322/? [01:56<00:00, 2.75it/s, train/loss=26.10]
Epoch 0: | | 323/? [01:57<00:00, 2.76it/s, train/loss=26.10]
Epoch 0: | | 323/? [01:57<00:00, 2.76it/s, train/loss=24.10]
Epoch 0: | | 324/? [01:57<00:00, 2.76it/s, train/loss=24.10]
Epoch 0: | | 324/? [01:57<00:00, 2.76it/s, train/loss=17.70]
Epoch 0: | | 325/? [01:57<00:00, 2.76it/s, train/loss=17.70]
Epoch 0: | | 325/? [01:57<00:00, 2.76it/s, train/loss=33.40]
Epoch 0: | | 326/? [01:58<00:00, 2.76it/s, train/loss=33.40]
Epoch 0: | | 326/? [01:58<00:00, 2.76it/s, train/loss=22.60]
Epoch 0: | | 327/? [01:58<00:00, 2.76it/s, train/loss=22.60]
Epoch 0: | | 327/? [01:58<00:00, 2.76it/s, train/loss=14.40]
Epoch 0: | | 328/? [01:58<00:00, 2.76it/s, train/loss=14.40]
Epoch 0: | | 328/? [01:58<00:00, 2.76it/s, train/loss=23.20]
Epoch 0: | | 329/? [01:59<00:00, 2.76it/s, train/loss=23.20]
Epoch 0: | | 329/? [01:59<00:00, 2.76it/s, train/loss=32.80]
Epoch 0: | | 330/? [01:59<00:00, 2.76it/s, train/loss=32.80]
Epoch 0: | | 330/? [01:59<00:00, 2.76it/s, train/loss=25.70]
Epoch 0: | | 331/? [01:59<00:00, 2.76it/s, train/loss=25.70]
Epoch 0: | | 331/? [01:59<00:00, 2.76it/s, train/loss=10.00]
Epoch 0: | | 332/? [02:00<00:00, 2.76it/s, train/loss=10.00]
Epoch 0: | | 332/? [02:00<00:00, 2.76it/s, train/loss=13.80]
Epoch 0: | | 333/? [02:00<00:00, 2.76it/s, train/loss=13.80]
Epoch 0: | | 333/? [02:00<00:00, 2.76it/s, train/loss=14.90]
Epoch 0: | | 334/? [02:00<00:00, 2.76it/s, train/loss=14.90]
Epoch 0: | | 334/? [02:00<00:00, 2.76it/s, train/loss=25.70]
Epoch 0: | | 335/? [02:01<00:00, 2.77it/s, train/loss=25.70]
Epoch 0: | | 335/? [02:01<00:00, 2.77it/s, train/loss=28.00]
Epoch 0: | | 336/? [02:01<00:00, 2.77it/s, train/loss=28.00]
Epoch 0: | | 336/? [02:01<00:00, 2.77it/s, train/loss=8.200]
Epoch 0: | | 337/? [02:01<00:00, 2.77it/s, train/loss=8.200]
Epoch 0: | | 337/? [02:01<00:00, 2.77it/s, train/loss=28.30]
Epoch 0: | | 338/? [02:02<00:00, 2.77it/s, train/loss=28.30]
Epoch 0: | | 338/? [02:02<00:00, 2.77it/s, train/loss=18.60]
Epoch 0: | | 339/? [02:02<00:00, 2.77it/s, train/loss=18.60]
Epoch 0: | | 339/? [02:02<00:00, 2.77it/s, train/loss=31.30]
Epoch 0: | | 340/? [02:02<00:00, 2.77it/s, train/loss=31.30]
Epoch 0: | | 340/? [02:02<00:00, 2.77it/s, train/loss=33.80]
Epoch 0: | | 341/? [02:03<00:00, 2.77it/s, train/loss=33.80]
Epoch 0: | | 341/? [02:03<00:00, 2.77it/s, train/loss=27.80]
Epoch 0: | | 342/? [02:03<00:00, 2.77it/s, train/loss=27.80]
Epoch 0: | | 342/? [02:03<00:00, 2.77it/s, train/loss=25.80]
Epoch 0: | | 343/? [02:03<00:00, 2.77it/s, train/loss=25.80]
Epoch 0: | | 343/? [02:03<00:00, 2.77it/s, train/loss=10.80]
Epoch 0: | | 344/? [02:04<00:00, 2.77it/s, train/loss=10.80]
Epoch 0: | | 344/? [02:04<00:00, 2.77it/s, train/loss=21.40]
Epoch 0: | | 345/? [02:04<00:00, 2.77it/s, train/loss=21.40]
Epoch 0: | | 345/? [02:04<00:00, 2.77it/s, train/loss=27.50]
Epoch 0: | | 346/? [02:04<00:00, 2.77it/s, train/loss=27.50]
Epoch 0: | | 346/? [02:04<00:00, 2.77it/s, train/loss=26.90]
Epoch 0: | | 347/? [02:05<00:00, 2.77it/s, train/loss=26.90]
Epoch 0: | | 347/? [02:05<00:00, 2.77it/s, train/loss=9.160]
Epoch 0: | | 348/? [02:05<00:00, 2.78it/s, train/loss=9.160]
Epoch 0: | | 348/? [02:05<00:00, 2.78it/s, train/loss=16.30]
Epoch 0: | | 349/? [02:05<00:00, 2.78it/s, train/loss=16.30]
Epoch 0: | | 349/? [02:05<00:00, 2.78it/s, train/loss=18.30]
Epoch 0: | | 350/? [02:06<00:00, 2.78it/s, train/loss=18.30]
Epoch 0: | | 350/? [02:06<00:00, 2.78it/s, train/loss=27.30]
Epoch 0: | | 351/? [02:06<00:00, 2.78it/s, train/loss=27.30]
Epoch 0: | | 351/? [02:06<00:00, 2.78it/s, train/loss=20.10]
Epoch 0: | | 352/? [02:06<00:00, 2.78it/s, train/loss=20.10]
Epoch 0: | | 352/? [02:06<00:00, 2.78it/s, train/loss=10.80]
Epoch 0: | | 353/? [02:07<00:00, 2.78it/s, train/loss=10.80]
Epoch 0: | | 353/? [02:07<00:00, 2.78it/s, train/loss=39.30]
Epoch 0: | | 354/? [02:07<00:00, 2.78it/s, train/loss=39.30]
Epoch 0: | | 354/? [02:07<00:00, 2.78it/s, train/loss=38.70]
Epoch 0: | | 355/? [02:07<00:00, 2.78it/s, train/loss=38.70]
Epoch 0: | | 355/? [02:07<00:00, 2.78it/s, train/loss=32.30]
Epoch 0: | | 356/? [02:08<00:00, 2.78it/s, train/loss=32.30]
Epoch 0: | | 356/? [02:08<00:00, 2.78it/s, train/loss=16.10]
Epoch 0: | | 357/? [02:08<00:00, 2.78it/s, train/loss=16.10]
Epoch 0: | | 357/? [02:08<00:00, 2.78it/s, train/loss=33.00]
Epoch 0: | | 358/? [02:08<00:00, 2.78it/s, train/loss=33.00]
Epoch 0: | | 358/? [02:08<00:00, 2.78it/s, train/loss=28.10]
Epoch 0: | | 359/? [02:08<00:00, 2.78it/s, train/loss=28.10]
Epoch 0: | | 359/? [02:08<00:00, 2.78it/s, train/loss=9.550]
Epoch 0: | | 360/? [02:09<00:00, 2.78it/s, train/loss=9.550]
Epoch 0: | | 360/? [02:09<00:00, 2.78it/s, train/loss=16.10]
Epoch 0: | | 361/? [02:09<00:00, 2.78it/s, train/loss=16.10]
Epoch 0: | | 361/? [02:09<00:00, 2.78it/s, train/loss=33.40]
Epoch 0: | | 362/? [02:09<00:00, 2.79it/s, train/loss=33.40]
Epoch 0: | | 362/? [02:09<00:00, 2.79it/s, train/loss=12.90]
Epoch 0: | | 363/? [02:10<00:00, 2.79it/s, train/loss=12.90]
Epoch 0: | | 363/? [02:10<00:00, 2.79it/s, train/loss=7.820]
Epoch 0: | | 364/? [02:10<00:00, 2.79it/s, train/loss=7.820]
Epoch 0: | | 364/? [02:10<00:00, 2.79it/s, train/loss=31.80]
Epoch 0: | | 365/? [02:10<00:00, 2.79it/s, train/loss=31.80]
Epoch 0: | | 365/? [02:10<00:00, 2.79it/s, train/loss=23.70]
Epoch 0: | | 366/? [02:11<00:00, 2.79it/s, train/loss=23.70]
Epoch 0: | | 366/? [02:11<00:00, 2.79it/s, train/loss=30.10]
Epoch 0: | | 367/? [02:11<00:00, 2.79it/s, train/loss=30.10]
Epoch 0: | | 367/? [02:11<00:00, 2.79it/s, train/loss=60.60]
Epoch 0: | | 368/? [02:11<00:00, 2.79it/s, train/loss=60.60]
Epoch 0: | | 368/? [02:11<00:00, 2.79it/s, train/loss=17.70]
Epoch 0: | | 369/? [02:12<00:00, 2.79it/s, train/loss=17.70]
Epoch 0: | | 369/? [02:12<00:00, 2.79it/s, train/loss=22.10]
Epoch 0: | | 370/? [02:12<00:00, 2.78it/s, train/loss=22.10]
Epoch 0: | | 370/? [02:12<00:00, 2.78it/s, train/loss=32.60]
Epoch 0: | | 371/? [02:13<00:00, 2.78it/s, train/loss=32.60]
Epoch 0: | | 371/? [02:13<00:00, 2.78it/s, train/loss=19.20]
Epoch 0: | | 372/? [02:13<00:00, 2.78it/s, train/loss=19.20]
Epoch 0: | | 372/? [02:13<00:00, 2.78it/s, train/loss=21.30]
Epoch 0: | | 373/? [02:13<00:00, 2.79it/s, train/loss=21.30]
Epoch 0: | | 373/? [02:13<00:00, 2.79it/s, train/loss=56.40]
Epoch 0: | | 374/? [02:14<00:00, 2.79it/s, train/loss=56.40]
Epoch 0: | | 374/? [02:14<00:00, 2.79it/s, train/loss=7.560]
Epoch 0: | | 375/? [02:14<00:00, 2.79it/s, train/loss=7.560]
Epoch 0: | | 375/? [02:14<00:00, 2.79it/s, train/loss=25.50]
Epoch 0: | | 376/? [02:14<00:00, 2.79it/s, train/loss=25.50]
Epoch 0: | | 376/? [02:14<00:00, 2.79it/s, train/loss=12.80]
Epoch 0: | | 377/? [02:15<00:00, 2.79it/s, train/loss=12.80]
Epoch 0: | | 377/? [02:15<00:00, 2.79it/s, train/loss=71.40]
Epoch 0: | | 378/? [02:15<00:00, 2.79it/s, train/loss=71.40]
Epoch 0: | | 378/? [02:15<00:00, 2.79it/s, train/loss=49.30]
Epoch 0: | | 379/? [02:15<00:00, 2.79it/s, train/loss=49.30]
Epoch 0: | | 379/? [02:15<00:00, 2.79it/s, train/loss=35.50]
Epoch 0: | | 380/? [02:16<00:00, 2.79it/s, train/loss=35.50]
Epoch 0: | | 380/? [02:16<00:00, 2.79it/s, train/loss=8.540]
Epoch 0: | | 381/? [02:16<00:00, 2.79it/s, train/loss=8.540]
Epoch 0: | | 381/? [02:16<00:00, 2.79it/s, train/loss=16.60]
Epoch 0: | | 382/? [02:16<00:00, 2.79it/s, train/loss=16.60]
Epoch 0: | | 382/? [02:16<00:00, 2.79it/s, train/loss=19.50]
Epoch 0: | | 383/? [02:17<00:00, 2.79it/s, train/loss=19.50]
Epoch 0: | | 383/? [02:17<00:00, 2.79it/s, train/loss=10.60]
Epoch 0: | | 384/? [02:17<00:00, 2.79it/s, train/loss=10.60]
Epoch 0: | | 384/? [02:17<00:00, 2.79it/s, train/loss=25.00]
Epoch 0: | | 385/? [02:17<00:00, 2.79it/s, train/loss=25.00]
Epoch 0: | | 385/? [02:17<00:00, 2.79it/s, train/loss=31.50]
Epoch 0: | | 386/? [02:18<00:00, 2.79it/s, train/loss=31.50]
Epoch 0: | | 386/? [02:18<00:00, 2.79it/s, train/loss=34.80]
Epoch 0: | | 387/? [02:18<00:00, 2.79it/s, train/loss=34.80]
Epoch 0: | | 387/? [02:18<00:00, 2.79it/s, train/loss=9.860]
Epoch 0: | | 388/? [02:18<00:00, 2.80it/s, train/loss=9.860]
Epoch 0: | | 388/? [02:18<00:00, 2.80it/s, train/loss=19.40]
Epoch 0: | | 389/? [02:19<00:00, 2.80it/s, train/loss=19.40]
Epoch 0: | | 389/? [02:19<00:00, 2.80it/s, train/loss=23.50]
Epoch 0: | | 390/? [02:19<00:00, 2.80it/s, train/loss=23.50]
Epoch 0: | | 390/? [02:19<00:00, 2.80it/s, train/loss=10.40]
Epoch 0: | | 391/? [02:19<00:00, 2.80it/s, train/loss=10.40]
Epoch 0: | | 391/? [02:19<00:00, 2.80it/s, train/loss=13.90]
Epoch 0: | | 392/? [02:20<00:00, 2.80it/s, train/loss=13.90]
Epoch 0: | | 392/? [02:20<00:00, 2.80it/s, train/loss=13.50]
Epoch 0: | | 393/? [02:20<00:00, 2.80it/s, train/loss=13.50]
Epoch 0: | | 393/? [02:20<00:00, 2.80it/s, train/loss=27.80]
Epoch 0: | | 394/? [02:20<00:00, 2.80it/s, train/loss=27.80]
Epoch 0: | | 394/? [02:20<00:00, 2.80it/s, train/loss=15.40]
Epoch 0: | | 395/? [02:21<00:00, 2.80it/s, train/loss=15.40]
Epoch 0: | | 395/? [02:21<00:00, 2.80it/s, train/loss=36.60]
Epoch 0: | | 396/? [02:21<00:00, 2.80it/s, train/loss=36.60]
Epoch 0: | | 396/? [02:21<00:00, 2.80it/s, train/loss=37.40]
Epoch 0: | | 397/? [02:21<00:00, 2.80it/s, train/loss=37.40]
Epoch 0: | | 397/? [02:21<00:00, 2.80it/s, train/loss=25.60]
Epoch 0: | | 398/? [02:22<00:00, 2.80it/s, train/loss=25.60]
Epoch 0: | | 398/? [02:22<00:00, 2.80it/s, train/loss=30.60]
Epoch 0: | | 399/? [02:22<00:00, 2.80it/s, train/loss=30.60]
Epoch 0: | | 399/? [02:22<00:00, 2.80it/s, train/loss=33.70]
Epoch 0: | | 400/? [02:22<00:00, 2.80it/s, train/loss=33.70]
Epoch 0: | | 400/? [02:22<00:00, 2.80it/s, train/loss=13.20]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:03, 11.05it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:03, 10.99it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:03, 10.82it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:03, 10.85it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:03, 11.03it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:03, 11.14it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:02, 11.13it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:02, 11.05it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:02, 11.07it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:02, 11.11it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:02, 11.18it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:02, 11.28it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:02, 11.35it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 11.39it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 11.06it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 11.03it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:02, 11.08it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:01<00:01, 11.13it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:01<00:01, 11.17it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:01<00:01, 11.22it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:01<00:01, 11.26it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:01<00:01, 11.30it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:02<00:01, 11.33it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 11.36it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 11.39it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 11.41it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 11.45it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:02<00:01, 11.48it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:02<00:00, 11.48it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:02<00:00, 11.49it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:02<00:00, 11.52it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:02<00:00, 11.54it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:02<00:00, 11.56it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:02<00:00, 11.58it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 11.57it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:03<00:00, 11.58it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:03<00:00, 11.48it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:03<00:00, 11.36it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:03<00:00, 11.31it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.32it/s][A
[A
Epoch 0: | | 400/? [02:29<00:00, 2.67it/s, train/loss=13.20]
Epoch 0: | | 401/? [02:30<00:00, 2.66it/s, train/loss=13.20]
Epoch 0: | | 401/? [02:30<00:00, 2.66it/s, train/loss=30.60]
Epoch 0: | | 402/? [02:31<00:00, 2.66it/s, train/loss=30.60]
Epoch 0: | | 402/? [02:31<00:00, 2.66it/s, train/loss=26.40]
Epoch 0: | | 403/? [02:31<00:00, 2.66it/s, train/loss=26.40]
Epoch 0: | | 403/? [02:31<00:00, 2.66it/s, train/loss=13.50]
Epoch 0: | | 404/? [02:31<00:00, 2.66it/s, train/loss=13.50]
Epoch 0: | | 404/? [02:31<00:00, 2.66it/s, train/loss=16.60]
Epoch 0: | | 405/? [02:32<00:00, 2.66it/s, train/loss=16.60]
Epoch 0: | | 405/? [02:32<00:00, 2.66it/s, train/loss=27.20]
Epoch 0: | | 406/? [02:32<00:00, 2.66it/s, train/loss=27.20]
Epoch 0: | | 406/? [02:32<00:00, 2.66it/s, train/loss=18.70]
Epoch 0: | | 407/? [02:32<00:00, 2.66it/s, train/loss=18.70]
Epoch 0: | | 407/? [02:32<00:00, 2.66it/s, train/loss=27.70]
Epoch 0: | | 408/? [02:33<00:00, 2.66it/s, train/loss=27.70]
Epoch 0: | | 408/? [02:33<00:00, 2.66it/s, train/loss=30.20]
Epoch 0: | | 409/? [02:33<00:00, 2.66it/s, train/loss=30.20]
Epoch 0: | | 409/? [02:33<00:00, 2.66it/s, train/loss=51.20]
Epoch 0: | | 410/? [02:33<00:00, 2.66it/s, train/loss=51.20]
Epoch 0: | | 410/? [02:33<00:00, 2.66it/s, train/loss=16.80]
Epoch 0: | | 411/? [02:34<00:00, 2.67it/s, train/loss=16.80]
Epoch 0: | | 411/? [02:34<00:00, 2.67it/s, train/loss=18.90]
Epoch 0: | | 412/? [02:34<00:00, 2.67it/s, train/loss=18.90]
Epoch 0: | | 412/? [02:34<00:00, 2.67it/s, train/loss=58.30]
Epoch 0: | | 413/? [02:34<00:00, 2.67it/s, train/loss=58.30]
Epoch 0: | | 413/? [02:34<00:00, 2.67it/s, train/loss=42.70]
Epoch 0: | | 414/? [02:35<00:00, 2.67it/s, train/loss=42.70]
Epoch 0: | | 414/? [02:35<00:00, 2.67it/s, train/loss=64.70]
Epoch 0: | | 415/? [02:35<00:00, 2.67it/s, train/loss=64.70]
Epoch 0: | | 415/? [02:35<00:00, 2.67it/s, train/loss=19.50]
Epoch 0: | | 416/? [02:35<00:00, 2.67it/s, train/loss=19.50]
Epoch 0: | | 416/? [02:35<00:00, 2.67it/s, train/loss=24.70]
Epoch 0: | | 417/? [02:36<00:00, 2.67it/s, train/loss=24.70]
Epoch 0: | | 417/? [02:36<00:00, 2.67it/s, train/loss=18.20]
Epoch 0: | | 418/? [02:36<00:00, 2.67it/s, train/loss=18.20]
Epoch 0: | | 418/? [02:36<00:00, 2.67it/s, train/loss=17.60]
Epoch 0: | | 419/? [02:36<00:00, 2.67it/s, train/loss=17.60]
Epoch 0: | | 419/? [02:36<00:00, 2.67it/s, train/loss=17.90]
Epoch 0: | | 420/? [02:37<00:00, 2.67it/s, train/loss=17.90]
Epoch 0: | | 420/? [02:37<00:00, 2.67it/s, train/loss=18.60]
Epoch 0: | | 421/? [02:37<00:00, 2.67it/s, train/loss=18.60]
Epoch 0: | | 421/? [02:37<00:00, 2.67it/s, train/loss=24.80]
Epoch 0: | | 422/? [02:37<00:00, 2.67it/s, train/loss=24.80]
Epoch 0: | | 422/? [02:37<00:00, 2.67it/s, train/loss=16.30]
Epoch 0: | | 423/? [02:38<00:00, 2.67it/s, train/loss=16.30]
Epoch 0: | | 423/? [02:38<00:00, 2.67it/s, train/loss=30.70]
Epoch 0: | | 424/? [02:38<00:00, 2.67it/s, train/loss=30.70]
Epoch 0: | | 424/? [02:38<00:00, 2.67it/s, train/loss=20.60]
Epoch 0: | | 425/? [02:38<00:00, 2.67it/s, train/loss=20.60]
Epoch 0: | | 425/? [02:38<00:00, 2.67it/s, train/loss=52.60]
Epoch 0: | | 426/? [02:39<00:00, 2.68it/s, train/loss=52.60]
Epoch 0: | | 426/? [02:39<00:00, 2.68it/s, train/loss=13.80]
Epoch 0: | | 427/? [02:39<00:00, 2.68it/s, train/loss=13.80]
Epoch 0: | | 427/? [02:39<00:00, 2.68it/s, train/loss=21.80]
Epoch 0: | | 428/? [02:39<00:00, 2.68it/s, train/loss=21.80]
Epoch 0: | | 428/? [02:39<00:00, 2.68it/s, train/loss=15.70]
Epoch 0: | | 429/? [02:40<00:00, 2.68it/s, train/loss=15.70]
Epoch 0: | | 429/? [02:40<00:00, 2.68it/s, train/loss=33.00]
Epoch 0: | | 430/? [02:40<00:00, 2.68it/s, train/loss=33.00]
Epoch 0: | | 430/? [02:40<00:00, 2.68it/s, train/loss=13.50]
Epoch 0: | | 431/? [02:40<00:00, 2.68it/s, train/loss=13.50]
Epoch 0: | | 431/? [02:40<00:00, 2.68it/s, train/loss=12.40]
Epoch 0: | | 432/? [02:41<00:00, 2.68it/s, train/loss=12.40]
Epoch 0: | | 432/? [02:41<00:00, 2.68it/s, train/loss=30.90]
Epoch 0: | | 433/? [02:41<00:00, 2.68it/s, train/loss=30.90]
Epoch 0: | | 433/? [02:41<00:00, 2.68it/s, train/loss=26.90]
Epoch 0: | | 434/? [02:41<00:00, 2.68it/s, train/loss=26.90]
Epoch 0: | | 434/? [02:41<00:00, 2.68it/s, train/loss=17.60]
Epoch 0: | | 435/? [02:42<00:00, 2.68it/s, train/loss=17.60]
Epoch 0: | | 435/? [02:42<00:00, 2.68it/s, train/loss=16.60]
Epoch 0: | | 436/? [02:42<00:00, 2.68it/s, train/loss=16.60]
Epoch 0: | | 436/? [02:42<00:00, 2.68it/s, train/loss=14.60]
Epoch 0: | | 437/? [02:42<00:00, 2.68it/s, train/loss=14.60]
Epoch 0: | | 437/? [02:42<00:00, 2.68it/s, train/loss=25.70]
Epoch 0: | | 438/? [02:43<00:00, 2.68it/s, train/loss=25.70]
Epoch 0: | | 438/? [02:43<00:00, 2.68it/s, train/loss=9.540]
Epoch 0: | | 439/? [02:43<00:00, 2.68it/s, train/loss=9.540]
Epoch 0: | | 439/? [02:43<00:00, 2.68it/s, train/loss=8.600]
Epoch 0: | | 440/? [02:43<00:00, 2.69it/s, train/loss=8.600]
Epoch 0: | | 440/? [02:43<00:00, 2.69it/s, train/loss=35.50]
Epoch 0: | | 441/? [02:44<00:00, 2.69it/s, train/loss=35.50]
Epoch 0: | | 441/? [02:44<00:00, 2.69it/s, train/loss=35.10]
Epoch 0: | | 442/? [02:44<00:00, 2.69it/s, train/loss=35.10]
Epoch 0: | | 442/? [02:44<00:00, 2.69it/s, train/loss=17.60]
Epoch 0: | | 443/? [02:44<00:00, 2.69it/s, train/loss=17.60]
Epoch 0: | | 443/? [02:44<00:00, 2.69it/s, train/loss=23.50]
Epoch 0: | | 444/? [02:45<00:00, 2.69it/s, train/loss=23.50]
Epoch 0: | | 444/? [02:45<00:00, 2.69it/s, train/loss=7.570]
Epoch 0: | | 445/? [02:45<00:00, 2.69it/s, train/loss=7.570]
Epoch 0: | | 445/? [02:45<00:00, 2.69it/s, train/loss=40.90]
Epoch 0: | | 446/? [02:45<00:00, 2.69it/s, train/loss=40.90]
Epoch 0: | | 446/? [02:45<00:00, 2.69it/s, train/loss=12.80]
Epoch 0: | | 447/? [02:46<00:00, 2.69it/s, train/loss=12.80]
Epoch 0: | | 447/? [02:46<00:00, 2.69it/s, train/loss=17.70]
Epoch 0: | | 448/? [02:46<00:00, 2.69it/s, train/loss=17.70]
Epoch 0: | | 448/? [02:46<00:00, 2.69it/s, train/loss=6.630]
Epoch 0: | | 449/? [02:46<00:00, 2.69it/s, train/loss=6.630]
Epoch 0: | | 449/? [02:46<00:00, 2.69it/s, train/loss=36.00]
Epoch 0: | | 450/? [02:47<00:00, 2.69it/s, train/loss=36.00]
Epoch 0: | | 450/? [02:47<00:00, 2.69it/s, train/loss=18.80]
Epoch 0: | | 451/? [02:47<00:00, 2.69it/s, train/loss=18.80]
Epoch 0: | | 451/? [02:47<00:00, 2.69it/s, train/loss=14.00]
Epoch 0: | | 452/? [02:47<00:00, 2.69it/s, train/loss=14.00]
Epoch 0: | | 452/? [02:47<00:00, 2.69it/s, train/loss=83.80]
Epoch 0: | | 453/? [02:48<00:00, 2.69it/s, train/loss=83.80]
Epoch 0: | | 453/? [02:48<00:00, 2.69it/s, train/loss=43.40]
Epoch 0: | | 454/? [02:48<00:00, 2.70it/s, train/loss=43.40]
Epoch 0: | | 454/? [02:48<00:00, 2.70it/s, train/loss=20.80]
Epoch 0: | | 455/? [02:48<00:00, 2.70it/s, train/loss=20.80]
Epoch 0: | | 455/? [02:48<00:00, 2.70it/s, train/loss=9.980]
Epoch 0: | | 456/? [02:49<00:00, 2.70it/s, train/loss=9.980]
Epoch 0: | | 456/? [02:49<00:00, 2.70it/s, train/loss=17.70]
Epoch 0: | | 457/? [02:49<00:00, 2.70it/s, train/loss=17.70]
Epoch 0: | | 457/? [02:49<00:00, 2.70it/s, train/loss=30.30]
Epoch 0: | | 458/? [02:49<00:00, 2.70it/s, train/loss=30.30]
Epoch 0: | | 458/? [02:49<00:00, 2.70it/s, train/loss=46.60]
Epoch 0: | | 459/? [02:50<00:00, 2.70it/s, train/loss=46.60]
Epoch 0: | | 459/? [02:50<00:00, 2.70it/s, train/loss=34.10]
Epoch 0: | | 460/? [02:50<00:00, 2.70it/s, train/loss=34.10]
Epoch 0: | | 460/? [02:50<00:00, 2.70it/s, train/loss=17.40]
Epoch 0: | | 461/? [02:50<00:00, 2.70it/s, train/loss=17.40]
Epoch 0: | | 461/? [02:50<00:00, 2.70it/s, train/loss=47.60]
Epoch 0: | | 462/? [02:51<00:00, 2.70it/s, train/loss=47.60]
Epoch 0: | | 462/? [02:51<00:00, 2.70it/s, train/loss=28.80]
Epoch 0: | | 463/? [02:51<00:00, 2.70it/s, train/loss=28.80]
Epoch 0: | | 463/? [02:51<00:00, 2.70it/s, train/loss=17.10]
Epoch 0: | | 464/? [02:51<00:00, 2.70it/s, train/loss=17.10]
Epoch 0: | | 464/? [02:51<00:00, 2.70it/s, train/loss=9.830]
Epoch 0: | | 465/? [02:52<00:00, 2.70it/s, train/loss=9.830]
Epoch 0: | | 465/? [02:52<00:00, 2.70it/s, train/loss=44.80]
Epoch 0: | | 466/? [02:52<00:00, 2.70it/s, train/loss=44.80]
Epoch 0: | | 466/? [02:52<00:00, 2.70it/s, train/loss=7.480]
Epoch 0: | | 467/? [02:52<00:00, 2.70it/s, train/loss=7.480]
Epoch 0: | | 467/? [02:52<00:00, 2.70it/s, train/loss=9.460]
Epoch 0: | | 468/? [02:53<00:00, 2.70it/s, train/loss=9.460]
Epoch 0: | | 468/? [02:53<00:00, 2.70it/s, train/loss=12.20]
Epoch 0: | | 469/? [02:53<00:00, 2.70it/s, train/loss=12.20]
Epoch 0: | | 469/? [02:53<00:00, 2.70it/s, train/loss=51.10]
Epoch 0: | | 470/? [02:53<00:00, 2.70it/s, train/loss=51.10]
Epoch 0: | | 470/? [02:53<00:00, 2.70it/s, train/loss=27.10]
Epoch 0: | | 471/? [02:54<00:00, 2.70it/s, train/loss=27.10]
Epoch 0: | | 471/? [02:54<00:00, 2.70it/s, train/loss=44.90]
Epoch 0: | | 472/? [02:54<00:00, 2.70it/s, train/loss=44.90]
Epoch 0: | | 472/? [02:54<00:00, 2.70it/s, train/loss=16.30]
Epoch 0: | | 473/? [02:54<00:00, 2.70it/s, train/loss=16.30]
Epoch 0: | | 473/? [02:54<00:00, 2.70it/s, train/loss=41.40]
Epoch 0: | | 474/? [02:55<00:00, 2.70it/s, train/loss=41.40]
Epoch 0: | | 474/? [02:55<00:00, 2.70it/s, train/loss=14.00]
Epoch 0: | | 475/? [02:55<00:00, 2.71it/s, train/loss=14.00]
Epoch 0: | | 475/? [02:55<00:00, 2.71it/s, train/loss=8.040]
Epoch 0: | | 476/? [02:55<00:00, 2.71it/s, train/loss=8.040]
Epoch 0: | | 476/? [02:55<00:00, 2.71it/s, train/loss=29.40]
Epoch 0: | | 477/? [02:56<00:00, 2.71it/s, train/loss=29.40]
Epoch 0: | | 477/? [02:56<00:00, 2.71it/s, train/loss=49.00]
Epoch 0: | | 478/? [02:56<00:00, 2.71it/s, train/loss=49.00]
Epoch 0: | | 478/? [02:56<00:00, 2.71it/s, train/loss=18.30]
Epoch 0: | | 479/? [02:56<00:00, 2.71it/s, train/loss=18.30]
Epoch 0: | | 479/? [02:56<00:00, 2.71it/s, train/loss=10.50]
Epoch 0: | | 480/? [02:57<00:00, 2.71it/s, train/loss=10.50]
Epoch 0: | | 480/? [02:57<00:00, 2.71it/s, train/loss=29.50]
Epoch 0: | | 481/? [02:57<00:00, 2.71it/s, train/loss=29.50]
Epoch 0: | | 481/? [02:57<00:00, 2.71it/s, train/loss=14.10]
Epoch 0: | | 482/? [02:57<00:00, 2.71it/s, train/loss=14.10]
Epoch 0: | | 482/? [02:57<00:00, 2.71it/s, train/loss=24.80]
Epoch 0: | | 483/? [02:58<00:00, 2.71it/s, train/loss=24.80]
Epoch 0: | | 483/? [02:58<00:00, 2.71it/s, train/loss=8.920]
Epoch 0: | | 484/? [02:58<00:00, 2.71it/s, train/loss=8.920]
Epoch 0: | | 484/? [02:58<00:00, 2.71it/s, train/loss=26.50]
Epoch 0: | | 485/? [02:58<00:00, 2.71it/s, train/loss=26.50]
Epoch 0: | | 485/? [02:58<00:00, 2.71it/s, train/loss=29.00]
Epoch 0: | | 486/? [02:59<00:00, 2.71it/s, train/loss=29.00]
Epoch 0: | | 486/? [02:59<00:00, 2.71it/s, train/loss=27.30]
Epoch 0: | | 487/? [02:59<00:00, 2.71it/s, train/loss=27.30]
Epoch 0: | | 487/? [02:59<00:00, 2.71it/s, train/loss=14.50]
Epoch 0: | | 488/? [02:59<00:00, 2.71it/s, train/loss=14.50]
Epoch 0: | | 488/? [02:59<00:00, 2.71it/s, train/loss=15.10]
Epoch 0: | | 489/? [03:00<00:00, 2.71it/s, train/loss=15.10]
Epoch 0: | | 489/? [03:00<00:00, 2.71it/s, train/loss=42.50]
Epoch 0: | | 490/? [03:00<00:00, 2.71it/s, train/loss=42.50]
Epoch 0: | | 490/? [03:00<00:00, 2.71it/s, train/loss=16.70]
Epoch 0: | | 491/? [03:00<00:00, 2.72it/s, train/loss=16.70]
Epoch 0: | | 491/? [03:00<00:00, 2.72it/s, train/loss=15.50]
Epoch 0: | | 492/? [03:01<00:00, 2.72it/s, train/loss=15.50]
Epoch 0: | | 492/? [03:01<00:00, 2.72it/s, train/loss=14.40]
Epoch 0: | | 493/? [03:01<00:00, 2.72it/s, train/loss=14.40]
Epoch 0: | | 493/? [03:01<00:00, 2.72it/s, train/loss=44.80]
Epoch 0: | | 494/? [03:01<00:00, 2.72it/s, train/loss=44.80]
Epoch 0: | | 494/? [03:01<00:00, 2.72it/s, train/loss=22.20]
Epoch 0: | | 495/? [03:02<00:00, 2.72it/s, train/loss=22.20]
Epoch 0: | | 495/? [03:02<00:00, 2.72it/s, train/loss=17.40]
Epoch 0: | | 496/? [03:02<00:00, 2.72it/s, train/loss=17.40]
Epoch 0: | | 496/? [03:02<00:00, 2.72it/s, train/loss=25.70]
Epoch 0: | | 497/? [03:02<00:00, 2.72it/s, train/loss=25.70]
Epoch 0: | | 497/? [03:02<00:00, 2.72it/s, train/loss=29.50]
Epoch 0: | | 498/? [03:03<00:00, 2.72it/s, train/loss=29.50]
Epoch 0: | | 498/? [03:03<00:00, 2.72it/s, train/loss=37.70]
Epoch 0: | | 499/? [03:03<00:00, 2.72it/s, train/loss=37.70]
Epoch 0: | | 499/? [03:03<00:00, 2.72it/s, train/loss=7.640]
Epoch 0: | | 500/? [03:03<00:00, 2.72it/s, train/loss=7.640]
Epoch 0: | | 500/? [03:03<00:00, 2.72it/s, train/loss=14.00]
Epoch 0: | | 501/? [03:04<00:00, 2.72it/s, train/loss=14.00]
Epoch 0: | | 501/? [03:04<00:00, 2.72it/s, train/loss=40.30]
Epoch 0: | | 502/? [03:04<00:00, 2.72it/s, train/loss=40.30]
Epoch 0: | | 502/? [03:04<00:00, 2.72it/s, train/loss=32.80]
Epoch 0: | | 503/? [03:04<00:00, 2.72it/s, train/loss=32.80]
Epoch 0: | | 503/? [03:04<00:00, 2.72it/s, train/loss=20.80]
Epoch 0: | | 504/? [03:05<00:00, 2.72it/s, train/loss=20.80]
Epoch 0: | | 504/? [03:05<00:00, 2.72it/s, train/loss=39.40]
Epoch 0: | | 505/? [03:05<00:00, 2.72it/s, train/loss=39.40]
Epoch 0: | | 505/? [03:05<00:00, 2.72it/s, train/loss=22.80]
Epoch 0: | | 506/? [03:05<00:00, 2.72it/s, train/loss=22.80]
Epoch 0: | | 506/? [03:05<00:00, 2.72it/s, train/loss=22.80]
Epoch 0: | | 507/? [03:06<00:00, 2.72it/s, train/loss=22.80]
Epoch 0: | | 507/? [03:06<00:00, 2.72it/s, train/loss=21.10]
Epoch 0: | | 508/? [03:06<00:00, 2.72it/s, train/loss=21.10]
Epoch 0: | | 508/? [03:06<00:00, 2.72it/s, train/loss=8.100]
Epoch 0: | | 509/? [03:06<00:00, 2.73it/s, train/loss=8.100]
Epoch 0: | | 509/? [03:06<00:00, 2.73it/s, train/loss=21.00]
Epoch 0: | | 510/? [03:07<00:00, 2.73it/s, train/loss=21.00]
Epoch 0: | | 510/? [03:07<00:00, 2.73it/s, train/loss=10.50]
Epoch 0: | | 511/? [03:07<00:00, 2.73it/s, train/loss=10.50]
Epoch 0: | | 511/? [03:07<00:00, 2.73it/s, train/loss=32.80]
Epoch 0: | | 512/? [03:07<00:00, 2.73it/s, train/loss=32.80]
Epoch 0: | | 512/? [03:07<00:00, 2.73it/s, train/loss=10.10]
Epoch 0: | | 513/? [03:08<00:00, 2.73it/s, train/loss=10.10]
Epoch 0: | | 513/? [03:08<00:00, 2.73it/s, train/loss=34.70]
Epoch 0: | | 514/? [03:08<00:00, 2.73it/s, train/loss=34.70]
Epoch 0: | | 514/? [03:08<00:00, 2.73it/s, train/loss=12.70]
Epoch 0: | | 515/? [03:08<00:00, 2.73it/s, train/loss=12.70]
Epoch 0: | | 515/? [03:08<00:00, 2.73it/s, train/loss=8.430]
Epoch 0: | | 516/? [03:09<00:00, 2.73it/s, train/loss=8.430]
Epoch 0: | | 516/? [03:09<00:00, 2.73it/s, train/loss=16.00]
Epoch 0: | | 517/? [03:09<00:00, 2.73it/s, train/loss=16.00]
Epoch 0: | | 517/? [03:09<00:00, 2.73it/s, train/loss=25.90]
Epoch 0: | | 518/? [03:09<00:00, 2.73it/s, train/loss=25.90]
Epoch 0: | | 518/? [03:09<00:00, 2.73it/s, train/loss=13.20]
Epoch 0: | | 519/? [03:10<00:00, 2.73it/s, train/loss=13.20]
Epoch 0: | | 519/? [03:10<00:00, 2.73it/s, train/loss=30.10]
Epoch 0: | | 520/? [03:10<00:00, 2.73it/s, train/loss=30.10]
Epoch 0: | | 520/? [03:10<00:00, 2.73it/s, train/loss=26.40]
Epoch 0: | | 521/? [03:10<00:00, 2.73it/s, train/loss=26.40]
Epoch 0: | | 521/? [03:10<00:00, 2.73it/s, train/loss=28.50]
Epoch 0: | | 522/? [03:11<00:00, 2.73it/s, train/loss=28.50]
Epoch 0: | | 522/? [03:11<00:00, 2.73it/s, train/loss=29.50]
Epoch 0: | | 523/? [03:11<00:00, 2.73it/s, train/loss=29.50]
Epoch 0: | | 523/? [03:11<00:00, 2.73it/s, train/loss=23.70]
Epoch 0: | | 524/? [03:11<00:00, 2.73it/s, train/loss=23.70]
Epoch 0: | | 524/? [03:11<00:00, 2.73it/s, train/loss=14.50]
Epoch 0: | | 525/? [03:12<00:00, 2.73it/s, train/loss=14.50]
Epoch 0: | | 525/? [03:12<00:00, 2.73it/s, train/loss=25.00]
Epoch 0: | | 526/? [03:12<00:00, 2.73it/s, train/loss=25.00]
Epoch 0: | | 526/? [03:12<00:00, 2.73it/s, train/loss=35.40]
Epoch 0: | | 527/? [03:12<00:00, 2.73it/s, train/loss=35.40]
Epoch 0: | | 527/? [03:12<00:00, 2.73it/s, train/loss=29.80]
Epoch 0: | | 528/? [03:13<00:00, 2.73it/s, train/loss=29.80]
Epoch 0: | | 528/? [03:13<00:00, 2.73it/s, train/loss=24.20]
Epoch 0: | | 529/? [03:13<00:00, 2.73it/s, train/loss=24.20]
Epoch 0: | | 529/? [03:13<00:00, 2.73it/s, train/loss=28.20]
Epoch 0: | | 530/? [03:13<00:00, 2.73it/s, train/loss=28.20]
Epoch 0: | | 530/? [03:13<00:00, 2.73it/s, train/loss=19.10]
Epoch 0: | | 531/? [03:14<00:00, 2.74it/s, train/loss=19.10]
Epoch 0: | | 531/? [03:14<00:00, 2.74it/s, train/loss=20.40]
Epoch 0: | | 532/? [03:14<00:00, 2.74it/s, train/loss=20.40]
Epoch 0: | | 532/? [03:14<00:00, 2.74it/s, train/loss=30.20]
Epoch 0: | | 533/? [03:14<00:00, 2.74it/s, train/loss=30.20]
Epoch 0: | | 533/? [03:14<00:00, 2.74it/s, train/loss=19.40]
Epoch 0: | | 534/? [03:15<00:00, 2.74it/s, train/loss=19.40]
Epoch 0: | | 534/? [03:15<00:00, 2.74it/s, train/loss=21.10]
Epoch 0: | | 535/? [03:15<00:00, 2.74it/s, train/loss=21.10]
Epoch 0: | | 535/? [03:15<00:00, 2.74it/s, train/loss=15.40]
Epoch 0: | | 536/? [03:15<00:00, 2.74it/s, train/loss=15.40]
Epoch 0: | | 536/? [03:15<00:00, 2.74it/s, train/loss=27.50]
Epoch 0: | | 537/? [03:16<00:00, 2.74it/s, train/loss=27.50]
Epoch 0: | | 537/? [03:16<00:00, 2.74it/s, train/loss=20.20]
Epoch 0: | | 538/? [03:16<00:00, 2.74it/s, train/loss=20.20]
Epoch 0: | | 538/? [03:16<00:00, 2.74it/s, train/loss=9.040]
Epoch 0: | | 539/? [03:16<00:00, 2.74it/s, train/loss=9.040]
Epoch 0: | | 539/? [03:16<00:00, 2.74it/s, train/loss=19.20]
Epoch 0: | | 540/? [03:17<00:00, 2.74it/s, train/loss=19.20]
Epoch 0: | | 540/? [03:17<00:00, 2.74it/s, train/loss=23.50]
Epoch 0: | | 541/? [03:17<00:00, 2.74it/s, train/loss=23.50]
Epoch 0: | | 541/? [03:17<00:00, 2.74it/s, train/loss=18.80]
Epoch 0: | | 542/? [03:17<00:00, 2.74it/s, train/loss=18.80]
Epoch 0: | | 542/? [03:17<00:00, 2.74it/s, train/loss=12.30]
Epoch 0: | | 543/? [03:18<00:00, 2.74it/s, train/loss=12.30]
Epoch 0: | | 543/? [03:18<00:00, 2.74it/s, train/loss=31.00]
Epoch 0: | | 544/? [03:18<00:00, 2.74it/s, train/loss=31.00]
Epoch 0: | | 544/? [03:18<00:00, 2.74it/s, train/loss=12.90]
Epoch 0: | | 545/? [03:18<00:00, 2.74it/s, train/loss=12.90]
Epoch 0: | | 545/? [03:18<00:00, 2.74it/s, train/loss=16.30]
Epoch 0: | | 546/? [03:19<00:00, 2.74it/s, train/loss=16.30]
Epoch 0: | | 546/? [03:19<00:00, 2.74it/s, train/loss=18.80]
Epoch 0: | | 547/? [03:19<00:00, 2.74it/s, train/loss=18.80]
Epoch 0: | | 547/? [03:19<00:00, 2.74it/s, train/loss=19.40]
Epoch 0: | | 548/? [03:19<00:00, 2.74it/s, train/loss=19.40]
Epoch 0: | | 548/? [03:19<00:00, 2.74it/s, train/loss=21.10]
Epoch 0: | | 549/? [03:19<00:00, 2.75it/s, train/loss=21.10]
Epoch 0: | | 549/? [03:20<00:00, 2.74it/s, train/loss=28.20]
Epoch 0: | | 550/? [03:20<00:00, 2.75it/s, train/loss=28.20]
Epoch 0: | | 550/? [03:20<00:00, 2.75it/s, train/loss=28.10]
Epoch 0: | | 551/? [03:20<00:00, 2.75it/s, train/loss=28.10]
Epoch 0: | | 551/? [03:20<00:00, 2.75it/s, train/loss=48.30]
Epoch 0: | | 552/? [03:20<00:00, 2.75it/s, train/loss=48.30]
Epoch 0: | | 552/? [03:20<00:00, 2.75it/s, train/loss=24.20]
Epoch 0: | | 553/? [03:21<00:00, 2.75it/s, train/loss=24.20]
Epoch 0: | | 553/? [03:21<00:00, 2.75it/s, train/loss=31.10]
Epoch 0: | | 554/? [03:21<00:00, 2.75it/s, train/loss=31.10]
Epoch 0: | | 554/? [03:21<00:00, 2.75it/s, train/loss=24.40]
Epoch 0: | | 555/? [03:21<00:00, 2.75it/s, train/loss=24.40]
Epoch 0: | | 555/? [03:21<00:00, 2.75it/s, train/loss=19.50]
Epoch 0: | | 556/? [03:22<00:00, 2.75it/s, train/loss=19.50]
Epoch 0: | | 556/? [03:22<00:00, 2.75it/s, train/loss=25.60]
Epoch 0: | | 557/? [03:22<00:00, 2.75it/s, train/loss=25.60]
Epoch 0: | | 557/? [03:22<00:00, 2.75it/s, train/loss=23.50]
Epoch 0: | | 558/? [03:22<00:00, 2.75it/s, train/loss=23.50]
Epoch 0: | | 558/? [03:22<00:00, 2.75it/s, train/loss=19.50]
Epoch 0: | | 559/? [03:23<00:00, 2.75it/s, train/loss=19.50]
Epoch 0: | | 559/? [03:23<00:00, 2.75it/s, train/loss=19.30]
Epoch 0: | | 560/? [03:23<00:00, 2.75it/s, train/loss=19.30]
Epoch 0: | | 560/? [03:23<00:00, 2.75it/s, train/loss=10.50]
Epoch 0: | | 561/? [03:23<00:00, 2.75it/s, train/loss=10.50]
Epoch 0: | | 561/? [03:23<00:00, 2.75it/s, train/loss=27.50]
Epoch 0: | | 562/? [03:24<00:00, 2.75it/s, train/loss=27.50]
Epoch 0: | | 562/? [03:24<00:00, 2.75it/s, train/loss=27.70]
Epoch 0: | | 563/? [03:24<00:00, 2.75it/s, train/loss=27.70]
Epoch 0: | | 563/? [03:24<00:00, 2.75it/s, train/loss=17.00]
Epoch 0: | | 564/? [03:24<00:00, 2.75it/s, train/loss=17.00]
Epoch 0: | | 564/? [03:24<00:00, 2.75it/s, train/loss=13.70]
Epoch 0: | | 565/? [03:25<00:00, 2.75it/s, train/loss=13.70]
Epoch 0: | | 565/? [03:25<00:00, 2.75it/s, train/loss=25.20]
Epoch 0: | | 566/? [03:25<00:00, 2.75it/s, train/loss=25.20]
Epoch 0: | | 566/? [03:25<00:00, 2.75it/s, train/loss=20.40]
Epoch 0: | | 567/? [03:25<00:00, 2.75it/s, train/loss=20.40]
Epoch 0: | | 567/? [03:25<00:00, 2.75it/s, train/loss=22.20]
Epoch 0: | | 568/? [03:26<00:00, 2.75it/s, train/loss=22.20]
Epoch 0: | | 568/? [03:26<00:00, 2.75it/s, train/loss=22.10]
Epoch 0: | | 569/? [03:26<00:00, 2.75it/s, train/loss=22.10]
Epoch 0: | | 569/? [03:26<00:00, 2.75it/s, train/loss=18.20]
Epoch 0: | | 570/? [03:26<00:00, 2.75it/s, train/loss=18.20]
Epoch 0: | | 570/? [03:26<00:00, 2.75it/s, train/loss=28.90]
Epoch 0: | | 571/? [03:27<00:00, 2.76it/s, train/loss=28.90]
Epoch 0: | | 571/? [03:27<00:00, 2.75it/s, train/loss=35.40]
Epoch 0: | | 572/? [03:27<00:00, 2.76it/s, train/loss=35.40]
Epoch 0: | | 572/? [03:27<00:00, 2.76it/s, train/loss=10.30]
Epoch 0: | | 573/? [03:27<00:00, 2.76it/s, train/loss=10.30]
Epoch 0: | | 573/? [03:27<00:00, 2.76it/s, train/loss=21.20]
Epoch 0: | | 574/? [03:28<00:00, 2.76it/s, train/loss=21.20]
Epoch 0: | | 574/? [03:28<00:00, 2.76it/s, train/loss=38.30]
Epoch 0: | | 575/? [03:28<00:00, 2.76it/s, train/loss=38.30]
Epoch 0: | | 575/? [03:28<00:00, 2.76it/s, train/loss=6.780]
Epoch 0: | | 576/? [03:28<00:00, 2.76it/s, train/loss=6.780]
Epoch 0: | | 576/? [03:28<00:00, 2.76it/s, train/loss=9.820]
Epoch 0: | | 577/? [03:29<00:00, 2.76it/s, train/loss=9.820]
Epoch 0: | | 577/? [03:29<00:00, 2.76it/s, train/loss=19.20]
Epoch 0: | | 578/? [03:29<00:00, 2.76it/s, train/loss=19.20]
Epoch 0: | | 578/? [03:29<00:00, 2.76it/s, train/loss=18.50]
Epoch 0: | | 579/? [03:29<00:00, 2.76it/s, train/loss=18.50]
Epoch 0: | | 579/? [03:29<00:00, 2.76it/s, train/loss=16.60]
Epoch 0: | | 580/? [03:30<00:00, 2.76it/s, train/loss=16.60]
Epoch 0: | | 580/? [03:30<00:00, 2.76it/s, train/loss=41.70]
Epoch 0: | | 581/? [03:30<00:00, 2.76it/s, train/loss=41.70]
Epoch 0: | | 581/? [03:30<00:00, 2.76it/s, train/loss=16.80]
Epoch 0: | | 582/? [03:30<00:00, 2.76it/s, train/loss=16.80]
Epoch 0: | | 582/? [03:30<00:00, 2.76it/s, train/loss=13.50]
Epoch 0: | | 583/? [03:31<00:00, 2.76it/s, train/loss=13.50]
Epoch 0: | | 583/? [03:31<00:00, 2.76it/s, train/loss=12.60]
Epoch 0: | | 584/? [03:31<00:00, 2.76it/s, train/loss=12.60]
Epoch 0: | | 584/? [03:31<00:00, 2.76it/s, train/loss=8.210]
Epoch 0: | | 585/? [03:31<00:00, 2.76it/s, train/loss=8.210]
Epoch 0: | | 585/? [03:31<00:00, 2.76it/s, train/loss=25.00]
Epoch 0: | | 586/? [03:32<00:00, 2.76it/s, train/loss=25.00]
Epoch 0: | | 586/? [03:32<00:00, 2.76it/s, train/loss=21.70]
Epoch 0: | | 587/? [03:32<00:00, 2.76it/s, train/loss=21.70]
Epoch 0: | | 587/? [03:32<00:00, 2.76it/s, train/loss=22.60]
Epoch 0: | | 588/? [03:32<00:00, 2.76it/s, train/loss=22.60]
Epoch 0: | | 588/? [03:32<00:00, 2.76it/s, train/loss=33.70]
Epoch 0: | | 589/? [03:33<00:00, 2.76it/s, train/loss=33.70]
Epoch 0: | | 589/? [03:33<00:00, 2.76it/s, train/loss=23.50]
Epoch 0: | | 590/? [03:33<00:00, 2.76it/s, train/loss=23.50]
Epoch 0: | | 590/? [03:33<00:00, 2.76it/s, train/loss=24.20]
Epoch 0: | | 591/? [03:33<00:00, 2.76it/s, train/loss=24.20]
Epoch 0: | | 591/? [03:33<00:00, 2.76it/s, train/loss=16.40]
Epoch 0: | | 592/? [03:34<00:00, 2.76it/s, train/loss=16.40]
Epoch 0: | | 592/? [03:34<00:00, 2.76it/s, train/loss=30.10]
Epoch 0: | | 593/? [03:34<00:00, 2.76it/s, train/loss=30.10]
Epoch 0: | | 593/? [03:34<00:00, 2.76it/s, train/loss=15.80]
Epoch 0: | | 594/? [03:34<00:00, 2.76it/s, train/loss=15.80]
Epoch 0: | | 594/? [03:34<00:00, 2.76it/s, train/loss=28.50]
Epoch 0: | | 595/? [03:35<00:00, 2.76it/s, train/loss=28.50]
Epoch 0: | | 595/? [03:35<00:00, 2.76it/s, train/loss=42.00]
Epoch 0: | | 596/? [03:35<00:00, 2.76it/s, train/loss=42.00]
Epoch 0: | | 596/? [03:35<00:00, 2.76it/s, train/loss=25.40]
Epoch 0: | | 597/? [03:35<00:00, 2.77it/s, train/loss=25.40]
Epoch 0: | | 597/? [03:35<00:00, 2.77it/s, train/loss=51.90]
Epoch 0: | | 598/? [03:36<00:00, 2.77it/s, train/loss=51.90]
Epoch 0: | | 598/? [03:36<00:00, 2.77it/s, train/loss=34.00]
Epoch 0: | | 599/? [03:36<00:00, 2.77it/s, train/loss=34.00]
Epoch 0: | | 599/? [03:36<00:00, 2.77it/s, train/loss=31.20]
Epoch 0: | | 600/? [03:36<00:00, 2.77it/s, train/loss=31.20]
Epoch 0: | | 600/? [03:36<00:00, 2.77it/s, train/loss=20.80]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:03, 11.29it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:03, 11.44it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:03, 11.46it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:03, 11.58it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:03, 11.58it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:02, 11.64it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:02, 11.63it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:02, 11.72it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:02, 11.78it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:02, 11.79it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:02, 11.83it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:02, 11.78it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:02, 11.81it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 11.83it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 11.86it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 11.87it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:01, 11.83it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:01<00:01, 11.85it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:01<00:01, 11.87it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:01<00:01, 11.88it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:01<00:01, 11.90it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:01<00:01, 11.86it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:01<00:01, 11.88it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 11.88it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 11.85it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 11.85it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 11.88it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:02<00:01, 11.90it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:02<00:00, 11.92it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:02<00:00, 11.94it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:02<00:00, 11.94it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:02<00:00, 11.75it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:02<00:00, 11.73it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:02<00:00, 11.70it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:02<00:00, 11.71it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:03<00:00, 11.70it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:03<00:00, 11.70it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:03<00:00, 11.71it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:03<00:00, 11.72it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.73it/s][A
[A
Epoch 0: | | 600/? [03:43<00:00, 2.68it/s, train/loss=20.80]
Epoch 0: | | 601/? [03:44<00:00, 2.67it/s, train/loss=20.80]
Epoch 0: | | 601/? [03:44<00:00, 2.67it/s, train/loss=45.20]
Epoch 0: | | 602/? [03:45<00:00, 2.67it/s, train/loss=45.20]
Epoch 0: | | 602/? [03:45<00:00, 2.67it/s, train/loss=19.60]
Epoch 0: | | 603/? [03:45<00:00, 2.67it/s, train/loss=19.60]
Epoch 0: | | 603/? [03:45<00:00, 2.67it/s, train/loss=43.40]
Epoch 0: | | 604/? [03:45<00:00, 2.68it/s, train/loss=43.40]
Epoch 0: | | 604/? [03:45<00:00, 2.68it/s, train/loss=9.500]
Epoch 0: | | 605/? [03:46<00:00, 2.68it/s, train/loss=9.500]
Epoch 0: | | 605/? [03:46<00:00, 2.68it/s, train/loss=18.10]
Epoch 0: | | 606/? [03:46<00:00, 2.68it/s, train/loss=18.10]
Epoch 0: | | 606/? [03:46<00:00, 2.68it/s, train/loss=21.10]
Epoch 0: | | 607/? [03:46<00:00, 2.68it/s, train/loss=21.10]
Epoch 0: | | 607/? [03:46<00:00, 2.68it/s, train/loss=22.80]
Epoch 0: | | 608/? [03:47<00:00, 2.68it/s, train/loss=22.80]
Epoch 0: | | 608/? [03:47<00:00, 2.68it/s, train/loss=30.10]
Epoch 0: | | 609/? [03:47<00:00, 2.68it/s, train/loss=30.10]
Epoch 0: | | 609/? [03:47<00:00, 2.68it/s, train/loss=24.90]
Epoch 0: | | 610/? [03:47<00:00, 2.68it/s, train/loss=24.90]
Epoch 0: | | 610/? [03:47<00:00, 2.68it/s, train/loss=11.10]
Epoch 0: | | 611/? [03:48<00:00, 2.68it/s, train/loss=11.10]
Epoch 0: | | 611/? [03:48<00:00, 2.68it/s, train/loss=26.60]
Epoch 0: | | 612/? [03:48<00:00, 2.68it/s, train/loss=26.60]
Epoch 0: | | 612/? [03:48<00:00, 2.68it/s, train/loss=26.10]
Epoch 0: | | 613/? [03:48<00:00, 2.68it/s, train/loss=26.10]
Epoch 0: | | 613/? [03:48<00:00, 2.68it/s, train/loss=27.20]
Epoch 0: | | 614/? [03:49<00:00, 2.68it/s, train/loss=27.20]
Epoch 0: | | 614/? [03:49<00:00, 2.68it/s, train/loss=23.90]
Epoch 0: | | 615/? [03:49<00:00, 2.68it/s, train/loss=23.90]
Epoch 0: | | 615/? [03:49<00:00, 2.68it/s, train/loss=50.80]
Epoch 0: | | 616/? [03:49<00:00, 2.68it/s, train/loss=50.80]
Epoch 0: | | 616/? [03:49<00:00, 2.68it/s, train/loss=8.490]
Epoch 0: | | 617/? [03:50<00:00, 2.68it/s, train/loss=8.490]
Epoch 0: | | 617/? [03:50<00:00, 2.68it/s, train/loss=18.10]
Epoch 0: | | 618/? [03:50<00:00, 2.68it/s, train/loss=18.10]
Epoch 0: | | 618/? [03:50<00:00, 2.68it/s, train/loss=8.960]
Epoch 0: | | 619/? [03:50<00:00, 2.68it/s, train/loss=8.960]
Epoch 0: | | 619/? [03:50<00:00, 2.68it/s, train/loss=20.80]
Epoch 0: | | 620/? [03:51<00:00, 2.68it/s, train/loss=20.80]
Epoch 0: | | 620/? [03:51<00:00, 2.68it/s, train/loss=7.220]
Epoch 0: | | 621/? [03:51<00:00, 2.68it/s, train/loss=7.220]
Epoch 0: | | 621/? [03:51<00:00, 2.68it/s, train/loss=32.80]
Epoch 0: | | 622/? [03:51<00:00, 2.68it/s, train/loss=32.80]
Epoch 0: | | 622/? [03:51<00:00, 2.68it/s, train/loss=20.60]
Epoch 0: | | 623/? [03:51<00:00, 2.69it/s, train/loss=20.60]
Epoch 0: | | 623/? [03:51<00:00, 2.69it/s, train/loss=41.70]
Epoch 0: | | 624/? [03:52<00:00, 2.69it/s, train/loss=41.70]
Epoch 0: | | 624/? [03:52<00:00, 2.69it/s, train/loss=22.60]
Epoch 0: | | 625/? [03:52<00:00, 2.69it/s, train/loss=22.60]
Epoch 0: | | 625/? [03:52<00:00, 2.69it/s, train/loss=18.70]
Epoch 0: | | 626/? [03:52<00:00, 2.69it/s, train/loss=18.70]
Epoch 0: | | 626/? [03:52<00:00, 2.69it/s, train/loss=14.00]
Epoch 0: | | 627/? [03:53<00:00, 2.69it/s, train/loss=14.00]
Epoch 0: | | 627/? [03:53<00:00, 2.69it/s, train/loss=24.30]
Epoch 0: | | 628/? [03:53<00:00, 2.69it/s, train/loss=24.30]
Epoch 0: | | 628/? [03:53<00:00, 2.69it/s, train/loss=20.40]
Epoch 0: | | 629/? [03:53<00:00, 2.69it/s, train/loss=20.40]
Epoch 0: | | 629/? [03:53<00:00, 2.69it/s, train/loss=34.40]
Epoch 0: | | 630/? [03:54<00:00, 2.69it/s, train/loss=34.40]
Epoch 0: | | 630/? [03:54<00:00, 2.69it/s, train/loss=27.80]
Epoch 0: | | 631/? [03:54<00:00, 2.69it/s, train/loss=27.80]
Epoch 0: | | 631/? [03:54<00:00, 2.69it/s, train/loss=13.00]
Epoch 0: | | 632/? [03:54<00:00, 2.69it/s, train/loss=13.00]
Epoch 0: | | 632/? [03:54<00:00, 2.69it/s, train/loss=16.80]
Epoch 0: | | 633/? [03:55<00:00, 2.69it/s, train/loss=16.80]
Epoch 0: | | 633/? [03:55<00:00, 2.69it/s, train/loss=47.30]
Epoch 0: | | 634/? [03:55<00:00, 2.69it/s, train/loss=47.30]
Epoch 0: | | 634/? [03:55<00:00, 2.69it/s, train/loss=24.20]
Epoch 0: | | 635/? [03:55<00:00, 2.69it/s, train/loss=24.20]
Epoch 0: | | 635/? [03:55<00:00, 2.69it/s, train/loss=7.330]
Epoch 0: | | 636/? [03:56<00:00, 2.69it/s, train/loss=7.330]
Epoch 0: | | 636/? [03:56<00:00, 2.69it/s, train/loss=14.50]
Epoch 0: | | 637/? [03:56<00:00, 2.69it/s, train/loss=14.50]
Epoch 0: | | 637/? [03:56<00:00, 2.69it/s, train/loss=28.80]
Epoch 0: | | 638/? [03:56<00:00, 2.69it/s, train/loss=28.80]
Epoch 0: | | 638/? [03:56<00:00, 2.69it/s, train/loss=24.00]
Epoch 0: | | 639/? [03:57<00:00, 2.69it/s, train/loss=24.00]
Epoch 0: | | 639/? [03:57<00:00, 2.69it/s, train/loss=7.980]
Epoch 0: | | 640/? [03:57<00:00, 2.69it/s, train/loss=7.980]
Epoch 0: | | 640/? [03:57<00:00, 2.69it/s, train/loss=46.90]
Epoch 0: | | 641/? [03:57<00:00, 2.69it/s, train/loss=46.90]
Epoch 0: | | 641/? [03:57<00:00, 2.69it/s, train/loss=21.50]
Epoch 0: | | 642/? [03:58<00:00, 2.70it/s, train/loss=21.50]
Epoch 0: | | 642/? [03:58<00:00, 2.70it/s, train/loss=40.10]
Epoch 0: | | 643/? [03:58<00:00, 2.70it/s, train/loss=40.10]
Epoch 0: | | 643/? [03:58<00:00, 2.70it/s, train/loss=41.30]
Epoch 0: | | 644/? [03:58<00:00, 2.70it/s, train/loss=41.30]
Epoch 0: | | 644/? [03:58<00:00, 2.70it/s, train/loss=48.10]
Epoch 0: | | 645/? [03:59<00:00, 2.70it/s, train/loss=48.10]
Epoch 0: | | 645/? [03:59<00:00, 2.70it/s, train/loss=21.50]
Epoch 0: | | 646/? [03:59<00:00, 2.70it/s, train/loss=21.50]
Epoch 0: | | 646/? [03:59<00:00, 2.70it/s, train/loss=24.60]
Epoch 0: | | 647/? [03:59<00:00, 2.70it/s, train/loss=24.60]
Epoch 0: | | 647/? [03:59<00:00, 2.70it/s, train/loss=63.90]
Epoch 0: | | 648/? [04:00<00:00, 2.70it/s, train/loss=63.90]
Epoch 0: | | 648/? [04:00<00:00, 2.70it/s, train/loss=20.90]
Epoch 0: | | 649/? [04:00<00:00, 2.70it/s, train/loss=20.90]
Epoch 0: | | 649/? [04:00<00:00, 2.70it/s, train/loss=55.00]
Epoch 0: | | 650/? [04:00<00:00, 2.70it/s, train/loss=55.00]
Epoch 0: | | 650/? [04:00<00:00, 2.70it/s, train/loss=25.60]
Epoch 0: | | 651/? [04:01<00:00, 2.70it/s, train/loss=25.60]
Epoch 0: | | 651/? [04:01<00:00, 2.70it/s, train/loss=17.00]
Epoch 0: | | 652/? [04:01<00:00, 2.70it/s, train/loss=17.00]
Epoch 0: | | 652/? [04:01<00:00, 2.70it/s, train/loss=19.20]
Epoch 0: | | 653/? [04:01<00:00, 2.70it/s, train/loss=19.20]
Epoch 0: | | 653/? [04:01<00:00, 2.70it/s, train/loss=20.70]
Epoch 0: | | 654/? [04:02<00:00, 2.70it/s, train/loss=20.70]
Epoch 0: | | 654/? [04:02<00:00, 2.70it/s, train/loss=31.90]
Epoch 0: | | 655/? [04:02<00:00, 2.70it/s, train/loss=31.90]
Epoch 0: | | 655/? [04:02<00:00, 2.70it/s, train/loss=13.60]
Epoch 0: | | 656/? [04:03<00:00, 2.70it/s, train/loss=13.60]
Epoch 0: | | 656/? [04:03<00:00, 2.70it/s, train/loss=25.40]
Epoch 0: | | 657/? [04:03<00:00, 2.70it/s, train/loss=25.40]
Epoch 0: | | 657/? [04:03<00:00, 2.70it/s, train/loss=42.40]
Epoch 0: | | 658/? [04:03<00:00, 2.70it/s, train/loss=42.40]
Epoch 0: | | 658/? [04:03<00:00, 2.70it/s, train/loss=12.40]
Epoch 0: | | 659/? [04:04<00:00, 2.70it/s, train/loss=12.40]
Epoch 0: | | 659/? [04:04<00:00, 2.70it/s, train/loss=29.20]
Epoch 0: | | 660/? [04:04<00:00, 2.70it/s, train/loss=29.20]
Epoch 0: | | 660/? [04:04<00:00, 2.70it/s, train/loss=8.920]
Epoch 0: | | 661/? [04:04<00:00, 2.70it/s, train/loss=8.920]
Epoch 0: | | 661/? [04:04<00:00, 2.70it/s, train/loss=23.50]
Epoch 0: | | 662/? [04:05<00:00, 2.70it/s, train/loss=23.50]
Epoch 0: | | 662/? [04:05<00:00, 2.70it/s, train/loss=24.90]
Epoch 0: | | 663/? [04:05<00:00, 2.70it/s, train/loss=24.90]
Epoch 0: | | 663/? [04:05<00:00, 2.70it/s, train/loss=33.00]
Epoch 0: | | 664/? [04:05<00:00, 2.70it/s, train/loss=33.00]
Epoch 0: | | 664/? [04:05<00:00, 2.70it/s, train/loss=19.80]
Epoch 0: | | 665/? [04:05<00:00, 2.70it/s, train/loss=19.80]
Epoch 0: | | 665/? [04:05<00:00, 2.70it/s, train/loss=25.70]
Epoch 0: | | 666/? [04:06<00:00, 2.70it/s, train/loss=25.70]
Epoch 0: | | 666/? [04:06<00:00, 2.70it/s, train/loss=27.60]
Epoch 0: | | 667/? [04:06<00:00, 2.70it/s, train/loss=27.60]
Epoch 0: | | 667/? [04:06<00:00, 2.70it/s, train/loss=36.80]
Epoch 0: | | 668/? [04:06<00:00, 2.70it/s, train/loss=36.80]
Epoch 0: | | 668/? [04:06<00:00, 2.70it/s, train/loss=18.20]
Epoch 0: | | 669/? [04:07<00:00, 2.71it/s, train/loss=18.20]
Epoch 0: | | 669/? [04:07<00:00, 2.71it/s, train/loss=29.60]
Epoch 0: | | 670/? [04:07<00:00, 2.71it/s, train/loss=29.60]
Epoch 0: | | 670/? [04:07<00:00, 2.71it/s, train/loss=52.50]
Epoch 0: | | 671/? [04:07<00:00, 2.71it/s, train/loss=52.50]
Epoch 0: | | 671/? [04:07<00:00, 2.71it/s, train/loss=11.80]
Epoch 0: | | 672/? [04:08<00:00, 2.71it/s, train/loss=11.80]
Epoch 0: | | 672/? [04:08<00:00, 2.71it/s, train/loss=19.90]
Epoch 0: | | 673/? [04:08<00:00, 2.71it/s, train/loss=19.90]
Epoch 0: | | 673/? [04:08<00:00, 2.71it/s, train/loss=17.60]
Epoch 0: | | 674/? [04:08<00:00, 2.71it/s, train/loss=17.60]
Epoch 0: | | 674/? [04:08<00:00, 2.71it/s, train/loss=31.90]
Epoch 0: | | 675/? [04:09<00:00, 2.71it/s, train/loss=31.90]
Epoch 0: | | 675/? [04:09<00:00, 2.71it/s, train/loss=24.00]
Epoch 0: | | 676/? [04:09<00:00, 2.71it/s, train/loss=24.00]
Epoch 0: | | 676/? [04:09<00:00, 2.71it/s, train/loss=9.220]
Epoch 0: | | 677/? [04:09<00:00, 2.71it/s, train/loss=9.220]
Epoch 0: | | 677/? [04:09<00:00, 2.71it/s, train/loss=29.80]
Epoch 0: | | 678/? [04:10<00:00, 2.71it/s, train/loss=29.80]
Epoch 0: | | 678/? [04:10<00:00, 2.71it/s, train/loss=9.360]
Epoch 0: | | 679/? [04:10<00:00, 2.71it/s, train/loss=9.360]
Epoch 0: | | 679/? [04:10<00:00, 2.71it/s, train/loss=26.90]
Epoch 0: | | 680/? [04:10<00:00, 2.71it/s, train/loss=26.90]
Epoch 0: | | 680/? [04:10<00:00, 2.71it/s, train/loss=23.60]
Epoch 0: | | 681/? [04:11<00:00, 2.71it/s, train/loss=23.60]
Epoch 0: | | 681/? [04:11<00:00, 2.71it/s, train/loss=24.20]
Epoch 0: | | 682/? [04:11<00:00, 2.71it/s, train/loss=24.20]
Epoch 0: | | 682/? [04:11<00:00, 2.71it/s, train/loss=29.20]
Epoch 0: | | 683/? [04:11<00:00, 2.71it/s, train/loss=29.20]
Epoch 0: | | 683/? [04:11<00:00, 2.71it/s, train/loss=23.70]
Epoch 0: | | 684/? [04:12<00:00, 2.71it/s, train/loss=23.70]
Epoch 0: | | 684/? [04:12<00:00, 2.71it/s, train/loss=8.900]
Epoch 0: | | 685/? [04:12<00:00, 2.71it/s, train/loss=8.900]
Epoch 0: | | 685/? [04:12<00:00, 2.71it/s, train/loss=29.60]
Epoch 0: | | 686/? [04:12<00:00, 2.71it/s, train/loss=29.60]
Epoch 0: | | 686/? [04:12<00:00, 2.71it/s, train/loss=44.80]
Epoch 0: | | 687/? [04:13<00:00, 2.71it/s, train/loss=44.80]
Epoch 0: | | 687/? [04:13<00:00, 2.71it/s, train/loss=65.00]
Epoch 0: | | 688/? [04:13<00:00, 2.71it/s, train/loss=65.00]
Epoch 0: | | 688/? [04:13<00:00, 2.71it/s, train/loss=17.10]
Epoch 0: | | 689/? [04:13<00:00, 2.71it/s, train/loss=17.10]
Epoch 0: | | 689/? [04:13<00:00, 2.71it/s, train/loss=28.30]
Epoch 0: | | 690/? [04:14<00:00, 2.71it/s, train/loss=28.30]
Epoch 0: | | 690/? [04:14<00:00, 2.71it/s, train/loss=38.20]
Epoch 0: | | 691/? [04:14<00:00, 2.72it/s, train/loss=38.20]
Epoch 0: | | 691/? [04:14<00:00, 2.72it/s, train/loss=9.110]
Epoch 0: | | 692/? [04:14<00:00, 2.72it/s, train/loss=9.110]
Epoch 0: | | 692/? [04:14<00:00, 2.72it/s, train/loss=29.20]
Epoch 0: | | 693/? [04:15<00:00, 2.72it/s, train/loss=29.20]
Epoch 0: | | 693/? [04:15<00:00, 2.72it/s, train/loss=16.60]
Epoch 0: | | 694/? [04:15<00:00, 2.72it/s, train/loss=16.60]
Epoch 0: | | 694/? [04:15<00:00, 2.72it/s, train/loss=31.70]
Epoch 0: | | 695/? [04:15<00:00, 2.72it/s, train/loss=31.70]
Epoch 0: | | 695/? [04:15<00:00, 2.72it/s, train/loss=11.80]
Epoch 0: | | 696/? [04:16<00:00, 2.72it/s, train/loss=11.80]
Epoch 0: | | 696/? [04:16<00:00, 2.72it/s, train/loss=29.40]
Epoch 0: | | 697/? [04:16<00:00, 2.72it/s, train/loss=29.40]
Epoch 0: | | 697/? [04:16<00:00, 2.72it/s, train/loss=35.70]
Epoch 0: | | 698/? [04:16<00:00, 2.72it/s, train/loss=35.70]
Epoch 0: | | 698/? [04:16<00:00, 2.72it/s, train/loss=14.40]
Epoch 0: | | 699/? [04:17<00:00, 2.72it/s, train/loss=14.40]
Epoch 0: | | 699/? [04:17<00:00, 2.72it/s, train/loss=34.40]
Epoch 0: | | 700/? [04:17<00:00, 2.72it/s, train/loss=34.40]
Epoch 0: | | 700/? [04:17<00:00, 2.72it/s, train/loss=12.10]
Epoch 0: | | 701/? [04:17<00:00, 2.72it/s, train/loss=12.10]
Epoch 0: | | 701/? [04:17<00:00, 2.72it/s, train/loss=15.30]
Epoch 0: | | 702/? [04:18<00:00, 2.72it/s, train/loss=15.30]
Epoch 0: | | 702/? [04:18<00:00, 2.72it/s, train/loss=22.70]
Epoch 0: | | 703/? [04:18<00:00, 2.72it/s, train/loss=22.70]
Epoch 0: | | 703/? [04:18<00:00, 2.72it/s, train/loss=20.80]
Epoch 0: | | 704/? [04:18<00:00, 2.72it/s, train/loss=20.80]
Epoch 0: | | 704/? [04:18<00:00, 2.72it/s, train/loss=7.570]
Epoch 0: | | 705/? [04:19<00:00, 2.72it/s, train/loss=7.570]
Epoch 0: | | 705/? [04:19<00:00, 2.72it/s, train/loss=21.90]
Epoch 0: | | 706/? [04:19<00:00, 2.72it/s, train/loss=21.90]
Epoch 0: | | 706/? [04:19<00:00, 2.72it/s, train/loss=19.50]
Epoch 0: | | 707/? [04:19<00:00, 2.72it/s, train/loss=19.50]
Epoch 0: | | 707/? [04:19<00:00, 2.72it/s, train/loss=11.60]
Epoch 0: | | 708/? [04:20<00:00, 2.72it/s, train/loss=11.60]
Epoch 0: | | 708/? [04:20<00:00, 2.72it/s, train/loss=13.30]
Epoch 0: | | 709/? [04:20<00:00, 2.72it/s, train/loss=13.30]
Epoch 0: | | 709/? [04:20<00:00, 2.72it/s, train/loss=17.80]
Epoch 0: | | 710/? [04:20<00:00, 2.72it/s, train/loss=17.80]
Epoch 0: | | 710/? [04:20<00:00, 2.72it/s, train/loss=19.00]
Epoch 0: | | 711/? [04:21<00:00, 2.72it/s, train/loss=19.00]
Epoch 0: | | 711/? [04:21<00:00, 2.72it/s, train/loss=21.70]
Epoch 0: | | 712/? [04:21<00:00, 2.72it/s, train/loss=21.70]
Epoch 0: | | 712/? [04:21<00:00, 2.72it/s, train/loss=35.30]
Epoch 0: | | 713/? [04:21<00:00, 2.72it/s, train/loss=35.30]
Epoch 0: | | 713/? [04:21<00:00, 2.72it/s, train/loss=21.40]
Epoch 0: | | 714/? [04:22<00:00, 2.72it/s, train/loss=21.40]
Epoch 0: | | 714/? [04:22<00:00, 2.72it/s, train/loss=34.50]
Epoch 0: | | 715/? [04:22<00:00, 2.72it/s, train/loss=34.50]
Epoch 0: | | 715/? [04:22<00:00, 2.72it/s, train/loss=26.30]
Epoch 0: | | 716/? [04:22<00:00, 2.73it/s, train/loss=26.30]
Epoch 0: | | 716/? [04:22<00:00, 2.73it/s, train/loss=17.80]
Epoch 0: | | 717/? [04:23<00:00, 2.73it/s, train/loss=17.80]
Epoch 0: | | 717/? [04:23<00:00, 2.73it/s, train/loss=70.40]
Epoch 0: | | 718/? [04:23<00:00, 2.73it/s, train/loss=70.40]
Epoch 0: | | 718/? [04:23<00:00, 2.73it/s, train/loss=27.50]
Epoch 0: | | 719/? [04:23<00:00, 2.73it/s, train/loss=27.50]
Epoch 0: | | 719/? [04:23<00:00, 2.73it/s, train/loss=17.10]
Epoch 0: | | 720/? [04:24<00:00, 2.73it/s, train/loss=17.10]
Epoch 0: | | 720/? [04:24<00:00, 2.73it/s, train/loss=13.80]
Epoch 0: | | 721/? [04:24<00:00, 2.73it/s, train/loss=13.80]
Epoch 0: | | 721/? [04:24<00:00, 2.73it/s, train/loss=39.50]
Epoch 0: | | 722/? [04:24<00:00, 2.73it/s, train/loss=39.50]
Epoch 0: | | 722/? [04:24<00:00, 2.73it/s, train/loss=23.60]
Epoch 0: | | 723/? [04:25<00:00, 2.73it/s, train/loss=23.60]
Epoch 0: | | 723/? [04:25<00:00, 2.73it/s, train/loss=37.80]
Epoch 0: | | 724/? [04:25<00:00, 2.73it/s, train/loss=37.80]
Epoch 0: | | 724/? [04:25<00:00, 2.73it/s, train/loss=18.90]
Epoch 0: | | 725/? [04:25<00:00, 2.73it/s, train/loss=18.90]
Epoch 0: | | 725/? [04:25<00:00, 2.73it/s, train/loss=31.20]
Epoch 0: | | 726/? [04:25<00:00, 2.73it/s, train/loss=31.20]
Epoch 0: | | 726/? [04:25<00:00, 2.73it/s, train/loss=23.20]
Epoch 0: | | 727/? [04:26<00:00, 2.73it/s, train/loss=23.20]
Epoch 0: | | 727/? [04:26<00:00, 2.73it/s, train/loss=20.90]
Epoch 0: | | 728/? [04:26<00:00, 2.73it/s, train/loss=20.90]
Epoch 0: | | 728/? [04:26<00:00, 2.73it/s, train/loss=24.60]
Epoch 0: | | 729/? [04:26<00:00, 2.73it/s, train/loss=24.60]
Epoch 0: | | 729/? [04:26<00:00, 2.73it/s, train/loss=16.90]
Epoch 0: | | 730/? [04:27<00:00, 2.73it/s, train/loss=16.90]
Epoch 0: | | 730/? [04:27<00:00, 2.73it/s, train/loss=14.70]
Epoch 0: | | 731/? [04:27<00:00, 2.73it/s, train/loss=14.70]
Epoch 0: | | 731/? [04:27<00:00, 2.73it/s, train/loss=7.040]
Epoch 0: | | 732/? [04:27<00:00, 2.73it/s, train/loss=7.040]
Epoch 0: | | 732/? [04:27<00:00, 2.73it/s, train/loss=16.10]
Epoch 0: | | 733/? [04:28<00:00, 2.73it/s, train/loss=16.10]
Epoch 0: | | 733/? [04:28<00:00, 2.73it/s, train/loss=39.30]
Epoch 0: | | 734/? [04:28<00:00, 2.73it/s, train/loss=39.30]
Epoch 0: | | 734/? [04:28<00:00, 2.73it/s, train/loss=26.50]
Epoch 0: | | 735/? [04:28<00:00, 2.73it/s, train/loss=26.50]
Epoch 0: | | 735/? [04:28<00:00, 2.73it/s, train/loss=14.00]
Epoch 0: | | 736/? [04:29<00:00, 2.73it/s, train/loss=14.00]
Epoch 0: | | 736/? [04:29<00:00, 2.73it/s, train/loss=18.90]
Epoch 0: | | 737/? [04:29<00:00, 2.73it/s, train/loss=18.90]
Epoch 0: | | 737/? [04:29<00:00, 2.73it/s, train/loss=32.80]
Epoch 0: | | 738/? [04:29<00:00, 2.73it/s, train/loss=32.80]
Epoch 0: | | 738/? [04:29<00:00, 2.73it/s, train/loss=22.50]
Epoch 0: | | 739/? [04:30<00:00, 2.73it/s, train/loss=22.50]
Epoch 0: | | 739/? [04:30<00:00, 2.73it/s, train/loss=19.90]
Epoch 0: | | 740/? [04:30<00:00, 2.74it/s, train/loss=19.90]
Epoch 0: | | 740/? [04:30<00:00, 2.74it/s, train/loss=13.80]
Epoch 0: | | 741/? [04:30<00:00, 2.74it/s, train/loss=13.80]
Epoch 0: | | 741/? [04:30<00:00, 2.74it/s, train/loss=46.20]
Epoch 0: | | 742/? [04:31<00:00, 2.74it/s, train/loss=46.20]
Epoch 0: | | 742/? [04:31<00:00, 2.74it/s, train/loss=23.10]
Epoch 0: | | 743/? [04:31<00:00, 2.74it/s, train/loss=23.10]
Epoch 0: | | 743/? [04:31<00:00, 2.74it/s, train/loss=35.30]
Epoch 0: | | 744/? [04:31<00:00, 2.74it/s, train/loss=35.30]
Epoch 0: | | 744/? [04:31<00:00, 2.74it/s, train/loss=17.30]
Epoch 0: | | 745/? [04:32<00:00, 2.74it/s, train/loss=17.30]
Epoch 0: | | 745/? [04:32<00:00, 2.74it/s, train/loss=35.60]
Epoch 0: | | 746/? [04:32<00:00, 2.74it/s, train/loss=35.60]
Epoch 0: | | 746/? [04:32<00:00, 2.74it/s, train/loss=30.30]
Epoch 0: | | 747/? [04:32<00:00, 2.74it/s, train/loss=30.30]
Epoch 0: | | 747/? [04:32<00:00, 2.74it/s, train/loss=9.280]
Epoch 0: | | 748/? [04:33<00:00, 2.74it/s, train/loss=9.280]
Epoch 0: | | 748/? [04:33<00:00, 2.74it/s, train/loss=35.70]
Epoch 0: | | 749/? [04:33<00:00, 2.74it/s, train/loss=35.70]
Epoch 0: | | 749/? [04:33<00:00, 2.74it/s, train/loss=30.50]
Epoch 0: | | 750/? [04:33<00:00, 2.74it/s, train/loss=30.50]
Epoch 0: | | 750/? [04:33<00:00, 2.74it/s, train/loss=28.80]
Epoch 0: | | 751/? [04:34<00:00, 2.74it/s, train/loss=28.80]
Epoch 0: | | 751/? [04:34<00:00, 2.74it/s, train/loss=23.70]
Epoch 0: | | 752/? [04:34<00:00, 2.74it/s, train/loss=23.70]
Epoch 0: | | 752/? [04:34<00:00, 2.74it/s, train/loss=22.00]
Epoch 0: | | 753/? [04:34<00:00, 2.74it/s, train/loss=22.00]
Epoch 0: | | 753/? [04:34<00:00, 2.74it/s, train/loss=16.70]
Epoch 0: | | 754/? [04:35<00:00, 2.74it/s, train/loss=16.70]
Epoch 0: | | 754/? [04:35<00:00, 2.74it/s, train/loss=8.490]
Epoch 0: | | 755/? [04:35<00:00, 2.74it/s, train/loss=8.490]
Epoch 0: | | 755/? [04:35<00:00, 2.74it/s, train/loss=12.40]
Epoch 0: | | 756/? [04:35<00:00, 2.74it/s, train/loss=12.40]
Epoch 0: | | 756/? [04:35<00:00, 2.74it/s, train/loss=11.90]
Epoch 0: | | 757/? [04:36<00:00, 2.74it/s, train/loss=11.90]
Epoch 0: | | 757/? [04:36<00:00, 2.74it/s, train/loss=15.30]
Epoch 0: | | 758/? [04:36<00:00, 2.74it/s, train/loss=15.30]
Epoch 0: | | 758/? [04:36<00:00, 2.74it/s, train/loss=18.30]
Epoch 0: | | 759/? [04:36<00:00, 2.74it/s, train/loss=18.30]
Epoch 0: | | 759/? [04:36<00:00, 2.74it/s, train/loss=15.90]
Epoch 0: | | 760/? [04:37<00:00, 2.74it/s, train/loss=15.90]
Epoch 0: | | 760/? [04:37<00:00, 2.74it/s, train/loss=30.70]
Epoch 0: | | 761/? [04:37<00:00, 2.74it/s, train/loss=30.70]
Epoch 0: | | 761/? [04:37<00:00, 2.74it/s, train/loss=37.50]
Epoch 0: | | 762/? [04:37<00:00, 2.74it/s, train/loss=37.50]
Epoch 0: | | 762/? [04:37<00:00, 2.74it/s, train/loss=24.00]
Epoch 0: | | 763/? [04:38<00:00, 2.74it/s, train/loss=24.00]
Epoch 0: | | 763/? [04:38<00:00, 2.74it/s, train/loss=23.80]
Epoch 0: | | 764/? [04:38<00:00, 2.74it/s, train/loss=23.80]
Epoch 0: | | 764/? [04:38<00:00, 2.74it/s, train/loss=13.40]
Epoch 0: | | 765/? [04:38<00:00, 2.74it/s, train/loss=13.40]
Epoch 0: | | 765/? [04:38<00:00, 2.74it/s, train/loss=41.50]
Epoch 0: | | 766/? [04:39<00:00, 2.75it/s, train/loss=41.50]
Epoch 0: | | 766/? [04:39<00:00, 2.75it/s, train/loss=29.70]
Epoch 0: | | 767/? [04:39<00:00, 2.75it/s, train/loss=29.70]
Epoch 0: | | 767/? [04:39<00:00, 2.75it/s, train/loss=16.90]
Epoch 0: | | 768/? [04:39<00:00, 2.75it/s, train/loss=16.90]
Epoch 0: | | 768/? [04:39<00:00, 2.75it/s, train/loss=31.50]
Epoch 0: | | 769/? [04:40<00:00, 2.75it/s, train/loss=31.50]
Epoch 0: | | 769/? [04:40<00:00, 2.75it/s, train/loss=29.30]
Epoch 0: | | 770/? [04:40<00:00, 2.75it/s, train/loss=29.30]
Epoch 0: | | 770/? [04:40<00:00, 2.75it/s, train/loss=23.60]
Epoch 0: | | 771/? [04:40<00:00, 2.75it/s, train/loss=23.60]
Epoch 0: | | 771/? [04:40<00:00, 2.75it/s, train/loss=17.80]
Epoch 0: | | 772/? [04:40<00:00, 2.75it/s, train/loss=17.80]
Epoch 0: | | 772/? [04:40<00:00, 2.75it/s, train/loss=11.00]
Epoch 0: | | 773/? [04:41<00:00, 2.75it/s, train/loss=11.00]
Epoch 0: | | 773/? [04:41<00:00, 2.75it/s, train/loss=34.10]
Epoch 0: | | 774/? [04:41<00:00, 2.75it/s, train/loss=34.10]
Epoch 0: | | 774/? [04:41<00:00, 2.75it/s, train/loss=15.80]
Epoch 0: | | 775/? [04:41<00:00, 2.75it/s, train/loss=15.80]
Epoch 0: | | 775/? [04:41<00:00, 2.75it/s, train/loss=8.520]
Epoch 0: | | 776/? [04:42<00:00, 2.75it/s, train/loss=8.520]
Epoch 0: | | 776/? [04:42<00:00, 2.75it/s, train/loss=6.730]
Epoch 0: | | 777/? [04:42<00:00, 2.75it/s, train/loss=6.730]
Epoch 0: | | 777/? [04:42<00:00, 2.75it/s, train/loss=16.90]
Epoch 0: | | 778/? [04:42<00:00, 2.75it/s, train/loss=16.90]
Epoch 0: | | 778/? [04:42<00:00, 2.75it/s, train/loss=19.80]
Epoch 0: | | 779/? [04:43<00:00, 2.75it/s, train/loss=19.80]
Epoch 0: | | 779/? [04:43<00:00, 2.75it/s, train/loss=53.00]
Epoch 0: | | 780/? [04:43<00:00, 2.75it/s, train/loss=53.00]
Epoch 0: | | 780/? [04:43<00:00, 2.75it/s, train/loss=22.80]
Epoch 0: | | 781/? [04:44<00:00, 2.75it/s, train/loss=22.80]
Epoch 0: | | 781/? [04:44<00:00, 2.75it/s, train/loss=22.60]
Epoch 0: | | 782/? [04:44<00:00, 2.75it/s, train/loss=22.60]
Epoch 0: | | 782/? [04:44<00:00, 2.75it/s, train/loss=12.40]
Epoch 0: | | 783/? [04:44<00:00, 2.75it/s, train/loss=12.40]
Epoch 0: | | 783/? [04:44<00:00, 2.75it/s, train/loss=27.50]
Epoch 0: | | 784/? [04:45<00:00, 2.75it/s, train/loss=27.50]
Epoch 0: | | 784/? [04:45<00:00, 2.75it/s, train/loss=32.30]
Epoch 0: | | 785/? [04:45<00:00, 2.75it/s, train/loss=32.30]
Epoch 0: | | 785/? [04:45<00:00, 2.75it/s, train/loss=36.80]
Epoch 0: | | 786/? [04:45<00:00, 2.75it/s, train/loss=36.80]
Epoch 0: | | 786/? [04:45<00:00, 2.75it/s, train/loss=21.70]
Epoch 0: | | 787/? [04:46<00:00, 2.75it/s, train/loss=21.70]
Epoch 0: | | 787/? [04:46<00:00, 2.75it/s, train/loss=38.40]
Epoch 0: | | 788/? [04:46<00:00, 2.75it/s, train/loss=38.40]
Epoch 0: | | 788/? [04:46<00:00, 2.75it/s, train/loss=37.90]
Epoch 0: | | 789/? [04:46<00:00, 2.75it/s, train/loss=37.90]
Epoch 0: | | 789/? [04:46<00:00, 2.75it/s, train/loss=36.00]
Epoch 0: | | 790/? [04:47<00:00, 2.75it/s, train/loss=36.00]
Epoch 0: | | 790/? [04:47<00:00, 2.75it/s, train/loss=20.20]
Epoch 0: | | 791/? [04:47<00:00, 2.75it/s, train/loss=20.20]
Epoch 0: | | 791/? [04:47<00:00, 2.75it/s, train/loss=21.00]
Epoch 0: | | 792/? [04:47<00:00, 2.75it/s, train/loss=21.00]
Epoch 0: | | 792/? [04:47<00:00, 2.75it/s, train/loss=18.70]
Epoch 0: | | 793/? [04:48<00:00, 2.75it/s, train/loss=18.70]
Epoch 0: | | 793/? [04:48<00:00, 2.75it/s, train/loss=48.10]
Epoch 0: | | 794/? [04:48<00:00, 2.75it/s, train/loss=48.10]
Epoch 0: | | 794/? [04:48<00:00, 2.75it/s, train/loss=8.580]
Epoch 0: | | 795/? [04:48<00:00, 2.75it/s, train/loss=8.580]
Epoch 0: | | 795/? [04:48<00:00, 2.75it/s, train/loss=20.30]
Epoch 0: | | 796/? [04:49<00:00, 2.75it/s, train/loss=20.30]
Epoch 0: | | 796/? [04:49<00:00, 2.75it/s, train/loss=17.20]
Epoch 0: | | 797/? [04:49<00:00, 2.75it/s, train/loss=17.20]
Epoch 0: | | 797/? [04:49<00:00, 2.75it/s, train/loss=21.70]
Epoch 0: | | 798/? [04:49<00:00, 2.75it/s, train/loss=21.70]
Epoch 0: | | 798/? [04:49<00:00, 2.75it/s, train/loss=30.10]
Epoch 0: | | 799/? [04:50<00:00, 2.76it/s, train/loss=30.10]
Epoch 0: | | 799/? [04:50<00:00, 2.76it/s, train/loss=13.00]
Epoch 0: | | 800/? [04:50<00:00, 2.76it/s, train/loss=13.00]
Epoch 0: | | 800/? [04:50<00:00, 2.76it/s, train/loss=6.670]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:03, 10.50it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:03, 11.18it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:03, 11.06it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:03, 11.04it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:03, 11.05it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:03, 11.10it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:02, 11.15it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:02, 11.26it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:02, 11.39it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:00<00:02, 11.49it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:00<00:02, 11.50it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:02, 11.49it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:02, 11.51it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 11.50it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 11.17it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 10.94it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:02, 10.99it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:01<00:01, 11.04it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:01<00:01, 11.08it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:01<00:01, 11.10it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:01<00:01, 11.11it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:01<00:01, 11.16it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:02<00:01, 11.18it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 11.23it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 11.25it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 11.27it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 11.14it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:02<00:01, 11.16it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:02<00:00, 11.20it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:02<00:00, 11.25it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:02<00:00, 11.29it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:02<00:00, 11.33it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:02<00:00, 11.35it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:02<00:00, 11.36it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 11.38it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:03<00:00, 11.38it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:03<00:00, 11.38it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:03<00:00, 11.34it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:03<00:00, 11.34it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:03<00:00, 11.35it/s][A
[A
Epoch 0: | | 800/? [04:58<00:00, 2.68it/s, train/loss=6.670]
`Trainer.fit` stopped: `max_steps=800` reached.
Epoch 0: | | 800/? [04:58<00:00, 2.68it/s, train/loss=6.670]
Epoch 0: | | 800/? [04:58<00:00, 2.68it/s, train/loss=6.670]
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
Testing: | | 0/? [00:00<?, ?it/s]
Testing: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 1%| | 1/120 [00:00<00:10, 11.05it/s]
Testing DataLoader 0: 2%|▏ | 2/120 [00:00<00:10, 11.31it/s]
Testing DataLoader 0: 2%|▎ | 3/120 [00:00<00:10, 11.59it/s]
Testing DataLoader 0: 3%|▎ | 4/120 [00:00<00:09, 11.62it/s]
Testing DataLoader 0: 4%|▍ | 5/120 [00:00<00:09, 11.56it/s]
Testing DataLoader 0: 5%|▌ | 6/120 [00:00<00:09, 11.51it/s]
Testing DataLoader 0: 6%|▌ | 7/120 [00:00<00:09, 11.41it/s]
Testing DataLoader 0: 7%|▋ | 8/120 [00:00<00:09, 11.42it/s]
Testing DataLoader 0: 8%|▊ | 9/120 [00:00<00:09, 11.42it/s]
Testing DataLoader 0: 8%|▊ | 10/120 [00:00<00:09, 11.45it/s]
Testing DataLoader 0: 9%|▉ | 11/120 [00:00<00:09, 11.50it/s]
Testing DataLoader 0: 10%|█ | 12/120 [00:01<00:09, 11.55it/s]
Testing DataLoader 0: 11%|█ | 13/120 [00:01<00:09, 11.56it/s]
Testing DataLoader 0: 12%|█▏ | 14/120 [00:01<00:09, 11.60it/s]
Testing DataLoader 0: 12%|█▎ | 15/120 [00:01<00:09, 11.64it/s]
Testing DataLoader 0: 13%|█▎ | 16/120 [00:01<00:08, 11.63it/s]
Testing DataLoader 0: 14%|█▍ | 17/120 [00:01<00:08, 11.67it/s]
Testing DataLoader 0: 15%|█▌ | 18/120 [00:01<00:08, 11.70it/s]
Testing DataLoader 0: 16%|█▌ | 19/120 [00:01<00:08, 11.70it/s]
Testing DataLoader 0: 17%|█▋ | 20/120 [00:01<00:08, 11.67it/s]
Testing DataLoader 0: 18%|█▊ | 21/120 [00:01<00:08, 11.70it/s]
Testing DataLoader 0: 18%|█▊ | 22/120 [00:01<00:08, 11.72it/s]
Testing DataLoader 0: 19%|█▉ | 23/120 [00:01<00:08, 11.51it/s]
Testing DataLoader 0: 20%|██ | 24/120 [00:02<00:08, 11.34it/s]
Testing DataLoader 0: 21%|██ | 25/120 [00:02<00:08, 11.19it/s]
Testing DataLoader 0: 22%|██▏ | 26/120 [00:02<00:08, 11.21it/s]
Testing DataLoader 0: 22%|██▎ | 27/120 [00:02<00:08, 11.23it/s]
Testing DataLoader 0: 23%|██▎ | 28/120 [00:02<00:08, 11.23it/s]
Testing DataLoader 0: 24%|██▍ | 29/120 [00:02<00:08, 11.26it/s]
Testing DataLoader 0: 25%|██▌ | 30/120 [00:02<00:07, 11.29it/s]
Testing DataLoader 0: 26%|██▌ | 31/120 [00:02<00:07, 11.30it/s]
Testing DataLoader 0: 27%|██▋ | 32/120 [00:02<00:07, 11.32it/s]
Testing DataLoader 0: 28%|██▊ | 33/120 [00:02<00:07, 11.33it/s]
Testing DataLoader 0: 28%|██▊ | 34/120 [00:02<00:07, 11.36it/s]
Testing DataLoader 0: 29%|██▉ | 35/120 [00:03<00:07, 11.37it/s]
Testing DataLoader 0: 30%|███ | 36/120 [00:03<00:07, 11.38it/s]
Testing DataLoader 0: 31%|███ | 37/120 [00:03<00:07, 11.41it/s]
Testing DataLoader 0: 32%|███▏ | 38/120 [00:03<00:07, 11.43it/s]
Testing DataLoader 0: 32%|███▎ | 39/120 [00:03<00:07, 11.45it/s]
Testing DataLoader 0: 33%|███▎ | 40/120 [00:03<00:06, 11.46it/s]
Testing DataLoader 0: 34%|███▍ | 41/120 [00:03<00:06, 11.47it/s]
Testing DataLoader 0: 35%|███▌ | 42/120 [00:03<00:06, 11.49it/s]
Testing DataLoader 0: 36%|███▌ | 43/120 [00:03<00:06, 11.51it/s]
Testing DataLoader 0: 37%|███▋ | 44/120 [00:03<00:06, 11.52it/s]
Testing DataLoader 0: 38%|███▊ | 45/120 [00:03<00:06, 11.50it/s]
Testing DataLoader 0: 38%|███▊ | 46/120 [00:04<00:06, 11.50it/s]
Testing DataLoader 0: 39%|███▉ | 47/120 [00:04<00:06, 11.50it/s]
Testing DataLoader 0: 40%|████ | 48/120 [00:04<00:06, 11.51it/s]
Testing DataLoader 0: 41%|████ | 49/120 [00:04<00:06, 11.51it/s]
Testing DataLoader 0: 42%|████▏ | 50/120 [00:04<00:06, 11.51it/s]
Testing DataLoader 0: 42%|████▎ | 51/120 [00:04<00:05, 11.52it/s]
Testing DataLoader 0: 43%|████▎ | 52/120 [00:04<00:05, 11.43it/s]
Testing DataLoader 0: 44%|████▍ | 53/120 [00:04<00:05, 11.40it/s]
Testing DataLoader 0: 45%|████▌ | 54/120 [00:04<00:05, 11.41it/s]
Testing DataLoader 0: 46%|████▌ | 55/120 [00:04<00:05, 11.42it/s]
Testing DataLoader 0: 47%|████▋ | 56/120 [00:04<00:05, 11.44it/s]
Testing DataLoader 0: 48%|████▊ | 57/120 [00:04<00:05, 11.44it/s]
Testing DataLoader 0: 48%|████▊ | 58/120 [00:05<00:05, 11.44it/s]
Testing DataLoader 0: 49%|████▉ | 59/120 [00:05<00:05, 11.44it/s]
Testing DataLoader 0: 50%|█████ | 60/120 [00:05<00:05, 11.44it/s]
Testing DataLoader 0: 51%|█████ | 61/120 [00:05<00:05, 11.45it/s]
Testing DataLoader 0: 52%|█████▏ | 62/120 [00:05<00:05, 11.46it/s]
Testing DataLoader 0: 52%|█████▎ | 63/120 [00:05<00:04, 11.47it/s]
Testing DataLoader 0: 53%|█████▎ | 64/120 [00:05<00:04, 11.48it/s]
Testing DataLoader 0: 54%|█████▍ | 65/120 [00:05<00:04, 11.49it/s]
Testing DataLoader 0: 55%|█████▌ | 66/120 [00:05<00:04, 11.49it/s]
Testing DataLoader 0: 56%|█████▌ | 67/120 [00:05<00:04, 11.49it/s]
Testing DataLoader 0: 57%|█████▋ | 68/120 [00:05<00:04, 11.49it/s]
Testing DataLoader 0: 57%|█████▊ | 69/120 [00:06<00:04, 11.46it/s]
Testing DataLoader 0: 58%|█████▊ | 70/120 [00:06<00:04, 11.46it/s]
Testing DataLoader 0: 59%|█████▉ | 71/120 [00:06<00:04, 11.47it/s]
Testing DataLoader 0: 60%|██████ | 72/120 [00:06<00:04, 11.47it/s]
Testing DataLoader 0: 61%|██████ | 73/120 [00:06<00:04, 11.48it/s]
Testing DataLoader 0: 62%|██████▏ | 74/120 [00:06<00:04, 11.48it/s]
Testing DataLoader 0: 62%|██████▎ | 75/120 [00:06<00:03, 11.49it/s]
Testing DataLoader 0: 63%|██████▎ | 76/120 [00:06<00:03, 11.50it/s]
Testing DataLoader 0: 64%|██████▍ | 77/120 [00:06<00:03, 11.50it/s]
Testing DataLoader 0: 65%|██████▌ | 78/120 [00:06<00:03, 11.50it/s]
Testing DataLoader 0: 66%|██████▌ | 79/120 [00:06<00:03, 11.50it/s]
Testing DataLoader 0: 67%|██████▋ | 80/120 [00:06<00:03, 11.51it/s]
Testing DataLoader 0: 68%|██████▊ | 81/120 [00:07<00:03, 11.51it/s]
Testing DataLoader 0: 68%|██████▊ | 82/120 [00:07<00:03, 11.52it/s]
Testing DataLoader 0: 69%|██████▉ | 83/120 [00:07<00:03, 11.53it/s]
Testing DataLoader 0: 70%|███████ | 84/120 [00:07<00:03, 11.53it/s]
Testing DataLoader 0: 71%|███████ | 85/120 [00:07<00:03, 11.54it/s]
Testing DataLoader 0: 72%|███████▏ | 86/120 [00:07<00:02, 11.54it/s]
Testing DataLoader 0: 72%|███████▎ | 87/120 [00:07<00:02, 11.54it/s]
Testing DataLoader 0: 73%|███████▎ | 88/120 [00:07<00:02, 11.55it/s]
Testing DataLoader 0: 74%|███████▍ | 89/120 [00:07<00:02, 11.56it/s]
Testing DataLoader 0: 75%|███████▌ | 90/120 [00:07<00:02, 11.56it/s]
Testing DataLoader 0: 76%|███████▌ | 91/120 [00:07<00:02, 11.57it/s]
Testing DataLoader 0: 77%|███████▋ | 92/120 [00:07<00:02, 11.58it/s]
Testing DataLoader 0: 78%|███████▊ | 93/120 [00:08<00:02, 11.59it/s]
Testing DataLoader 0: 78%|███████▊ | 94/120 [00:08<00:02, 11.60it/s]
Testing DataLoader 0: 79%|███████▉ | 95/120 [00:08<00:02, 11.61it/s]
Testing DataLoader 0: 80%|████████ | 96/120 [00:08<00:02, 11.61it/s]
Testing DataLoader 0: 81%|████████ | 97/120 [00:08<00:01, 11.61it/s]
Testing DataLoader 0: 82%|████████▏ | 98/120 [00:08<00:01, 11.62it/s]
Testing DataLoader 0: 82%|████████▎ | 99/120 [00:08<00:01, 11.62it/s]
Testing DataLoader 0: 83%|████████▎ | 100/120 [00:08<00:01, 11.62it/s]
Testing DataLoader 0: 84%|████████▍ | 101/120 [00:08<00:01, 11.62it/s]
Testing DataLoader 0: 85%|████████▌ | 102/120 [00:08<00:01, 11.62it/s]
Testing DataLoader 0: 86%|████████▌ | 103/120 [00:08<00:01, 11.61it/s]
Testing DataLoader 0: 87%|████████▋ | 104/120 [00:08<00:01, 11.62it/s]
Testing DataLoader 0: 88%|████████▊ | 105/120 [00:09<00:01, 11.62it/s]
Testing DataLoader 0: 88%|████████▊ | 106/120 [00:09<00:01, 11.61it/s]
Testing DataLoader 0: 89%|████████▉ | 107/120 [00:09<00:01, 11.61it/s]
Testing DataLoader 0: 90%|█████████ | 108/120 [00:09<00:01, 11.61it/s]
Testing DataLoader 0: 91%|█████████ | 109/120 [00:09<00:00, 11.61it/s]
Testing DataLoader 0: 92%|█████████▏| 110/120 [00:09<00:00, 11.59it/s]
Testing DataLoader 0: 92%|█████████▎| 111/120 [00:09<00:00, 11.59it/s]
Testing DataLoader 0: 93%|█████████▎| 112/120 [00:09<00:00, 11.59it/s]
Testing DataLoader 0: 94%|█████████▍| 113/120 [00:09<00:00, 11.57it/s]
Testing DataLoader 0: 95%|█████████▌| 114/120 [00:09<00:00, 11.57it/s]
Testing DataLoader 0: 96%|█████████▌| 115/120 [00:09<00:00, 11.58it/s]
Testing DataLoader 0: 97%|█████████▋| 116/120 [00:10<00:00, 11.58it/s]
Testing DataLoader 0: 98%|█████████▊| 117/120 [00:10<00:00, 11.58it/s]
Testing DataLoader 0: 98%|█████████▊| 118/120 [00:10<00:00, 11.58it/s]
Testing DataLoader 0: 99%|█████████▉| 119/120 [00:10<00:00, 11.58it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:10<00:00, 11.59it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:18<00:00, 6.56it/s]
Test results saved to outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/save
Running step 4: texture refinement
{'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800},
'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}},
'data_type': 'dreamcraft3d-single-image-datamodule',
'description': '',
'exp_dir': 'outputs/dreamcraft3d-texture',
'exp_root_dir': 'outputs',
'n_gpus': 1,
'name': 'dreamcraft3d-texture',
'resume': None,
'seed': 0,
'system': {'stage': 'texture', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True, 'isosurface_remove_outliers': True, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378}, 'fix_geometry': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'dreamcraft3d-mask-nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'stable-diffusion-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'prompt': 'A green leafy plant in a striped terracotta pot', 'front_threshold': 30.0, 'back_threshold': 30.0}, 'guidance_type': 'dreamcraft3d-stable-diffusion-bsd-lora-guidance', 'guidance': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'pretrained_model_name_or_path_lora': 'stabilityai/stable-diffusion-2-1-base', 'guidance_scale': 5.0, 'min_step_percent': 0.05, 'max_step_percent': 0.3, 'only_pretrain_step': 10, 'per_update_pretrain_step': 10}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': -1, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_vsd': 0.1, 'lambda_lora': 0.1, 'lambda_pretrain': 0.1, 'lambda_3d_sds': 0.01, 'lambda_rgb': 1000.0, 'lambda_mask': 0.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_z_variance': 0.0, 'lambda_reg': 0.0}, 'optimizer': {'name': 'AdamW', 'args': {'betas': [0.9, 0.99], 'eps': 0.0001}, 'params': {'geometry.encoding': {'lr': 0.005}, 'geometry.feature_network': {'lr': 0.001}, 'guidance': {'lr': 0.0001}}}, 'geometry_convert_from': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/ckpts/last.ckpt'},
'system_type': 'dreamcraft3d-system',
'tag': 'replicate_user',
'timestamp': '@20240222-135357',
'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32, 'gradient_clip_val': 1.0},
'trial_dir': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357',
'trial_name': 'replicate_user@20240222-135357',
'use_timestamp': True}
Initializing geometry from a given checkpoint ...
Loading Stable Diffusion ...
Loading pipeline components...: 0%| | 0/4 [00:00<?, ?it/s]
Loading pipeline components...: 25%|██▌ | 1/4 [00:00<00:01, 1.81it/s]
Loading pipeline components...: 50%|█████ | 2/4 [00:00<00:00, 3.48it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:03<00:00, 1.11it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:03<00:00, 1.26it/s]
Loading pipeline components...: 0%| | 0/4 [00:00<?, ?it/s]
Loading pipeline components...: 25%|██▌ | 1/4 [00:00<00:01, 1.83it/s]
Loading pipeline components...: 50%|█████ | 2/4 [00:00<00:00, 3.52it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:01<00:00, 4.19it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:01<00:00, 3.73it/s]
Loaded Stable Diffusion!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_5m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_5m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_11m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_11m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_224 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_384 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/controlnet_aux/segment_anything/modeling/tiny_vit_sam.py:654: UserWarning: Overwriting tiny_vit_21m_512 in registry with controlnet_aux.segment_anything.modeling.tiny_vit_sam.tiny_vit_21m_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
return register_model(fn_wrapper)
tokenizer/tokenizer_config.json: 0%| | 0.00/807 [00:00<?, ?B/s]
tokenizer/tokenizer_config.json: 100%|██████████| 807/807 [00:00<00:00, 5.66MB/s]
tokenizer/vocab.json: 0%| | 0.00/1.06M [00:00<?, ?B/s]
tokenizer/vocab.json: 100%|██████████| 1.06M/1.06M [00:00<00:00, 3.06MB/s]
tokenizer/vocab.json: 100%|██████████| 1.06M/1.06M [00:00<00:00, 3.06MB/s]
tokenizer/merges.txt: 0%| | 0.00/525k [00:00<?, ?B/s]
tokenizer/merges.txt: 100%|██████████| 525k/525k [00:00<00:00, 21.7MB/s]
tokenizer/special_tokens_map.json: 0%| | 0.00/460 [00:00<?, ?B/s]
tokenizer/special_tokens_map.json: 100%|██████████| 460/460 [00:00<00:00, 2.77MB/s]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
| Name | Type | Params
----------------------------------------------------------
0 | geometry | TetrahedraSDFGrid | 12.6 M
1 | material | NoMaterial | 0
2 | background | SolidColorBackground | 0
3 | renderer | NVDiffRasterizer | 0
4 | guidance | StableDiffusionBSDGuidance | 870 M
----------------------------------------------------------
882 M Trainable params
0 Non-trainable params
882 M Total params
3,530.663 Total estimated model params size (MB)
Validation results will be saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save
Training: | | 0/? [00:00<?, ?it/s]
Training: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 0/? [00:00<?, ?it/s]
Epoch 0: | | 1/? [00:01<00:00, 0.61it/s]
Epoch 0: | | 1/? [00:01<00:00, 0.60it/s, train/loss=1.330]
Epoch 0: | | 2/? [00:01<00:00, 1.03it/s, train/loss=1.330]
Epoch 0: | | 2/? [00:02<00:00, 1.00it/s, train/loss=1.800]
Epoch 0: | | 3/? [00:02<00:00, 1.46it/s, train/loss=1.800]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/diffusers/models/attention_processor.py:1746: FutureWarning: `LoRAAttnProcessor` is deprecated and will be removed in version 0.26.0. Make sure use AttnProcessor instead by settingLoRA layers to `self.{to_q,to_k,to_v,to_out[0]}.lora_layer` respectively. This will be done automatically when using `LoraLoaderMixin.load_lora_weights`
deprecate(
Epoch 0: | | 3/? [00:02<00:00, 1.46it/s, train/loss=20.90]
Epoch 0: | | 4/? [00:02<00:00, 1.62it/s, train/loss=20.90]
Epoch 0: | | 4/? [00:02<00:00, 1.62it/s, train/loss=2.410]
Epoch 0: | | 5/? [00:02<00:00, 1.97it/s, train/loss=2.410]
Epoch 0: | | 5/? [00:02<00:00, 1.97it/s, train/loss=20.40]
Epoch 0: | | 6/? [00:02<00:00, 2.06it/s, train/loss=20.40]
Epoch 0: | | 6/? [00:02<00:00, 2.05it/s, train/loss=3.250]
Epoch 0: | | 7/? [00:02<00:00, 2.35it/s, train/loss=3.250]
Epoch 0: | | 7/? [00:02<00:00, 2.35it/s, train/loss=19.90]
Epoch 0: | | 8/? [00:03<00:00, 2.38it/s, train/loss=19.90]
Epoch 0: | | 8/? [00:03<00:00, 2.38it/s, train/loss=2.610]
Epoch 0: | | 9/? [00:03<00:00, 2.63it/s, train/loss=2.610]
Epoch 0: | | 9/? [00:03<00:00, 2.63it/s, train/loss=19.50]
Epoch 0: | | 10/? [00:03<00:00, 2.63it/s, train/loss=19.50]
Epoch 0: | | 10/? [00:03<00:00, 2.63it/s, train/loss=0.927]
Epoch 0: | | 11/? [00:04<00:00, 2.34it/s, train/loss=0.927]
Epoch 0: | | 11/? [00:04<00:00, 2.31it/s, train/loss=3.080]
Epoch 0: | | 12/? [00:05<00:00, 2.38it/s, train/loss=3.080]
Epoch 0: | | 12/? [00:05<00:00, 2.36it/s, train/loss=3.780]
Epoch 0: | | 13/? [00:05<00:00, 2.52it/s, train/loss=3.780]
Epoch 0: | | 13/? [00:05<00:00, 2.52it/s, train/loss=18.80]
Epoch 0: | | 14/? [00:05<00:00, 2.53it/s, train/loss=18.80]
Epoch 0: | | 14/? [00:05<00:00, 2.53it/s, train/loss=1.730]
Epoch 0: | | 15/? [00:05<00:00, 2.68it/s, train/loss=1.730]
Epoch 0: | | 15/? [00:05<00:00, 2.68it/s, train/loss=18.60]
Epoch 0: | | 16/? [00:05<00:00, 2.68it/s, train/loss=18.60]
Epoch 0: | | 16/? [00:05<00:00, 2.68it/s, train/loss=1.910]
Epoch 0: | | 17/? [00:06<00:00, 2.82it/s, train/loss=1.910]
Epoch 0: | | 17/? [00:06<00:00, 2.82it/s, train/loss=18.30]
Epoch 0: | | 18/? [00:06<00:00, 2.80it/s, train/loss=18.30]
Epoch 0: | | 18/? [00:06<00:00, 2.80it/s, train/loss=0.785]
Epoch 0: | | 19/? [00:06<00:00, 2.93it/s, train/loss=0.785]
Epoch 0: | | 19/? [00:06<00:00, 2.93it/s, train/loss=18.00]
Epoch 0: | | 20/? [00:06<00:00, 2.91it/s, train/loss=18.00]
Epoch 0: | | 20/? [00:06<00:00, 2.91it/s, train/loss=1.770]
Epoch 0: | | 21/? [00:07<00:00, 2.71it/s, train/loss=1.770]
Epoch 0: | | 21/? [00:07<00:00, 2.69it/s, train/loss=1.730]
Epoch 0: | | 22/? [00:08<00:00, 2.72it/s, train/loss=1.730]
Epoch 0: | | 22/? [00:08<00:00, 2.70it/s, train/loss=3.860]
Epoch 0: | | 23/? [00:08<00:00, 2.80it/s, train/loss=3.860]
Epoch 0: | | 23/? [00:08<00:00, 2.80it/s, train/loss=17.50]
Epoch 0: | | 24/? [00:08<00:00, 2.79it/s, train/loss=17.50]
Epoch 0: | | 24/? [00:08<00:00, 2.79it/s, train/loss=2.070]
Epoch 0: | | 25/? [00:08<00:00, 2.89it/s, train/loss=2.070]
Epoch 0: | | 25/? [00:08<00:00, 2.89it/s, train/loss=17.30]
Epoch 0: | | 26/? [00:09<00:00, 2.88it/s, train/loss=17.30]
Epoch 0: | | 26/? [00:09<00:00, 2.88it/s, train/loss=1.730]
Epoch 0: | | 27/? [00:09<00:00, 2.97it/s, train/loss=1.730]
Epoch 0: | | 27/? [00:09<00:00, 2.97it/s, train/loss=17.00]
Epoch 0: | | 28/? [00:09<00:00, 2.96it/s, train/loss=17.00]
Epoch 0: | | 28/? [00:09<00:00, 2.96it/s, train/loss=2.510]
Epoch 0: | | 29/? [00:09<00:00, 3.05it/s, train/loss=2.510]
Epoch 0: | | 29/? [00:09<00:00, 3.05it/s, train/loss=16.80]
Epoch 0: | | 30/? [00:09<00:00, 3.03it/s, train/loss=16.80]
Epoch 0: | | 30/? [00:09<00:00, 3.03it/s, train/loss=3.290]
Epoch 0: | | 31/? [00:10<00:00, 2.87it/s, train/loss=3.290]
Epoch 0: | | 31/? [00:10<00:00, 2.86it/s, train/loss=2.080]
Epoch 0: | | 32/? [00:11<00:00, 2.88it/s, train/loss=2.080]
Epoch 0: | | 32/? [00:11<00:00, 2.86it/s, train/loss=0.979]
Epoch 0: | | 33/? [00:11<00:00, 2.94it/s, train/loss=0.979]
Epoch 0: | | 33/? [00:11<00:00, 2.94it/s, train/loss=16.30]
Epoch 0: | | 34/? [00:11<00:00, 2.93it/s, train/loss=16.30]
Epoch 0: | | 34/? [00:11<00:00, 2.93it/s, train/loss=1.400]
Epoch 0: | | 35/? [00:11<00:00, 3.00it/s, train/loss=1.400]
Epoch 0: | | 35/? [00:11<00:00, 3.00it/s, train/loss=16.10]
Epoch 0: | | 36/? [00:12<00:00, 2.99it/s, train/loss=16.10]
Epoch 0: | | 36/? [00:12<00:00, 2.99it/s, train/loss=2.130]
Epoch 0: | | 37/? [00:12<00:00, 3.06it/s, train/loss=2.130]
Epoch 0: | | 37/? [00:12<00:00, 3.05it/s, train/loss=15.80]
Epoch 0: | | 38/? [00:12<00:00, 3.04it/s, train/loss=15.80]
Epoch 0: | | 38/? [00:12<00:00, 3.04it/s, train/loss=2.690]
Epoch 0: | | 39/? [00:12<00:00, 3.11it/s, train/loss=2.690]
Epoch 0: | | 39/? [00:12<00:00, 3.11it/s, train/loss=15.60]
Epoch 0: | | 40/? [00:12<00:00, 3.09it/s, train/loss=15.60]
Epoch 0: | | 40/? [00:12<00:00, 3.09it/s, train/loss=0.976]
Epoch 0: | | 41/? [00:13<00:00, 2.97it/s, train/loss=0.976]
Epoch 0: | | 41/? [00:13<00:00, 2.95it/s, train/loss=1.850]
Epoch 0: | | 42/? [00:14<00:00, 2.97it/s, train/loss=1.850]
Epoch 0: | | 42/? [00:14<00:00, 2.95it/s, train/loss=0.784]
Epoch 0: | | 43/? [00:14<00:00, 3.01it/s, train/loss=0.784]
Epoch 0: | | 43/? [00:14<00:00, 3.01it/s, train/loss=15.20]
Epoch 0: | | 44/? [00:14<00:00, 3.00it/s, train/loss=15.20]
Epoch 0: | | 44/? [00:14<00:00, 3.00it/s, train/loss=1.540]
Epoch 0: | | 45/? [00:14<00:00, 3.06it/s, train/loss=1.540]
Epoch 0: | | 45/? [00:14<00:00, 3.06it/s, train/loss=15.00]
Epoch 0: | | 46/? [00:15<00:00, 3.04it/s, train/loss=15.00]
Epoch 0: | | 46/? [00:15<00:00, 3.04it/s, train/loss=1.380]
Epoch 0: | | 47/? [00:15<00:00, 3.10it/s, train/loss=1.380]
Epoch 0: | | 47/? [00:15<00:00, 3.10it/s, train/loss=14.80]
Epoch 0: | | 48/? [00:15<00:00, 3.09it/s, train/loss=14.80]
Epoch 0: | | 48/? [00:15<00:00, 3.09it/s, train/loss=2.230]
Epoch 0: | | 49/? [00:15<00:00, 3.14it/s, train/loss=2.230]
Epoch 0: | | 49/? [00:15<00:00, 3.14it/s, train/loss=14.50]
Epoch 0: | | 50/? [00:15<00:00, 3.13it/s, train/loss=14.50]
Epoch 0: | | 50/? [00:15<00:00, 3.13it/s, train/loss=3.040]
Epoch 0: | | 51/? [00:16<00:00, 3.02it/s, train/loss=3.040]
Epoch 0: | | 51/? [00:16<00:00, 3.01it/s, train/loss=0.739]
Epoch 0: | | 52/? [00:17<00:00, 3.02it/s, train/loss=0.739]
Epoch 0: | | 52/? [00:17<00:00, 3.01it/s, train/loss=3.670]
Epoch 0: | | 53/? [00:17<00:00, 3.06it/s, train/loss=3.670]
Epoch 0: | | 53/? [00:17<00:00, 3.06it/s, train/loss=14.20]
Epoch 0: | | 54/? [00:17<00:00, 3.05it/s, train/loss=14.20]
Epoch 0: | | 54/? [00:17<00:00, 3.05it/s, train/loss=1.620]
Epoch 0: | | 55/? [00:17<00:00, 3.10it/s, train/loss=1.620]
Epoch 0: | | 55/? [00:17<00:00, 3.10it/s, train/loss=14.00]
Epoch 0: | | 56/? [00:18<00:00, 3.08it/s, train/loss=14.00]
Epoch 0: | | 56/? [00:18<00:00, 3.08it/s, train/loss=2.510]
Epoch 0: | | 57/? [00:18<00:00, 3.13it/s, train/loss=2.510]
Epoch 0: | | 57/? [00:18<00:00, 3.13it/s, train/loss=13.80]
Epoch 0: | | 58/? [00:18<00:00, 3.12it/s, train/loss=13.80]
Epoch 0: | | 58/? [00:18<00:00, 3.12it/s, train/loss=3.540]
Epoch 0: | | 59/? [00:18<00:00, 3.16it/s, train/loss=3.540]
Epoch 0: | | 59/? [00:18<00:00, 3.16it/s, train/loss=13.60]
Epoch 0: | | 60/? [00:19<00:00, 3.15it/s, train/loss=13.60]
Epoch 0: | | 60/? [00:19<00:00, 3.15it/s, train/loss=3.700]
Epoch 0: | | 61/? [00:19<00:00, 3.06it/s, train/loss=3.700]
Epoch 0: | | 61/? [00:19<00:00, 3.05it/s, train/loss=0.619]
Epoch 0: | | 62/? [00:20<00:00, 3.06it/s, train/loss=0.619]
Epoch 0: | | 62/? [00:20<00:00, 3.05it/s, train/loss=2.010]
Epoch 0: | | 63/? [00:20<00:00, 3.09it/s, train/loss=2.010]
Epoch 0: | | 63/? [00:20<00:00, 3.09it/s, train/loss=13.30]
Epoch 0: | | 64/? [00:20<00:00, 3.08it/s, train/loss=13.30]
Epoch 0: | | 64/? [00:20<00:00, 3.08it/s, train/loss=1.010]
Epoch 0: | | 65/? [00:20<00:00, 3.12it/s, train/loss=1.010]
Epoch 0: | | 65/? [00:20<00:00, 3.12it/s, train/loss=13.10]
Epoch 0: | | 66/? [00:21<00:00, 3.11it/s, train/loss=13.10]
Epoch 0: | | 66/? [00:21<00:00, 3.11it/s, train/loss=3.870]
Epoch 0: | | 67/? [00:21<00:00, 3.15it/s, train/loss=3.870]
Epoch 0: | | 67/? [00:21<00:00, 3.15it/s, train/loss=12.90]
Epoch 0: | | 68/? [00:21<00:00, 3.14it/s, train/loss=12.90]
Epoch 0: | | 68/? [00:21<00:00, 3.14it/s, train/loss=2.660]
Epoch 0: | | 69/? [00:21<00:00, 3.17it/s, train/loss=2.660]
Epoch 0: | | 69/? [00:21<00:00, 3.17it/s, train/loss=12.70]
Epoch 0: | | 70/? [00:22<00:00, 3.16it/s, train/loss=12.70]
Epoch 0: | | 70/? [00:22<00:00, 3.16it/s, train/loss=3.440]
Epoch 0: | | 71/? [00:23<00:00, 3.09it/s, train/loss=3.440]
Epoch 0: | | 71/? [00:23<00:00, 3.08it/s, train/loss=0.751]
Epoch 0: | | 72/? [00:23<00:00, 3.09it/s, train/loss=0.751]
Epoch 0: | | 72/? [00:23<00:00, 3.08it/s, train/loss=2.930]
Epoch 0: | | 73/? [00:23<00:00, 3.11it/s, train/loss=2.930]
Epoch 0: | | 73/? [00:23<00:00, 3.11it/s, train/loss=12.40]
Epoch 0: | | 74/? [00:23<00:00, 3.10it/s, train/loss=12.40]
Epoch 0: | | 74/? [00:23<00:00, 3.10it/s, train/loss=2.180]
Epoch 0: | | 75/? [00:23<00:00, 3.14it/s, train/loss=2.180]
Epoch 0: | | 75/? [00:23<00:00, 3.14it/s, train/loss=12.20]
Epoch 0: | | 76/? [00:24<00:00, 3.13it/s, train/loss=12.20]
Epoch 0: | | 76/? [00:24<00:00, 3.13it/s, train/loss=2.370]
Epoch 0: | | 77/? [00:24<00:00, 3.17it/s, train/loss=2.370]
Epoch 0: | | 77/? [00:24<00:00, 3.17it/s, train/loss=12.00]
Epoch 0: | | 78/? [00:24<00:00, 3.16it/s, train/loss=12.00]
Epoch 0: | | 78/? [00:24<00:00, 3.16it/s, train/loss=2.250]
Epoch 0: | | 79/? [00:24<00:00, 3.19it/s, train/loss=2.250]
Epoch 0: | | 79/? [00:24<00:00, 3.19it/s, train/loss=11.80]
Epoch 0: | | 80/? [00:25<00:00, 3.18it/s, train/loss=11.80]
Epoch 0: | | 80/? [00:25<00:00, 3.18it/s, train/loss=2.530]
Epoch 0: | | 81/? [00:26<00:00, 3.11it/s, train/loss=2.530]
Epoch 0: | | 81/? [00:26<00:00, 3.10it/s, train/loss=2.030]
Epoch 0: | | 82/? [00:26<00:00, 3.11it/s, train/loss=2.030]
Epoch 0: | | 82/? [00:26<00:00, 3.10it/s, train/loss=0.990]
Epoch 0: | | 83/? [00:26<00:00, 3.14it/s, train/loss=0.990]
Epoch 0: | | 83/? [00:26<00:00, 3.13it/s, train/loss=11.50]
Epoch 0: | | 84/? [00:26<00:00, 3.13it/s, train/loss=11.50]
Epoch 0: | | 84/? [00:26<00:00, 3.13it/s, train/loss=2.540]
Epoch 0: | | 85/? [00:26<00:00, 3.16it/s, train/loss=2.540]
Epoch 0: | | 85/? [00:26<00:00, 3.16it/s, train/loss=11.40]
Epoch 0: | | 86/? [00:27<00:00, 3.15it/s, train/loss=11.40]
Epoch 0: | | 86/? [00:27<00:00, 3.15it/s, train/loss=2.830]
Epoch 0: | | 87/? [00:27<00:00, 3.18it/s, train/loss=2.830]
Epoch 0: | | 87/? [00:27<00:00, 3.18it/s, train/loss=11.20]
Epoch 0: | | 88/? [00:27<00:00, 3.17it/s, train/loss=11.20]
Epoch 0: | | 88/? [00:27<00:00, 3.17it/s, train/loss=1.430]
Epoch 0: | | 89/? [00:27<00:00, 3.20it/s, train/loss=1.430]
Epoch 0: | | 89/? [00:27<00:00, 3.20it/s, train/loss=11.10]
Epoch 0: | | 90/? [00:28<00:00, 3.19it/s, train/loss=11.10]
Epoch 0: | | 90/? [00:28<00:00, 3.19it/s, train/loss=1.880]
Epoch 0: | | 91/? [00:29<00:00, 3.13it/s, train/loss=1.880]
Epoch 0: | | 91/? [00:29<00:00, 3.12it/s, train/loss=1.450]
Epoch 0: | | 92/? [00:29<00:00, 3.13it/s, train/loss=1.450]
Epoch 0: | | 92/? [00:29<00:00, 3.12it/s, train/loss=1.310]
Epoch 0: | | 93/? [00:29<00:00, 3.15it/s, train/loss=1.310]
Epoch 0: | | 93/? [00:29<00:00, 3.15it/s, train/loss=10.80]
Epoch 0: | | 94/? [00:29<00:00, 3.14it/s, train/loss=10.80]
Epoch 0: | | 94/? [00:29<00:00, 3.14it/s, train/loss=0.665]
Epoch 0: | | 95/? [00:29<00:00, 3.17it/s, train/loss=0.665]
Epoch 0: | | 95/? [00:29<00:00, 3.17it/s, train/loss=10.70]
Epoch 0: | | 96/? [00:30<00:00, 3.16it/s, train/loss=10.70]
Epoch 0: | | 96/? [00:30<00:00, 3.16it/s, train/loss=2.050]
Epoch 0: | | 97/? [00:30<00:00, 3.19it/s, train/loss=2.050]
Epoch 0: | | 97/? [00:30<00:00, 3.19it/s, train/loss=10.50]
Epoch 0: | | 98/? [00:30<00:00, 3.18it/s, train/loss=10.50]
Epoch 0: | | 98/? [00:30<00:00, 3.18it/s, train/loss=2.290]
Epoch 0: | | 99/? [00:30<00:00, 3.21it/s, train/loss=2.290]
Epoch 0: | | 99/? [00:30<00:00, 3.21it/s, train/loss=10.40]
Epoch 0: | | 100/? [00:31<00:00, 3.20it/s, train/loss=10.40]
Epoch 0: | | 100/? [00:31<00:00, 3.20it/s, train/loss=1.910]
Epoch 0: | | 101/? [00:32<00:00, 3.15it/s, train/loss=1.910]
Epoch 0: | | 101/? [00:32<00:00, 3.14it/s, train/loss=1.090]
Epoch 0: | | 102/? [00:32<00:00, 3.15it/s, train/loss=1.090]
Epoch 0: | | 102/? [00:32<00:00, 3.14it/s, train/loss=2.970]
Epoch 0: | | 103/? [00:32<00:00, 3.17it/s, train/loss=2.970]
Epoch 0: | | 103/? [00:32<00:00, 3.17it/s, train/loss=10.10]
Epoch 0: | | 104/? [00:32<00:00, 3.16it/s, train/loss=10.10]
Epoch 0: | | 104/? [00:32<00:00, 3.16it/s, train/loss=2.400]
Epoch 0: | | 105/? [00:32<00:00, 3.18it/s, train/loss=2.400]
Epoch 0: | | 105/? [00:32<00:00, 3.18it/s, train/loss=10.00]
Epoch 0: | | 106/? [00:33<00:00, 3.18it/s, train/loss=10.00]
Epoch 0: | | 106/? [00:33<00:00, 3.18it/s, train/loss=2.730]
Epoch 0: | | 107/? [00:33<00:00, 3.20it/s, train/loss=2.730]
Epoch 0: | | 107/? [00:33<00:00, 3.20it/s, train/loss=9.900]
Epoch 0: | | 108/? [00:33<00:00, 3.20it/s, train/loss=9.900]
Epoch 0: | | 108/? [00:33<00:00, 3.20it/s, train/loss=2.430]
Epoch 0: | | 109/? [00:33<00:00, 3.22it/s, train/loss=2.430]
Epoch 0: | | 109/? [00:33<00:00, 3.22it/s, train/loss=9.770]
Epoch 0: | | 110/? [00:34<00:00, 3.21it/s, train/loss=9.770]
Epoch 0: | | 110/? [00:34<00:00, 3.21it/s, train/loss=1.070]
Epoch 0: | | 111/? [00:35<00:00, 3.16it/s, train/loss=1.070]
Epoch 0: | | 111/? [00:35<00:00, 3.15it/s, train/loss=2.210]
Epoch 0: | | 112/? [00:35<00:00, 3.16it/s, train/loss=2.210]
Epoch 0: | | 112/? [00:35<00:00, 3.15it/s, train/loss=0.631]
Epoch 0: | | 113/? [00:35<00:00, 3.18it/s, train/loss=0.631]
Epoch 0: | | 113/? [00:35<00:00, 3.18it/s, train/loss=9.550]
Epoch 0: | | 114/? [00:35<00:00, 3.17it/s, train/loss=9.550]
Epoch 0: | | 114/? [00:35<00:00, 3.17it/s, train/loss=1.270]
Epoch 0: | | 115/? [00:36<00:00, 3.19it/s, train/loss=1.270]
Epoch 0: | | 115/? [00:36<00:00, 3.19it/s, train/loss=9.450]
Epoch 0: | | 116/? [00:36<00:00, 3.19it/s, train/loss=9.450]
Epoch 0: | | 116/? [00:36<00:00, 3.19it/s, train/loss=1.790]
Epoch 0: | | 117/? [00:36<00:00, 3.21it/s, train/loss=1.790]
Epoch 0: | | 117/? [00:36<00:00, 3.21it/s, train/loss=9.340]
Epoch 0: | | 118/? [00:36<00:00, 3.20it/s, train/loss=9.340]
Epoch 0: | | 118/? [00:36<00:00, 3.20it/s, train/loss=2.310]
Epoch 0: | | 119/? [00:36<00:00, 3.23it/s, train/loss=2.310]
Epoch 0: | | 119/? [00:36<00:00, 3.23it/s, train/loss=9.220]
Epoch 0: | | 120/? [00:37<00:00, 3.22it/s, train/loss=9.220]
Epoch 0: | | 120/? [00:37<00:00, 3.22it/s, train/loss=2.210]
Epoch 0: | | 121/? [00:38<00:00, 3.17it/s, train/loss=2.210]
Epoch 0: | | 121/? [00:38<00:00, 3.17it/s, train/loss=6.350]
Epoch 0: | | 122/? [00:38<00:00, 3.17it/s, train/loss=6.350]
Epoch 0: | | 122/? [00:38<00:00, 3.16it/s, train/loss=2.140]
Epoch 0: | | 123/? [00:38<00:00, 3.19it/s, train/loss=2.140]
Epoch 0: | | 123/? [00:38<00:00, 3.19it/s, train/loss=9.020]
Epoch 0: | | 124/? [00:38<00:00, 3.18it/s, train/loss=9.020]
Epoch 0: | | 124/? [00:38<00:00, 3.18it/s, train/loss=2.490]
Epoch 0: | | 125/? [00:39<00:00, 3.20it/s, train/loss=2.490]
Epoch 0: | | 125/? [00:39<00:00, 3.20it/s, train/loss=8.930]
Epoch 0: | | 126/? [00:39<00:00, 3.20it/s, train/loss=8.930]
Epoch 0: | | 126/? [00:39<00:00, 3.20it/s, train/loss=0.836]
Epoch 0: | | 127/? [00:39<00:00, 3.22it/s, train/loss=0.836]
Epoch 0: | | 127/? [00:39<00:00, 3.22it/s, train/loss=8.830]
Epoch 0: | | 128/? [00:39<00:00, 3.21it/s, train/loss=8.830]
Epoch 0: | | 128/? [00:39<00:00, 3.21it/s, train/loss=1.060]
Epoch 0: | | 129/? [00:39<00:00, 3.23it/s, train/loss=1.060]
Epoch 0: | | 129/? [00:39<00:00, 3.23it/s, train/loss=8.730]
Epoch 0: | | 130/? [00:40<00:00, 3.23it/s, train/loss=8.730]
Epoch 0: | | 130/? [00:40<00:00, 3.23it/s, train/loss=2.120]
Epoch 0: | | 131/? [00:41<00:00, 3.18it/s, train/loss=2.120]
Epoch 0: | | 131/? [00:41<00:00, 3.18it/s, train/loss=4.420]
Epoch 0: | | 132/? [00:41<00:00, 3.18it/s, train/loss=4.420]
Epoch 0: | | 132/? [00:41<00:00, 3.17it/s, train/loss=2.920]
Epoch 0: | | 133/? [00:41<00:00, 3.19it/s, train/loss=2.920]
Epoch 0: | | 133/? [00:41<00:00, 3.19it/s, train/loss=8.560]
Epoch 0: | | 134/? [00:42<00:00, 3.19it/s, train/loss=8.560]
Epoch 0: | | 134/? [00:42<00:00, 3.19it/s, train/loss=1.740]
Epoch 0: | | 135/? [00:42<00:00, 3.21it/s, train/loss=1.740]
Epoch 0: | | 135/? [00:42<00:00, 3.21it/s, train/loss=8.480]
Epoch 0: | | 136/? [00:42<00:00, 3.20it/s, train/loss=8.480]
Epoch 0: | | 136/? [00:42<00:00, 3.20it/s, train/loss=5.630]
Epoch 0: | | 137/? [00:42<00:00, 3.22it/s, train/loss=5.630]
Epoch 0: | | 137/? [00:42<00:00, 3.22it/s, train/loss=8.390]
Epoch 0: | | 138/? [00:42<00:00, 3.22it/s, train/loss=8.390]
Epoch 0: | | 138/? [00:42<00:00, 3.22it/s, train/loss=2.640]
Epoch 0: | | 139/? [00:42<00:00, 3.24it/s, train/loss=2.640]
Epoch 0: | | 139/? [00:42<00:00, 3.24it/s, train/loss=8.310]
Epoch 0: | | 140/? [00:43<00:00, 3.23it/s, train/loss=8.310]
Epoch 0: | | 140/? [00:43<00:00, 3.23it/s, train/loss=1.650]
Epoch 0: | | 141/? [00:44<00:00, 3.19it/s, train/loss=1.650]
Epoch 0: | | 141/? [00:44<00:00, 3.18it/s, train/loss=1.890]
Epoch 0: | | 142/? [00:44<00:00, 3.19it/s, train/loss=1.890]
Epoch 0: | | 142/? [00:44<00:00, 3.18it/s, train/loss=1.700]
Epoch 0: | | 143/? [00:44<00:00, 3.20it/s, train/loss=1.700]
Epoch 0: | | 143/? [00:44<00:00, 3.20it/s, train/loss=8.180]
Epoch 0: | | 144/? [00:45<00:00, 3.20it/s, train/loss=8.180]
Epoch 0: | | 144/? [00:45<00:00, 3.20it/s, train/loss=2.450]
Epoch 0: | | 145/? [00:45<00:00, 3.21it/s, train/loss=2.450]
Epoch 0: | | 145/? [00:45<00:00, 3.21it/s, train/loss=8.110]
Epoch 0: | | 146/? [00:45<00:00, 3.21it/s, train/loss=8.110]
Epoch 0: | | 146/? [00:45<00:00, 3.21it/s, train/loss=1.610]
Epoch 0: | | 147/? [00:45<00:00, 3.22it/s, train/loss=1.610]
Epoch 0: | | 147/? [00:45<00:00, 3.22it/s, train/loss=8.040]
Epoch 0: | | 148/? [00:45<00:00, 3.22it/s, train/loss=8.040]
Epoch 0: | | 148/? [00:45<00:00, 3.22it/s, train/loss=2.790]
Epoch 0: | | 149/? [00:46<00:00, 3.24it/s, train/loss=2.790]
Epoch 0: | | 149/? [00:46<00:00, 3.23it/s, train/loss=7.960]
Epoch 0: | | 150/? [00:46<00:00, 3.23it/s, train/loss=7.960]
Epoch 0: | | 150/? [00:46<00:00, 3.23it/s, train/loss=2.020]
Epoch 0: | | 151/? [00:47<00:00, 3.19it/s, train/loss=2.020]
Epoch 0: | | 151/? [00:47<00:00, 3.19it/s, train/loss=1.330]
Epoch 0: | | 152/? [00:47<00:00, 3.18it/s, train/loss=1.330]
Epoch 0: | | 152/? [00:47<00:00, 3.18it/s, train/loss=2.790]
Epoch 0: | | 153/? [00:47<00:00, 3.20it/s, train/loss=2.790]
Epoch 0: | | 153/? [00:47<00:00, 3.20it/s, train/loss=7.830]
Epoch 0: | | 154/? [00:48<00:00, 3.19it/s, train/loss=7.830]
Epoch 0: | | 154/? [00:48<00:00, 3.19it/s, train/loss=3.220]
Epoch 0: | | 155/? [00:48<00:00, 3.21it/s, train/loss=3.220]
Epoch 0: | | 155/? [00:48<00:00, 3.21it/s, train/loss=7.760]
Epoch 0: | | 156/? [00:48<00:00, 3.20it/s, train/loss=7.760]
Epoch 0: | | 156/? [00:48<00:00, 3.20it/s, train/loss=2.120]
Epoch 0: | | 157/? [00:48<00:00, 3.22it/s, train/loss=2.120]
Epoch 0: | | 157/? [00:48<00:00, 3.22it/s, train/loss=7.700]
Epoch 0: | | 158/? [00:49<00:00, 3.20it/s, train/loss=7.700]
Epoch 0: | | 158/? [00:49<00:00, 3.20it/s, train/loss=1.940]
Epoch 0: | | 159/? [00:49<00:00, 3.21it/s, train/loss=1.940]
Epoch 0: | | 159/? [00:49<00:00, 3.21it/s, train/loss=7.640]
Epoch 0: | | 160/? [00:49<00:00, 3.20it/s, train/loss=7.640]
Epoch 0: | | 160/? [00:49<00:00, 3.20it/s, train/loss=1.960]
Epoch 0: | | 161/? [00:51<00:00, 3.15it/s, train/loss=1.960]
Epoch 0: | | 161/? [00:51<00:00, 3.15it/s, train/loss=0.607]
Epoch 0: | | 162/? [00:51<00:00, 3.14it/s, train/loss=0.607]
Epoch 0: | | 162/? [00:51<00:00, 3.14it/s, train/loss=0.631]
Epoch 0: | | 163/? [00:51<00:00, 3.15it/s, train/loss=0.631]
Epoch 0: | | 163/? [00:51<00:00, 3.15it/s, train/loss=7.540]
Epoch 0: | | 164/? [00:52<00:00, 3.14it/s, train/loss=7.540]
Epoch 0: | | 164/? [00:52<00:00, 3.14it/s, train/loss=2.620]
Epoch 0: | | 165/? [00:52<00:00, 3.15it/s, train/loss=2.620]
Epoch 0: | | 165/? [00:52<00:00, 3.15it/s, train/loss=7.500]
Epoch 0: | | 166/? [00:52<00:00, 3.15it/s, train/loss=7.500]
Epoch 0: | | 166/? [00:52<00:00, 3.15it/s, train/loss=2.730]
Epoch 0: | | 167/? [00:52<00:00, 3.16it/s, train/loss=2.730]
Epoch 0: | | 167/? [00:52<00:00, 3.16it/s, train/loss=7.450]
Epoch 0: | | 168/? [00:53<00:00, 3.16it/s, train/loss=7.450]
Epoch 0: | | 168/? [00:53<00:00, 3.16it/s, train/loss=1.880]
Epoch 0: | | 169/? [00:53<00:00, 3.17it/s, train/loss=1.880]
Epoch 0: | | 169/? [00:53<00:00, 3.17it/s, train/loss=7.390]
Epoch 0: | | 170/? [00:53<00:00, 3.17it/s, train/loss=7.390]
Epoch 0: | | 170/? [00:53<00:00, 3.17it/s, train/loss=1.330]
Epoch 0: | | 171/? [00:54<00:00, 3.13it/s, train/loss=1.330]
Epoch 0: | | 171/? [00:54<00:00, 3.13it/s, train/loss=1.980]
Epoch 0: | | 172/? [00:54<00:00, 3.13it/s, train/loss=1.980]
Epoch 0: | | 172/? [00:54<00:00, 3.13it/s, train/loss=0.843]
Epoch 0: | | 173/? [00:55<00:00, 3.14it/s, train/loss=0.843]
Epoch 0: | | 173/? [00:55<00:00, 3.14it/s, train/loss=7.300]
Epoch 0: | | 174/? [00:55<00:00, 3.14it/s, train/loss=7.300]
Epoch 0: | | 174/? [00:55<00:00, 3.14it/s, train/loss=3.970]
Epoch 0: | | 175/? [00:55<00:00, 3.15it/s, train/loss=3.970]
Epoch 0: | | 175/? [00:55<00:00, 3.15it/s, train/loss=7.240]
Epoch 0: | | 176/? [00:55<00:00, 3.15it/s, train/loss=7.240]
Epoch 0: | | 176/? [00:55<00:00, 3.15it/s, train/loss=1.490]
Epoch 0: | | 177/? [00:55<00:00, 3.16it/s, train/loss=1.490]
Epoch 0: | | 177/? [00:55<00:00, 3.16it/s, train/loss=7.180]
Epoch 0: | | 178/? [00:56<00:00, 3.16it/s, train/loss=7.180]
Epoch 0: | | 178/? [00:56<00:00, 3.16it/s, train/loss=2.410]
Epoch 0: | | 179/? [00:56<00:00, 3.18it/s, train/loss=2.410]
Epoch 0: | | 179/? [00:56<00:00, 3.18it/s, train/loss=7.130]
Epoch 0: | | 180/? [00:56<00:00, 3.17it/s, train/loss=7.130]
Epoch 0: | | 180/? [00:56<00:00, 3.17it/s, train/loss=4.450]
Epoch 0: | | 181/? [00:57<00:00, 3.14it/s, train/loss=4.450]
Epoch 0: | | 181/? [00:57<00:00, 3.13it/s, train/loss=2.640]
Epoch 0: | | 182/? [00:58<00:00, 3.13it/s, train/loss=2.640]
Epoch 0: | | 182/? [00:58<00:00, 3.12it/s, train/loss=1.290]
Epoch 0: | | 183/? [00:58<00:00, 3.13it/s, train/loss=1.290]
Epoch 0: | | 183/? [00:58<00:00, 3.13it/s, train/loss=7.040]
Epoch 0: | | 184/? [00:58<00:00, 3.12it/s, train/loss=7.040]
Epoch 0: | | 184/? [00:58<00:00, 3.12it/s, train/loss=1.280]
Epoch 0: | | 185/? [00:58<00:00, 3.14it/s, train/loss=1.280]
Epoch 0: | | 185/? [00:58<00:00, 3.14it/s, train/loss=6.990]
Epoch 0: | | 186/? [00:59<00:00, 3.14it/s, train/loss=6.990]
Epoch 0: | | 186/? [00:59<00:00, 3.14it/s, train/loss=1.760]
Epoch 0: | | 187/? [00:59<00:00, 3.15it/s, train/loss=1.760]
Epoch 0: | | 187/? [00:59<00:00, 3.15it/s, train/loss=6.940]
Epoch 0: | | 188/? [00:59<00:00, 3.15it/s, train/loss=6.940]
Epoch 0: | | 188/? [00:59<00:00, 3.15it/s, train/loss=1.270]
Epoch 0: | | 189/? [00:59<00:00, 3.16it/s, train/loss=1.270]
Epoch 0: | | 189/? [00:59<00:00, 3.16it/s, train/loss=6.890]
Epoch 0: | | 190/? [01:00<00:00, 3.16it/s, train/loss=6.890]
Epoch 0: | | 190/? [01:00<00:00, 3.16it/s, train/loss=0.835]
Epoch 0: | | 191/? [01:01<00:00, 3.12it/s, train/loss=0.835]
Epoch 0: | | 191/? [01:01<00:00, 3.12it/s, train/loss=1.100]
Epoch 0: | | 192/? [01:01<00:00, 3.12it/s, train/loss=1.100]
Epoch 0: | | 192/? [01:01<00:00, 3.12it/s, train/loss=1.180]
Epoch 0: | | 193/? [01:01<00:00, 3.13it/s, train/loss=1.180]
Epoch 0: | | 193/? [01:01<00:00, 3.13it/s, train/loss=6.810]
Epoch 0: | | 194/? [01:01<00:00, 3.13it/s, train/loss=6.810]
Epoch 0: | | 194/? [01:01<00:00, 3.13it/s, train/loss=3.430]
Epoch 0: | | 195/? [01:02<00:00, 3.14it/s, train/loss=3.430]
Epoch 0: | | 195/? [01:02<00:00, 3.14it/s, train/loss=6.770]
Epoch 0: | | 196/? [01:02<00:00, 3.14it/s, train/loss=6.770]
Epoch 0: | | 196/? [01:02<00:00, 3.14it/s, train/loss=2.480]
Epoch 0: | | 197/? [01:02<00:00, 3.15it/s, train/loss=2.480]
Epoch 0: | | 197/? [01:02<00:00, 3.15it/s, train/loss=6.720]
Epoch 0: | | 198/? [01:02<00:00, 3.15it/s, train/loss=6.720]
Epoch 0: | | 198/? [01:02<00:00, 3.15it/s, train/loss=1.160]
Epoch 0: | | 199/? [01:02<00:00, 3.16it/s, train/loss=1.160]
Epoch 0: | | 199/? [01:02<00:00, 3.16it/s, train/loss=6.670]
Epoch 0: | | 200/? [01:03<00:00, 3.16it/s, train/loss=6.670]
Epoch 0: | | 200/? [01:03<00:00, 3.16it/s, train/loss=2.950]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:04, 9.34it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:04, 8.52it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:04, 8.71it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:04, 8.76it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:03, 8.88it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:03, 8.96it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:03, 9.00it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:03, 9.05it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:03, 9.06it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:01<00:03, 9.09it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:01<00:03, 9.10it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:03, 9.12it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:02, 9.15it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 9.18it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 9.17it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 9.17it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:02, 9.16it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:01<00:02, 9.18it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:02<00:02, 9.19it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:02<00:02, 9.21it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:02<00:02, 9.23it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:02<00:01, 9.23it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:02<00:01, 9.25it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 9.26it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 9.26it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 9.27it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 9.28it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:03<00:01, 9.30it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:03<00:01, 9.33it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:03<00:01, 9.33it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:03<00:00, 9.35it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:03<00:00, 9.35it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:03<00:00, 9.37it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:03<00:00, 9.37it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 9.38it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:03<00:00, 9.38it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:03<00:00, 9.36it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:04<00:00, 9.35it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:04<00:00, 9.35it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00, 9.35it/s][A
[A
Epoch 0: | | 200/? [01:12<00:00, 2.76it/s, train/loss=2.950]
Epoch 0: | | 201/? [01:20<00:00, 2.51it/s, train/loss=2.950]
Epoch 0: | | 201/? [01:20<00:00, 2.51it/s, train/loss=1.330]
Epoch 0: | | 202/? [01:20<00:00, 2.51it/s, train/loss=1.330]
Epoch 0: | | 202/? [01:20<00:00, 2.51it/s, train/loss=0.757]
Epoch 0: | | 203/? [01:20<00:00, 2.52it/s, train/loss=0.757]
Epoch 0: | | 203/? [01:20<00:00, 2.52it/s, train/loss=6.590]
Epoch 0: | | 204/? [01:20<00:00, 2.52it/s, train/loss=6.590]
Epoch 0: | | 204/? [01:20<00:00, 2.52it/s, train/loss=1.360]
Epoch 0: | | 205/? [01:20<00:00, 2.53it/s, train/loss=1.360]
Epoch 0: | | 205/? [01:20<00:00, 2.53it/s, train/loss=6.550]
Epoch 0: | | 206/? [01:21<00:00, 2.53it/s, train/loss=6.550]
Epoch 0: | | 206/? [01:21<00:00, 2.53it/s, train/loss=3.090]
Epoch 0: | | 207/? [01:21<00:00, 2.55it/s, train/loss=3.090]
Epoch 0: | | 207/? [01:21<00:00, 2.55it/s, train/loss=6.500]
Epoch 0: | | 208/? [01:21<00:00, 2.55it/s, train/loss=6.500]
Epoch 0: | | 208/? [01:21<00:00, 2.55it/s, train/loss=3.700]
Epoch 0: | | 209/? [01:21<00:00, 2.56it/s, train/loss=3.700]
Epoch 0: | | 209/? [01:21<00:00, 2.56it/s, train/loss=6.450]
Epoch 0: | | 210/? [01:22<00:00, 2.56it/s, train/loss=6.450]
Epoch 0: | | 210/? [01:22<00:00, 2.56it/s, train/loss=2.180]
Epoch 0: | | 211/? [01:23<00:00, 2.54it/s, train/loss=2.180]
Epoch 0: | | 211/? [01:23<00:00, 2.54it/s, train/loss=2.080]
Epoch 0: | | 212/? [01:23<00:00, 2.54it/s, train/loss=2.080]
Epoch 0: | | 212/? [01:23<00:00, 2.54it/s, train/loss=1.330]
Epoch 0: | | 213/? [01:23<00:00, 2.55it/s, train/loss=1.330]
Epoch 0: | | 213/? [01:23<00:00, 2.55it/s, train/loss=6.370]
Epoch 0: | | 214/? [01:23<00:00, 2.55it/s, train/loss=6.370]
Epoch 0: | | 214/? [01:23<00:00, 2.55it/s, train/loss=6.390]
Epoch 0: | | 215/? [01:23<00:00, 2.56it/s, train/loss=6.390]
Epoch 0: | | 215/? [01:23<00:00, 2.56it/s, train/loss=6.320]
Epoch 0: | | 216/? [01:24<00:00, 2.56it/s, train/loss=6.320]
Epoch 0: | | 216/? [01:24<00:00, 2.56it/s, train/loss=2.420]
Epoch 0: | | 217/? [01:24<00:00, 2.57it/s, train/loss=2.420]
Epoch 0: | | 217/? [01:24<00:00, 2.57it/s, train/loss=6.280]
Epoch 0: | | 218/? [01:24<00:00, 2.57it/s, train/loss=6.280]
Epoch 0: | | 218/? [01:24<00:00, 2.57it/s, train/loss=0.810]
Epoch 0: | | 219/? [01:24<00:00, 2.58it/s, train/loss=0.810]
Epoch 0: | | 219/? [01:24<00:00, 2.58it/s, train/loss=6.250]
Epoch 0: | | 220/? [01:25<00:00, 2.58it/s, train/loss=6.250]
Epoch 0: | | 220/? [01:25<00:00, 2.58it/s, train/loss=2.580]
Epoch 0: | | 221/? [01:26<00:00, 2.57it/s, train/loss=2.580]
Epoch 0: | | 221/? [01:26<00:00, 2.56it/s, train/loss=1.950]
Epoch 0: | | 222/? [01:26<00:00, 2.57it/s, train/loss=1.950]
Epoch 0: | | 222/? [01:26<00:00, 2.57it/s, train/loss=2.630]
Epoch 0: | | 223/? [01:26<00:00, 2.58it/s, train/loss=2.630]
Epoch 0: | | 223/? [01:26<00:00, 2.58it/s, train/loss=6.190]
Epoch 0: | | 224/? [01:26<00:00, 2.58it/s, train/loss=6.190]
Epoch 0: | | 224/? [01:26<00:00, 2.58it/s, train/loss=1.390]
Epoch 0: | | 225/? [01:27<00:00, 2.59it/s, train/loss=1.390]
Epoch 0: | | 225/? [01:27<00:00, 2.59it/s, train/loss=6.140]
Epoch 0: | | 226/? [01:27<00:00, 2.59it/s, train/loss=6.140]
Epoch 0: | | 226/? [01:27<00:00, 2.59it/s, train/loss=1.380]
Epoch 0: | | 227/? [01:27<00:00, 2.60it/s, train/loss=1.380]
Epoch 0: | | 227/? [01:27<00:00, 2.60it/s, train/loss=6.100]
Epoch 0: | | 228/? [01:27<00:00, 2.60it/s, train/loss=6.100]
Epoch 0: | | 228/? [01:27<00:00, 2.60it/s, train/loss=3.490]
Epoch 0: | | 229/? [01:27<00:00, 2.61it/s, train/loss=3.490]
Epoch 0: | | 229/? [01:27<00:00, 2.61it/s, train/loss=6.060]
Epoch 0: | | 230/? [01:28<00:00, 2.61it/s, train/loss=6.060]
Epoch 0: | | 230/? [01:28<00:00, 2.61it/s, train/loss=1.660]
Epoch 0: | | 231/? [01:29<00:00, 2.59it/s, train/loss=1.660]
Epoch 0: | | 231/? [01:29<00:00, 2.59it/s, train/loss=1.780]
Epoch 0: | | 232/? [01:29<00:00, 2.59it/s, train/loss=1.780]
Epoch 0: | | 232/? [01:29<00:00, 2.59it/s, train/loss=1.100]
Epoch 0: | | 233/? [01:29<00:00, 2.60it/s, train/loss=1.100]
Epoch 0: | | 233/? [01:29<00:00, 2.60it/s, train/loss=6.010]
Epoch 0: | | 234/? [01:30<00:00, 2.60it/s, train/loss=6.010]
Epoch 0: | | 234/? [01:30<00:00, 2.60it/s, train/loss=2.180]
Epoch 0: | | 235/? [01:30<00:00, 2.61it/s, train/loss=2.180]
Epoch 0: | | 235/? [01:30<00:00, 2.61it/s, train/loss=5.970]
Epoch 0: | | 236/? [01:30<00:00, 2.61it/s, train/loss=5.970]
Epoch 0: | | 236/? [01:30<00:00, 2.61it/s, train/loss=2.190]
Epoch 0: | | 237/? [01:30<00:00, 2.62it/s, train/loss=2.190]
Epoch 0: | | 237/? [01:30<00:00, 2.62it/s, train/loss=5.920]
Epoch 0: | | 238/? [01:30<00:00, 2.62it/s, train/loss=5.920]
Epoch 0: | | 238/? [01:30<00:00, 2.62it/s, train/loss=2.410]
Epoch 0: | | 239/? [01:30<00:00, 2.63it/s, train/loss=2.410]
Epoch 0: | | 239/? [01:30<00:00, 2.63it/s, train/loss=5.900]
Epoch 0: | | 240/? [01:31<00:00, 2.63it/s, train/loss=5.900]
Epoch 0: | | 240/? [01:31<00:00, 2.63it/s, train/loss=3.740]
Epoch 0: | | 241/? [01:32<00:00, 2.61it/s, train/loss=3.740]
Epoch 0: | | 241/? [01:32<00:00, 2.61it/s, train/loss=0.724]
Epoch 0: | | 242/? [01:32<00:00, 2.61it/s, train/loss=0.724]
Epoch 0: | | 242/? [01:32<00:00, 2.61it/s, train/loss=2.850]
Epoch 0: | | 243/? [01:32<00:00, 2.62it/s, train/loss=2.850]
Epoch 0: | | 243/? [01:32<00:00, 2.62it/s, train/loss=5.900]
Epoch 0: | | 244/? [01:33<00:00, 2.62it/s, train/loss=5.900]
Epoch 0: | | 244/? [01:33<00:00, 2.62it/s, train/loss=2.430]
Epoch 0: | | 245/? [01:33<00:00, 2.62it/s, train/loss=2.430]
Epoch 0: | | 245/? [01:33<00:00, 2.62it/s, train/loss=5.900]
Epoch 0: | | 246/? [01:33<00:00, 2.62it/s, train/loss=5.900]
Epoch 0: | | 246/? [01:33<00:00, 2.62it/s, train/loss=1.230]
Epoch 0: | | 247/? [01:34<00:00, 2.63it/s, train/loss=1.230]
Epoch 0: | | 247/? [01:34<00:00, 2.63it/s, train/loss=5.870]
Epoch 0: | | 248/? [01:34<00:00, 2.63it/s, train/loss=5.870]
Epoch 0: | | 248/? [01:34<00:00, 2.63it/s, train/loss=2.390]
Epoch 0: | | 249/? [01:34<00:00, 2.63it/s, train/loss=2.390]
Epoch 0: | | 249/? [01:34<00:00, 2.63it/s, train/loss=5.860]
Epoch 0: | | 250/? [01:34<00:00, 2.63it/s, train/loss=5.860]
Epoch 0: | | 250/? [01:34<00:00, 2.63it/s, train/loss=1.140]
Epoch 0: | | 251/? [01:35<00:00, 2.62it/s, train/loss=1.140]
Epoch 0: | | 251/? [01:35<00:00, 2.62it/s, train/loss=2.820]
Epoch 0: | | 252/? [01:36<00:00, 2.62it/s, train/loss=2.820]
Epoch 0: | | 252/? [01:36<00:00, 2.62it/s, train/loss=1.120]
Epoch 0: | | 253/? [01:36<00:00, 2.63it/s, train/loss=1.120]
Epoch 0: | | 253/? [01:36<00:00, 2.63it/s, train/loss=5.850]
Epoch 0: | | 254/? [01:36<00:00, 2.63it/s, train/loss=5.850]
Epoch 0: | | 254/? [01:36<00:00, 2.63it/s, train/loss=1.020]
Epoch 0: | | 255/? [01:36<00:00, 2.64it/s, train/loss=1.020]
Epoch 0: | | 255/? [01:36<00:00, 2.64it/s, train/loss=5.830]
Epoch 0: | | 256/? [01:37<00:00, 2.64it/s, train/loss=5.830]
Epoch 0: | | 256/? [01:37<00:00, 2.64it/s, train/loss=1.290]
Epoch 0: | | 257/? [01:37<00:00, 2.65it/s, train/loss=1.290]
Epoch 0: | | 257/? [01:37<00:00, 2.65it/s, train/loss=5.800]
Epoch 0: | | 258/? [01:37<00:00, 2.65it/s, train/loss=5.800]
Epoch 0: | | 258/? [01:37<00:00, 2.65it/s, train/loss=1.870]
Epoch 0: | | 259/? [01:37<00:00, 2.65it/s, train/loss=1.870]
Epoch 0: | | 259/? [01:37<00:00, 2.65it/s, train/loss=5.770]
Epoch 0: | | 260/? [01:37<00:00, 2.65it/s, train/loss=5.770]
Epoch 0: | | 260/? [01:37<00:00, 2.65it/s, train/loss=1.200]
Epoch 0: | | 261/? [01:38<00:00, 2.64it/s, train/loss=1.200]
Epoch 0: | | 261/? [01:38<00:00, 2.64it/s, train/loss=2.530]
Epoch 0: | | 262/? [01:39<00:00, 2.64it/s, train/loss=2.530]
Epoch 0: | | 262/? [01:39<00:00, 2.64it/s, train/loss=3.570]
Epoch 0: | | 263/? [01:39<00:00, 2.65it/s, train/loss=3.570]
Epoch 0: | | 263/? [01:39<00:00, 2.65it/s, train/loss=5.770]
Epoch 0: | | 264/? [01:39<00:00, 2.65it/s, train/loss=5.770]
Epoch 0: | | 264/? [01:39<00:00, 2.65it/s, train/loss=0.946]
Epoch 0: | | 265/? [01:39<00:00, 2.66it/s, train/loss=0.946]
Epoch 0: | | 265/? [01:39<00:00, 2.66it/s, train/loss=5.760]
Epoch 0: | | 266/? [01:40<00:00, 2.65it/s, train/loss=5.760]
Epoch 0: | | 266/? [01:40<00:00, 2.65it/s, train/loss=1.480]
Epoch 0: | | 267/? [01:40<00:00, 2.66it/s, train/loss=1.480]
Epoch 0: | | 267/? [01:40<00:00, 2.66it/s, train/loss=5.740]
Epoch 0: | | 268/? [01:40<00:00, 2.65it/s, train/loss=5.740]
Epoch 0: | | 268/? [01:40<00:00, 2.65it/s, train/loss=3.570]
Epoch 0: | | 269/? [01:41<00:00, 2.66it/s, train/loss=3.570]
Epoch 0: | | 269/? [01:41<00:00, 2.66it/s, train/loss=5.720]
Epoch 0: | | 270/? [01:41<00:00, 2.66it/s, train/loss=5.720]
Epoch 0: | | 270/? [01:41<00:00, 2.66it/s, train/loss=2.580]
Epoch 0: | | 271/? [01:42<00:00, 2.65it/s, train/loss=2.580]
Epoch 0: | | 271/? [01:42<00:00, 2.65it/s, train/loss=2.380]
Epoch 0: | | 272/? [01:42<00:00, 2.65it/s, train/loss=2.380]
Epoch 0: | | 272/? [01:42<00:00, 2.65it/s, train/loss=0.554]
Epoch 0: | | 273/? [01:42<00:00, 2.66it/s, train/loss=0.554]
Epoch 0: | | 273/? [01:42<00:00, 2.66it/s, train/loss=5.690]
Epoch 0: | | 274/? [01:43<00:00, 2.66it/s, train/loss=5.690]
Epoch 0: | | 274/? [01:43<00:00, 2.66it/s, train/loss=1.810]
Epoch 0: | | 275/? [01:43<00:00, 2.67it/s, train/loss=1.810]
Epoch 0: | | 275/? [01:43<00:00, 2.67it/s, train/loss=5.660]
Epoch 0: | | 276/? [01:43<00:00, 2.66it/s, train/loss=5.660]
Epoch 0: | | 276/? [01:43<00:00, 2.66it/s, train/loss=3.710]
Epoch 0: | | 277/? [01:43<00:00, 2.67it/s, train/loss=3.710]
Epoch 0: | | 277/? [01:43<00:00, 2.67it/s, train/loss=5.640]
Epoch 0: | | 278/? [01:44<00:00, 2.67it/s, train/loss=5.640]
Epoch 0: | | 278/? [01:44<00:00, 2.67it/s, train/loss=2.730]
Epoch 0: | | 279/? [01:44<00:00, 2.68it/s, train/loss=2.730]
Epoch 0: | | 279/? [01:44<00:00, 2.68it/s, train/loss=5.610]
Epoch 0: | | 280/? [01:44<00:00, 2.68it/s, train/loss=5.610]
Epoch 0: | | 280/? [01:44<00:00, 2.68it/s, train/loss=1.710]
Epoch 0: | | 281/? [01:45<00:00, 2.67it/s, train/loss=1.710]
Epoch 0: | | 281/? [01:45<00:00, 2.67it/s, train/loss=2.830]
Epoch 0: | | 282/? [01:45<00:00, 2.67it/s, train/loss=2.830]
Epoch 0: | | 282/? [01:45<00:00, 2.67it/s, train/loss=4.200]
Epoch 0: | | 283/? [01:45<00:00, 2.67it/s, train/loss=4.200]
Epoch 0: | | 283/? [01:45<00:00, 2.67it/s, train/loss=5.560]
Epoch 0: | | 284/? [01:46<00:00, 2.67it/s, train/loss=5.560]
Epoch 0: | | 284/? [01:46<00:00, 2.67it/s, train/loss=2.860]
Epoch 0: | | 285/? [01:46<00:00, 2.68it/s, train/loss=2.860]
Epoch 0: | | 285/? [01:46<00:00, 2.68it/s, train/loss=5.520]
Epoch 0: | | 286/? [01:46<00:00, 2.68it/s, train/loss=5.520]
Epoch 0: | | 286/? [01:46<00:00, 2.68it/s, train/loss=3.260]
Epoch 0: | | 287/? [01:46<00:00, 2.69it/s, train/loss=3.260]
Epoch 0: | | 287/? [01:46<00:00, 2.69it/s, train/loss=5.480]
Epoch 0: | | 288/? [01:47<00:00, 2.69it/s, train/loss=5.480]
Epoch 0: | | 288/? [01:47<00:00, 2.69it/s, train/loss=2.080]
Epoch 0: | | 289/? [01:47<00:00, 2.70it/s, train/loss=2.080]
Epoch 0: | | 289/? [01:47<00:00, 2.70it/s, train/loss=5.440]
Epoch 0: | | 290/? [01:47<00:00, 2.70it/s, train/loss=5.440]
Epoch 0: | | 290/? [01:47<00:00, 2.70it/s, train/loss=2.980]
Epoch 0: | | 291/? [01:48<00:00, 2.68it/s, train/loss=2.980]
Epoch 0: | | 291/? [01:48<00:00, 2.68it/s, train/loss=1.650]
Epoch 0: | | 292/? [01:48<00:00, 2.69it/s, train/loss=1.650]
Epoch 0: | | 292/? [01:48<00:00, 2.68it/s, train/loss=1.700]
Epoch 0: | | 293/? [01:48<00:00, 2.69it/s, train/loss=1.700]
Epoch 0: | | 293/? [01:48<00:00, 2.69it/s, train/loss=5.400]
Epoch 0: | | 294/? [01:49<00:00, 2.69it/s, train/loss=5.400]
Epoch 0: | | 294/? [01:49<00:00, 2.69it/s, train/loss=3.030]
Epoch 0: | | 295/? [01:49<00:00, 2.70it/s, train/loss=3.030]
Epoch 0: | | 295/? [01:49<00:00, 2.70it/s, train/loss=5.380]
Epoch 0: | | 296/? [01:49<00:00, 2.70it/s, train/loss=5.380]
Epoch 0: | | 296/? [01:49<00:00, 2.70it/s, train/loss=2.820]
Epoch 0: | | 297/? [01:49<00:00, 2.71it/s, train/loss=2.820]
Epoch 0: | | 297/? [01:49<00:00, 2.71it/s, train/loss=5.350]
Epoch 0: | | 298/? [01:50<00:00, 2.71it/s, train/loss=5.350]
Epoch 0: | | 298/? [01:50<00:00, 2.71it/s, train/loss=1.420]
Epoch 0: | | 299/? [01:50<00:00, 2.71it/s, train/loss=1.420]
Epoch 0: | | 299/? [01:50<00:00, 2.71it/s, train/loss=5.320]
Epoch 0: | | 300/? [01:50<00:00, 2.71it/s, train/loss=5.320]
Epoch 0: | | 300/? [01:50<00:00, 2.71it/s, train/loss=1.020]
Epoch 0: | | 301/? [01:51<00:00, 2.70it/s, train/loss=1.020]
Epoch 0: | | 301/? [01:51<00:00, 2.70it/s, train/loss=0.883]
Epoch 0: | | 302/? [01:51<00:00, 2.70it/s, train/loss=0.883]
Epoch 0: | | 302/? [01:51<00:00, 2.70it/s, train/loss=3.050]
Epoch 0: | | 303/? [01:51<00:00, 2.71it/s, train/loss=3.050]
Epoch 0: | | 303/? [01:51<00:00, 2.71it/s, train/loss=5.280]
Epoch 0: | | 304/? [01:52<00:00, 2.71it/s, train/loss=5.280]
Epoch 0: | | 304/? [01:52<00:00, 2.71it/s, train/loss=2.640]
Epoch 0: | | 305/? [01:52<00:00, 2.72it/s, train/loss=2.640]
Epoch 0: | | 305/? [01:52<00:00, 2.72it/s, train/loss=5.260]
Epoch 0: | | 306/? [01:52<00:00, 2.71it/s, train/loss=5.260]
Epoch 0: | | 306/? [01:52<00:00, 2.71it/s, train/loss=1.430]
Epoch 0: | | 307/? [01:52<00:00, 2.72it/s, train/loss=1.430]
Epoch 0: | | 307/? [01:52<00:00, 2.72it/s, train/loss=5.230]
Epoch 0: | | 308/? [01:53<00:00, 2.72it/s, train/loss=5.230]
Epoch 0: | | 308/? [01:53<00:00, 2.72it/s, train/loss=2.380]
Epoch 0: | | 309/? [01:53<00:00, 2.73it/s, train/loss=2.380]
Epoch 0: | | 309/? [01:53<00:00, 2.73it/s, train/loss=5.200]
Epoch 0: | | 310/? [01:53<00:00, 2.73it/s, train/loss=5.200]
Epoch 0: | | 310/? [01:53<00:00, 2.73it/s, train/loss=1.700]
Epoch 0: | | 311/? [01:54<00:00, 2.72it/s, train/loss=1.700]
Epoch 0: | | 311/? [01:54<00:00, 2.71it/s, train/loss=2.040]
Epoch 0: | | 312/? [01:54<00:00, 2.72it/s, train/loss=2.040]
Epoch 0: | | 312/? [01:54<00:00, 2.71it/s, train/loss=0.999]
Epoch 0: | | 313/? [01:54<00:00, 2.72it/s, train/loss=0.999]
Epoch 0: | | 313/? [01:54<00:00, 2.72it/s, train/loss=5.190]
Epoch 0: | | 314/? [01:55<00:00, 2.72it/s, train/loss=5.190]
Epoch 0: | | 314/? [01:55<00:00, 2.72it/s, train/loss=1.130]
Epoch 0: | | 315/? [01:55<00:00, 2.73it/s, train/loss=1.130]
Epoch 0: | | 315/? [01:55<00:00, 2.73it/s, train/loss=5.190]
Epoch 0: | | 316/? [01:55<00:00, 2.73it/s, train/loss=5.190]
Epoch 0: | | 316/? [01:55<00:00, 2.73it/s, train/loss=3.310]
Epoch 0: | | 317/? [01:55<00:00, 2.74it/s, train/loss=3.310]
Epoch 0: | | 317/? [01:55<00:00, 2.74it/s, train/loss=5.170]
Epoch 0: | | 318/? [01:56<00:00, 2.73it/s, train/loss=5.170]
Epoch 0: | | 318/? [01:56<00:00, 2.73it/s, train/loss=1.810]
Epoch 0: | | 319/? [01:56<00:00, 2.74it/s, train/loss=1.810]
Epoch 0: | | 319/? [01:56<00:00, 2.74it/s, train/loss=5.160]
Epoch 0: | | 320/? [01:56<00:00, 2.74it/s, train/loss=5.160]
Epoch 0: | | 320/? [01:56<00:00, 2.74it/s, train/loss=2.270]
Epoch 0: | | 321/? [01:57<00:00, 2.73it/s, train/loss=2.270]
Epoch 0: | | 321/? [01:57<00:00, 2.73it/s, train/loss=1.920]
Epoch 0: | | 322/? [01:57<00:00, 2.73it/s, train/loss=1.920]
Epoch 0: | | 322/? [01:58<00:00, 2.73it/s, train/loss=1.600]
Epoch 0: | | 323/? [01:58<00:00, 2.73it/s, train/loss=1.600]
Epoch 0: | | 323/? [01:58<00:00, 2.73it/s, train/loss=5.150]
Epoch 0: | | 324/? [01:58<00:00, 2.73it/s, train/loss=5.150]
Epoch 0: | | 324/? [01:58<00:00, 2.73it/s, train/loss=3.730]
Epoch 0: | | 325/? [01:58<00:00, 2.74it/s, train/loss=3.730]
Epoch 0: | | 325/? [01:58<00:00, 2.74it/s, train/loss=5.150]
Epoch 0: | | 326/? [01:58<00:00, 2.74it/s, train/loss=5.150]
Epoch 0: | | 326/? [01:58<00:00, 2.74it/s, train/loss=2.220]
Epoch 0: | | 327/? [01:59<00:00, 2.75it/s, train/loss=2.220]
Epoch 0: | | 327/? [01:59<00:00, 2.75it/s, train/loss=5.130]
Epoch 0: | | 328/? [01:59<00:00, 2.75it/s, train/loss=5.130]
Epoch 0: | | 328/? [01:59<00:00, 2.75it/s, train/loss=1.950]
Epoch 0: | | 329/? [01:59<00:00, 2.75it/s, train/loss=1.950]
Epoch 0: | | 329/? [01:59<00:00, 2.75it/s, train/loss=5.100]
Epoch 0: | | 330/? [01:59<00:00, 2.75it/s, train/loss=5.100]
Epoch 0: | | 330/? [01:59<00:00, 2.75it/s, train/loss=5.410]
Epoch 0: | | 331/? [02:00<00:00, 2.74it/s, train/loss=5.410]
Epoch 0: | | 331/? [02:00<00:00, 2.74it/s, train/loss=2.210]
Epoch 0: | | 332/? [02:01<00:00, 2.74it/s, train/loss=2.210]
Epoch 0: | | 332/? [02:01<00:00, 2.74it/s, train/loss=1.130]
Epoch 0: | | 333/? [02:01<00:00, 2.75it/s, train/loss=1.130]
Epoch 0: | | 333/? [02:01<00:00, 2.75it/s, train/loss=5.080]
Epoch 0: | | 334/? [02:01<00:00, 2.75it/s, train/loss=5.080]
Epoch 0: | | 334/? [02:01<00:00, 2.75it/s, train/loss=2.390]
Epoch 0: | | 335/? [02:01<00:00, 2.75it/s, train/loss=2.390]
Epoch 0: | | 335/? [02:01<00:00, 2.75it/s, train/loss=5.060]
Epoch 0: | | 336/? [02:02<00:00, 2.75it/s, train/loss=5.060]
Epoch 0: | | 336/? [02:02<00:00, 2.75it/s, train/loss=3.190]
Epoch 0: | | 337/? [02:02<00:00, 2.76it/s, train/loss=3.190]
Epoch 0: | | 337/? [02:02<00:00, 2.76it/s, train/loss=5.040]
Epoch 0: | | 338/? [02:02<00:00, 2.76it/s, train/loss=5.040]
Epoch 0: | | 338/? [02:02<00:00, 2.76it/s, train/loss=0.746]
Epoch 0: | | 339/? [02:02<00:00, 2.77it/s, train/loss=0.746]
Epoch 0: | | 339/? [02:02<00:00, 2.77it/s, train/loss=5.020]
Epoch 0: | | 340/? [02:02<00:00, 2.77it/s, train/loss=5.020]
Epoch 0: | | 340/? [02:02<00:00, 2.77it/s, train/loss=1.340]
Epoch 0: | | 341/? [02:03<00:00, 2.75it/s, train/loss=1.340]
Epoch 0: | | 341/? [02:03<00:00, 2.75it/s, train/loss=1.570]
Epoch 0: | | 342/? [02:04<00:00, 2.75it/s, train/loss=1.570]
Epoch 0: | | 342/? [02:04<00:00, 2.75it/s, train/loss=2.380]
Epoch 0: | | 343/? [02:04<00:00, 2.76it/s, train/loss=2.380]
Epoch 0: | | 343/? [02:04<00:00, 2.76it/s, train/loss=5.000]
Epoch 0: | | 344/? [02:04<00:00, 2.76it/s, train/loss=5.000]
Epoch 0: | | 344/? [02:04<00:00, 2.76it/s, train/loss=4.760]
Epoch 0: | | 345/? [02:04<00:00, 2.77it/s, train/loss=4.760]
Epoch 0: | | 345/? [02:04<00:00, 2.77it/s, train/loss=4.980]
Epoch 0: | | 346/? [02:05<00:00, 2.77it/s, train/loss=4.980]
Epoch 0: | | 346/? [02:05<00:00, 2.77it/s, train/loss=3.570]
Epoch 0: | | 347/? [02:05<00:00, 2.77it/s, train/loss=3.570]
Epoch 0: | | 347/? [02:05<00:00, 2.77it/s, train/loss=4.940]
Epoch 0: | | 348/? [02:05<00:00, 2.77it/s, train/loss=4.940]
Epoch 0: | | 348/? [02:05<00:00, 2.77it/s, train/loss=2.680]
Epoch 0: | | 349/? [02:05<00:00, 2.78it/s, train/loss=2.680]
Epoch 0: | | 349/? [02:05<00:00, 2.78it/s, train/loss=4.940]
Epoch 0: | | 350/? [02:06<00:00, 2.78it/s, train/loss=4.940]
Epoch 0: | | 350/? [02:06<00:00, 2.78it/s, train/loss=1.490]
Epoch 0: | | 351/? [02:06<00:00, 2.77it/s, train/loss=1.490]
Epoch 0: | | 351/? [02:06<00:00, 2.76it/s, train/loss=2.270]
Epoch 0: | | 352/? [02:07<00:00, 2.77it/s, train/loss=2.270]
Epoch 0: | | 352/? [02:07<00:00, 2.77it/s, train/loss=1.580]
Epoch 0: | | 353/? [02:07<00:00, 2.77it/s, train/loss=1.580]
Epoch 0: | | 353/? [02:07<00:00, 2.77it/s, train/loss=4.990]
Epoch 0: | | 354/? [02:07<00:00, 2.77it/s, train/loss=4.990]
Epoch 0: | | 354/? [02:07<00:00, 2.77it/s, train/loss=0.693]
Epoch 0: | | 355/? [02:07<00:00, 2.78it/s, train/loss=0.693]
Epoch 0: | | 355/? [02:07<00:00, 2.78it/s, train/loss=4.980]
Epoch 0: | | 356/? [02:08<00:00, 2.77it/s, train/loss=4.980]
Epoch 0: | | 356/? [02:08<00:00, 2.77it/s, train/loss=2.220]
Epoch 0: | | 357/? [02:08<00:00, 2.78it/s, train/loss=2.220]
Epoch 0: | | 357/? [02:08<00:00, 2.78it/s, train/loss=4.950]
Epoch 0: | | 358/? [02:08<00:00, 2.78it/s, train/loss=4.950]
Epoch 0: | | 358/? [02:08<00:00, 2.78it/s, train/loss=0.770]
Epoch 0: | | 359/? [02:08<00:00, 2.79it/s, train/loss=0.770]
Epoch 0: | | 359/? [02:08<00:00, 2.79it/s, train/loss=4.930]
Epoch 0: | | 360/? [02:09<00:00, 2.79it/s, train/loss=4.930]
Epoch 0: | | 360/? [02:09<00:00, 2.79it/s, train/loss=3.010]
Epoch 0: | | 361/? [02:10<00:00, 2.77it/s, train/loss=3.010]
Epoch 0: | | 361/? [02:10<00:00, 2.77it/s, train/loss=0.704]
Epoch 0: | | 362/? [02:10<00:00, 2.78it/s, train/loss=0.704]
Epoch 0: | | 362/? [02:10<00:00, 2.77it/s, train/loss=2.000]
Epoch 0: | | 363/? [02:10<00:00, 2.78it/s, train/loss=2.000]
Epoch 0: | | 363/? [02:10<00:00, 2.78it/s, train/loss=4.930]
Epoch 0: | | 364/? [02:10<00:00, 2.78it/s, train/loss=4.930]
Epoch 0: | | 364/? [02:10<00:00, 2.78it/s, train/loss=2.770]
Epoch 0: | | 365/? [02:10<00:00, 2.79it/s, train/loss=2.770]
Epoch 0: | | 365/? [02:10<00:00, 2.79it/s, train/loss=4.920]
Epoch 0: | | 366/? [02:11<00:00, 2.79it/s, train/loss=4.920]
Epoch 0: | | 366/? [02:11<00:00, 2.79it/s, train/loss=1.270]
Epoch 0: | | 367/? [02:11<00:00, 2.79it/s, train/loss=1.270]
Epoch 0: | | 367/? [02:11<00:00, 2.79it/s, train/loss=4.900]
Epoch 0: | | 368/? [02:11<00:00, 2.79it/s, train/loss=4.900]
Epoch 0: | | 368/? [02:11<00:00, 2.79it/s, train/loss=2.370]
Epoch 0: | | 369/? [02:11<00:00, 2.80it/s, train/loss=2.370]
Epoch 0: | | 369/? [02:11<00:00, 2.80it/s, train/loss=4.890]
Epoch 0: | | 370/? [02:12<00:00, 2.80it/s, train/loss=4.890]
Epoch 0: | | 370/? [02:12<00:00, 2.80it/s, train/loss=1.150]
Epoch 0: | | 371/? [02:13<00:00, 2.79it/s, train/loss=1.150]
Epoch 0: | | 371/? [02:13<00:00, 2.78it/s, train/loss=2.940]
Epoch 0: | | 372/? [02:13<00:00, 2.79it/s, train/loss=2.940]
Epoch 0: | | 372/? [02:13<00:00, 2.78it/s, train/loss=1.090]
Epoch 0: | | 373/? [02:13<00:00, 2.79it/s, train/loss=1.090]
Epoch 0: | | 373/? [02:13<00:00, 2.79it/s, train/loss=4.880]
Epoch 0: | | 374/? [02:14<00:00, 2.79it/s, train/loss=4.880]
Epoch 0: | | 374/? [02:14<00:00, 2.79it/s, train/loss=3.940]
Epoch 0: | | 375/? [02:14<00:00, 2.80it/s, train/loss=3.940]
Epoch 0: | | 375/? [02:14<00:00, 2.80it/s, train/loss=4.870]
Epoch 0: | | 376/? [02:14<00:00, 2.80it/s, train/loss=4.870]
Epoch 0: | | 376/? [02:14<00:00, 2.80it/s, train/loss=2.950]
Epoch 0: | | 377/? [02:14<00:00, 2.80it/s, train/loss=2.950]
Epoch 0: | | 377/? [02:14<00:00, 2.80it/s, train/loss=4.840]
Epoch 0: | | 378/? [02:14<00:00, 2.80it/s, train/loss=4.840]
Epoch 0: | | 378/? [02:14<00:00, 2.80it/s, train/loss=2.900]
Epoch 0: | | 379/? [02:14<00:00, 2.81it/s, train/loss=2.900]
Epoch 0: | | 379/? [02:14<00:00, 2.81it/s, train/loss=4.820]
Epoch 0: | | 380/? [02:15<00:00, 2.81it/s, train/loss=4.820]
Epoch 0: | | 380/? [02:15<00:00, 2.81it/s, train/loss=2.240]
Epoch 0: | | 381/? [02:16<00:00, 2.80it/s, train/loss=2.240]
Epoch 0: | | 381/? [02:16<00:00, 2.79it/s, train/loss=0.726]
Epoch 0: | | 382/? [02:16<00:00, 2.79it/s, train/loss=0.726]
Epoch 0: | | 382/? [02:16<00:00, 2.79it/s, train/loss=1.090]
Epoch 0: | | 383/? [02:16<00:00, 2.80it/s, train/loss=1.090]
Epoch 0: | | 383/? [02:16<00:00, 2.80it/s, train/loss=4.800]
Epoch 0: | | 384/? [02:17<00:00, 2.80it/s, train/loss=4.800]
Epoch 0: | | 384/? [02:17<00:00, 2.80it/s, train/loss=3.060]
Epoch 0: | | 385/? [02:17<00:00, 2.81it/s, train/loss=3.060]
Epoch 0: | | 385/? [02:17<00:00, 2.81it/s, train/loss=4.780]
Epoch 0: | | 386/? [02:17<00:00, 2.80it/s, train/loss=4.780]
Epoch 0: | | 386/? [02:17<00:00, 2.80it/s, train/loss=2.630]
Epoch 0: | | 387/? [02:17<00:00, 2.81it/s, train/loss=2.630]
Epoch 0: | | 387/? [02:17<00:00, 2.81it/s, train/loss=4.750]
Epoch 0: | | 388/? [02:18<00:00, 2.81it/s, train/loss=4.750]
Epoch 0: | | 388/? [02:18<00:00, 2.81it/s, train/loss=0.970]
Epoch 0: | | 389/? [02:18<00:00, 2.82it/s, train/loss=0.970]
Epoch 0: | | 389/? [02:18<00:00, 2.82it/s, train/loss=4.730]
Epoch 0: | | 390/? [02:18<00:00, 2.81it/s, train/loss=4.730]
Epoch 0: | | 390/? [02:18<00:00, 2.81it/s, train/loss=3.590]
Epoch 0: | | 391/? [02:19<00:00, 2.80it/s, train/loss=3.590]
Epoch 0: | | 391/? [02:19<00:00, 2.80it/s, train/loss=1.050]
Epoch 0: | | 392/? [02:19<00:00, 2.80it/s, train/loss=1.050]
Epoch 0: | | 392/? [02:19<00:00, 2.80it/s, train/loss=0.961]
Epoch 0: | | 393/? [02:19<00:00, 2.81it/s, train/loss=0.961]
Epoch 0: | | 393/? [02:19<00:00, 2.81it/s, train/loss=4.700]
Epoch 0: | | 394/? [02:20<00:00, 2.81it/s, train/loss=4.700]
Epoch 0: | | 394/? [02:20<00:00, 2.81it/s, train/loss=2.750]
Epoch 0: | | 395/? [02:20<00:00, 2.81it/s, train/loss=2.750]
Epoch 0: | | 395/? [02:20<00:00, 2.81it/s, train/loss=4.690]
Epoch 0: | | 396/? [02:20<00:00, 2.81it/s, train/loss=4.690]
Epoch 0: | | 396/? [02:20<00:00, 2.81it/s, train/loss=4.030]
Epoch 0: | | 397/? [02:20<00:00, 2.82it/s, train/loss=4.030]
Epoch 0: | | 397/? [02:20<00:00, 2.82it/s, train/loss=4.670]
Epoch 0: | | 398/? [02:21<00:00, 2.82it/s, train/loss=4.670]
Epoch 0: | | 398/? [02:21<00:00, 2.82it/s, train/loss=2.210]
Epoch 0: | | 399/? [02:21<00:00, 2.82it/s, train/loss=2.210]
Epoch 0: | | 399/? [02:21<00:00, 2.82it/s, train/loss=4.660]
Epoch 0: | | 400/? [02:21<00:00, 2.82it/s, train/loss=4.660]
Epoch 0: | | 400/? [02:21<00:00, 2.82it/s, train/loss=2.450]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:04, 8.57it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:04, 8.84it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:04, 8.95it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:04, 8.76it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:03, 8.82it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:03, 8.82it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:03, 8.89it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:03, 8.95it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:00<00:03, 9.01it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:01<00:03, 9.01it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:01<00:03, 9.03it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:03, 9.07it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:02, 9.10it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 9.10it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 9.09it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 9.06it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:02, 9.07it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:01<00:02, 9.07it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:02<00:02, 9.08it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:02<00:02, 9.06it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:02<00:02, 9.05it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:02<00:01, 9.06it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:02<00:01, 9.07it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 9.08it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 9.10it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 9.10it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 9.12it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:03<00:01, 9.13it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:03<00:01, 8.97it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:03<00:01, 8.92it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:03<00:01, 8.93it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:03<00:00, 8.95it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:03<00:00, 8.97it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:03<00:00, 8.97it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 8.98it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:04<00:00, 8.96it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:04<00:00, 8.96it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:04<00:00, 8.95it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:04<00:00, 8.95it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00, 8.95it/s][A
[A
Epoch 0: | | 400/? [02:30<00:00, 2.65it/s, train/loss=2.450]
Epoch 0: | | 401/? [02:50<00:00, 2.35it/s, train/loss=2.450]
Epoch 0: | | 401/? [02:51<00:00, 2.34it/s, train/loss=0.663]
Epoch 0: | | 402/? [02:51<00:00, 2.35it/s, train/loss=0.663]
Epoch 0: | | 402/? [02:51<00:00, 2.35it/s, train/loss=1.990]
Epoch 0: | | 403/? [02:51<00:00, 2.35it/s, train/loss=1.990]
Epoch 0: | | 403/? [02:51<00:00, 2.35it/s, train/loss=4.650]
Epoch 0: | | 404/? [02:51<00:00, 2.35it/s, train/loss=4.650]
Epoch 0: | | 404/? [02:51<00:00, 2.35it/s, train/loss=1.070]
Epoch 0: | | 405/? [02:51<00:00, 2.36it/s, train/loss=1.070]
Epoch 0: | | 405/? [02:51<00:00, 2.36it/s, train/loss=4.640]
Epoch 0: | | 406/? [02:52<00:00, 2.36it/s, train/loss=4.640]
Epoch 0: | | 406/? [02:52<00:00, 2.36it/s, train/loss=2.970]
Epoch 0: | | 407/? [02:52<00:00, 2.36it/s, train/loss=2.970]
Epoch 0: | | 407/? [02:52<00:00, 2.36it/s, train/loss=4.610]
Epoch 0: | | 408/? [02:52<00:00, 2.36it/s, train/loss=4.610]
Epoch 0: | | 408/? [02:52<00:00, 2.36it/s, train/loss=2.380]
Epoch 0: | | 409/? [02:52<00:00, 2.37it/s, train/loss=2.380]
Epoch 0: | | 409/? [02:52<00:00, 2.37it/s, train/loss=4.590]
Epoch 0: | | 410/? [02:53<00:00, 2.36it/s, train/loss=4.590]
Epoch 0: | | 410/? [02:53<00:00, 2.36it/s, train/loss=1.430]
Epoch 0: | | 411/? [02:54<00:00, 2.36it/s, train/loss=1.430]
Epoch 0: | | 411/? [02:54<00:00, 2.35it/s, train/loss=1.160]
Epoch 0: | | 412/? [02:54<00:00, 2.36it/s, train/loss=1.160]
Epoch 0: | | 412/? [02:54<00:00, 2.36it/s, train/loss=1.590]
Epoch 0: | | 413/? [02:54<00:00, 2.36it/s, train/loss=1.590]
Epoch 0: | | 413/? [02:54<00:00, 2.36it/s, train/loss=4.570]
Epoch 0: | | 414/? [02:55<00:00, 2.36it/s, train/loss=4.570]
Epoch 0: | | 414/? [02:55<00:00, 2.36it/s, train/loss=1.560]
Epoch 0: | | 415/? [02:55<00:00, 2.37it/s, train/loss=1.560]
Epoch 0: | | 415/? [02:55<00:00, 2.37it/s, train/loss=4.550]
Epoch 0: | | 416/? [02:55<00:00, 2.37it/s, train/loss=4.550]
Epoch 0: | | 416/? [02:55<00:00, 2.37it/s, train/loss=3.270]
Epoch 0: | | 417/? [02:55<00:00, 2.37it/s, train/loss=3.270]
Epoch 0: | | 417/? [02:55<00:00, 2.37it/s, train/loss=4.530]
Epoch 0: | | 418/? [02:56<00:00, 2.37it/s, train/loss=4.530]
Epoch 0: | | 418/? [02:56<00:00, 2.37it/s, train/loss=3.370]
Epoch 0: | | 419/? [02:56<00:00, 2.38it/s, train/loss=3.370]
Epoch 0: | | 419/? [02:56<00:00, 2.38it/s, train/loss=4.520]
Epoch 0: | | 420/? [02:56<00:00, 2.38it/s, train/loss=4.520]
Epoch 0: | | 420/? [02:56<00:00, 2.38it/s, train/loss=2.730]
Epoch 0: | | 421/? [02:57<00:00, 2.37it/s, train/loss=2.730]
Epoch 0: | | 421/? [02:57<00:00, 2.37it/s, train/loss=0.665]
Epoch 0: | | 422/? [02:58<00:00, 2.37it/s, train/loss=0.665]
Epoch 0: | | 422/? [02:58<00:00, 2.37it/s, train/loss=2.290]
Epoch 0: | | 423/? [02:58<00:00, 2.37it/s, train/loss=2.290]
Epoch 0: | | 423/? [02:58<00:00, 2.37it/s, train/loss=4.540]
Epoch 0: | | 424/? [02:58<00:00, 2.38it/s, train/loss=4.540]
Epoch 0: | | 424/? [02:58<00:00, 2.38it/s, train/loss=2.300]
Epoch 0: | | 425/? [02:58<00:00, 2.38it/s, train/loss=2.300]
Epoch 0: | | 425/? [02:58<00:00, 2.38it/s, train/loss=4.540]
Epoch 0: | | 426/? [02:58<00:00, 2.38it/s, train/loss=4.540]
Epoch 0: | | 426/? [02:58<00:00, 2.38it/s, train/loss=1.450]
Epoch 0: | | 427/? [02:59<00:00, 2.39it/s, train/loss=1.450]
Epoch 0: | | 427/? [02:59<00:00, 2.38it/s, train/loss=4.500]
Epoch 0: | | 428/? [02:59<00:00, 2.39it/s, train/loss=4.500]
Epoch 0: | | 428/? [02:59<00:00, 2.39it/s, train/loss=0.830]
Epoch 0: | | 429/? [02:59<00:00, 2.39it/s, train/loss=0.830]
Epoch 0: | | 429/? [02:59<00:00, 2.39it/s, train/loss=4.490]
Epoch 0: | | 430/? [02:59<00:00, 2.39it/s, train/loss=4.490]
Epoch 0: | | 430/? [02:59<00:00, 2.39it/s, train/loss=0.742]
Epoch 0: | | 431/? [03:00<00:00, 2.38it/s, train/loss=0.742]
Epoch 0: | | 431/? [03:00<00:00, 2.38it/s, train/loss=1.350]
Epoch 0: | | 432/? [03:01<00:00, 2.38it/s, train/loss=1.350]
Epoch 0: | | 432/? [03:01<00:00, 2.38it/s, train/loss=2.160]
Epoch 0: | | 433/? [03:01<00:00, 2.39it/s, train/loss=2.160]
Epoch 0: | | 433/? [03:01<00:00, 2.39it/s, train/loss=4.540]
Epoch 0: | | 434/? [03:01<00:00, 2.39it/s, train/loss=4.540]
Epoch 0: | | 434/? [03:01<00:00, 2.39it/s, train/loss=2.430]
Epoch 0: | | 435/? [03:01<00:00, 2.39it/s, train/loss=2.430]
Epoch 0: | | 435/? [03:01<00:00, 2.39it/s, train/loss=4.530]
Epoch 0: | | 436/? [03:02<00:00, 2.39it/s, train/loss=4.530]
Epoch 0: | | 436/? [03:02<00:00, 2.39it/s, train/loss=3.150]
Epoch 0: | | 437/? [03:02<00:00, 2.40it/s, train/loss=3.150]
Epoch 0: | | 437/? [03:02<00:00, 2.40it/s, train/loss=4.510]
Epoch 0: | | 438/? [03:02<00:00, 2.40it/s, train/loss=4.510]
Epoch 0: | | 438/? [03:02<00:00, 2.40it/s, train/loss=2.300]
Epoch 0: | | 439/? [03:02<00:00, 2.40it/s, train/loss=2.300]
Epoch 0: | | 439/? [03:02<00:00, 2.40it/s, train/loss=4.510]
Epoch 0: | | 440/? [03:03<00:00, 2.40it/s, train/loss=4.510]
Epoch 0: | | 440/? [03:03<00:00, 2.40it/s, train/loss=3.060]
Epoch 0: | | 441/? [03:03<00:00, 2.40it/s, train/loss=3.060]
Epoch 0: | | 441/? [03:03<00:00, 2.40it/s, train/loss=1.380]
Epoch 0: | | 442/? [03:04<00:00, 2.40it/s, train/loss=1.380]
Epoch 0: | | 442/? [03:04<00:00, 2.40it/s, train/loss=2.210]
Epoch 0: | | 443/? [03:04<00:00, 2.40it/s, train/loss=2.210]
Epoch 0: | | 443/? [03:04<00:00, 2.40it/s, train/loss=4.530]
Epoch 0: | | 444/? [03:04<00:00, 2.40it/s, train/loss=4.530]
Epoch 0: | | 444/? [03:04<00:00, 2.40it/s, train/loss=1.410]
Epoch 0: | | 445/? [03:04<00:00, 2.41it/s, train/loss=1.410]
Epoch 0: | | 445/? [03:04<00:00, 2.41it/s, train/loss=4.520]
Epoch 0: | | 446/? [03:05<00:00, 2.41it/s, train/loss=4.520]
Epoch 0: | | 446/? [03:05<00:00, 2.41it/s, train/loss=0.731]
Epoch 0: | | 447/? [03:05<00:00, 2.41it/s, train/loss=0.731]
Epoch 0: | | 447/? [03:05<00:00, 2.41it/s, train/loss=4.500]
Epoch 0: | | 448/? [03:05<00:00, 2.41it/s, train/loss=4.500]
Epoch 0: | | 448/? [03:05<00:00, 2.41it/s, train/loss=1.490]
Epoch 0: | | 449/? [03:05<00:00, 2.42it/s, train/loss=1.490]
Epoch 0: | | 449/? [03:05<00:00, 2.42it/s, train/loss=4.470]
Epoch 0: | | 450/? [03:06<00:00, 2.42it/s, train/loss=4.470]
Epoch 0: | | 450/? [03:06<00:00, 2.42it/s, train/loss=3.620]
Epoch 0: | | 451/? [03:07<00:00, 2.41it/s, train/loss=3.620]
Epoch 0: | | 451/? [03:07<00:00, 2.41it/s, train/loss=3.350]
Epoch 0: | | 452/? [03:07<00:00, 2.41it/s, train/loss=3.350]
Epoch 0: | | 452/? [03:07<00:00, 2.41it/s, train/loss=1.390]
Epoch 0: | | 453/? [03:07<00:00, 2.42it/s, train/loss=1.390]
Epoch 0: | | 453/? [03:07<00:00, 2.42it/s, train/loss=4.420]
Epoch 0: | | 454/? [03:07<00:00, 2.42it/s, train/loss=4.420]
Epoch 0: | | 454/? [03:07<00:00, 2.42it/s, train/loss=2.750]
Epoch 0: | | 455/? [03:07<00:00, 2.42it/s, train/loss=2.750]
Epoch 0: | | 455/? [03:07<00:00, 2.42it/s, train/loss=4.400]
Epoch 0: | | 456/? [03:08<00:00, 2.42it/s, train/loss=4.400]
Epoch 0: | | 456/? [03:08<00:00, 2.42it/s, train/loss=1.430]
Epoch 0: | | 457/? [03:08<00:00, 2.43it/s, train/loss=1.430]
Epoch 0: | | 457/? [03:08<00:00, 2.43it/s, train/loss=4.380]
Epoch 0: | | 458/? [03:08<00:00, 2.43it/s, train/loss=4.380]
Epoch 0: | | 458/? [03:08<00:00, 2.43it/s, train/loss=1.900]
Epoch 0: | | 459/? [03:08<00:00, 2.43it/s, train/loss=1.900]
Epoch 0: | | 459/? [03:08<00:00, 2.43it/s, train/loss=4.350]
Epoch 0: | | 460/? [03:09<00:00, 2.43it/s, train/loss=4.350]
Epoch 0: | | 460/? [03:09<00:00, 2.43it/s, train/loss=3.030]
Epoch 0: | | 461/? [03:10<00:00, 2.42it/s, train/loss=3.030]
Epoch 0: | | 461/? [03:10<00:00, 2.42it/s, train/loss=2.120]
Epoch 0: | | 462/? [03:10<00:00, 2.43it/s, train/loss=2.120]
Epoch 0: | | 462/? [03:10<00:00, 2.42it/s, train/loss=1.960]
Epoch 0: | | 463/? [03:10<00:00, 2.43it/s, train/loss=1.960]
Epoch 0: | | 463/? [03:10<00:00, 2.43it/s, train/loss=4.340]
Epoch 0: | | 464/? [03:10<00:00, 2.43it/s, train/loss=4.340]
Epoch 0: | | 464/? [03:10<00:00, 2.43it/s, train/loss=1.650]
Epoch 0: | | 465/? [03:11<00:00, 2.43it/s, train/loss=1.650]
Epoch 0: | | 465/? [03:11<00:00, 2.43it/s, train/loss=4.340]
Epoch 0: | | 466/? [03:11<00:00, 2.43it/s, train/loss=4.340]
Epoch 0: | | 466/? [03:11<00:00, 2.43it/s, train/loss=0.967]
Epoch 0: | | 467/? [03:11<00:00, 2.44it/s, train/loss=0.967]
Epoch 0: | | 467/? [03:11<00:00, 2.44it/s, train/loss=4.320]
Epoch 0: | | 468/? [03:11<00:00, 2.44it/s, train/loss=4.320]
Epoch 0: | | 468/? [03:11<00:00, 2.44it/s, train/loss=3.190]
Epoch 0: | | 469/? [03:11<00:00, 2.44it/s, train/loss=3.190]
Epoch 0: | | 469/? [03:11<00:00, 2.44it/s, train/loss=4.310]
Epoch 0: | | 470/? [03:12<00:00, 2.44it/s, train/loss=4.310]
Epoch 0: | | 470/? [03:12<00:00, 2.44it/s, train/loss=2.530]
Epoch 0: | | 471/? [03:13<00:00, 2.44it/s, train/loss=2.530]
Epoch 0: | | 471/? [03:13<00:00, 2.44it/s, train/loss=2.540]
Epoch 0: | | 472/? [03:13<00:00, 2.44it/s, train/loss=2.540]
Epoch 0: | | 472/? [03:13<00:00, 2.44it/s, train/loss=1.790]
Epoch 0: | | 473/? [03:13<00:00, 2.44it/s, train/loss=1.790]
Epoch 0: | | 473/? [03:13<00:00, 2.44it/s, train/loss=4.330]
Epoch 0: | | 474/? [03:14<00:00, 2.44it/s, train/loss=4.330]
Epoch 0: | | 474/? [03:14<00:00, 2.44it/s, train/loss=3.140]
Epoch 0: | | 475/? [03:14<00:00, 2.45it/s, train/loss=3.140]
Epoch 0: | | 475/? [03:14<00:00, 2.45it/s, train/loss=4.320]
Epoch 0: | | 476/? [03:14<00:00, 2.45it/s, train/loss=4.320]
Epoch 0: | | 476/? [03:14<00:00, 2.45it/s, train/loss=2.120]
Epoch 0: | | 477/? [03:14<00:00, 2.45it/s, train/loss=2.120]
Epoch 0: | | 477/? [03:14<00:00, 2.45it/s, train/loss=4.300]
Epoch 0: | | 478/? [03:15<00:00, 2.45it/s, train/loss=4.300]
Epoch 0: | | 478/? [03:15<00:00, 2.45it/s, train/loss=1.920]
Epoch 0: | | 479/? [03:15<00:00, 2.46it/s, train/loss=1.920]
Epoch 0: | | 479/? [03:15<00:00, 2.46it/s, train/loss=4.280]
Epoch 0: | | 480/? [03:15<00:00, 2.46it/s, train/loss=4.280]
Epoch 0: | | 480/? [03:15<00:00, 2.46it/s, train/loss=2.280]
Epoch 0: | | 481/? [03:16<00:00, 2.45it/s, train/loss=2.280]
Epoch 0: | | 481/? [03:16<00:00, 2.45it/s, train/loss=0.513]
Epoch 0: | | 482/? [03:16<00:00, 2.45it/s, train/loss=0.513]
Epoch 0: | | 482/? [03:16<00:00, 2.45it/s, train/loss=0.849]
Epoch 0: | | 483/? [03:16<00:00, 2.45it/s, train/loss=0.849]
Epoch 0: | | 483/? [03:16<00:00, 2.45it/s, train/loss=4.270]
Epoch 0: | | 484/? [03:17<00:00, 2.45it/s, train/loss=4.270]
Epoch 0: | | 484/? [03:17<00:00, 2.45it/s, train/loss=1.970]
Epoch 0: | | 485/? [03:17<00:00, 2.46it/s, train/loss=1.970]
Epoch 0: | | 485/? [03:17<00:00, 2.46it/s, train/loss=4.250]
Epoch 0: | | 486/? [03:17<00:00, 2.46it/s, train/loss=4.250]
Epoch 0: | | 486/? [03:17<00:00, 2.46it/s, train/loss=1.330]
Epoch 0: | | 487/? [03:17<00:00, 2.46it/s, train/loss=1.330]
Epoch 0: | | 487/? [03:17<00:00, 2.46it/s, train/loss=4.240]
Epoch 0: | | 488/? [03:18<00:00, 2.46it/s, train/loss=4.240]
Epoch 0: | | 488/? [03:18<00:00, 2.46it/s, train/loss=3.980]
Epoch 0: | | 489/? [03:18<00:00, 2.47it/s, train/loss=3.980]
Epoch 0: | | 489/? [03:18<00:00, 2.47it/s, train/loss=4.250]
Epoch 0: | | 490/? [03:18<00:00, 2.47it/s, train/loss=4.250]
Epoch 0: | | 490/? [03:18<00:00, 2.47it/s, train/loss=3.170]
Epoch 0: | | 491/? [03:19<00:00, 2.46it/s, train/loss=3.170]
Epoch 0: | | 491/? [03:19<00:00, 2.46it/s, train/loss=3.520]
Epoch 0: | | 492/? [03:19<00:00, 2.46it/s, train/loss=3.520]
Epoch 0: | | 492/? [03:19<00:00, 2.46it/s, train/loss=1.780]
Epoch 0: | | 493/? [03:19<00:00, 2.47it/s, train/loss=1.780]
Epoch 0: | | 493/? [03:19<00:00, 2.47it/s, train/loss=4.330]
Epoch 0: | | 494/? [03:20<00:00, 2.47it/s, train/loss=4.330]
Epoch 0: | | 494/? [03:20<00:00, 2.46it/s, train/loss=2.840]
Epoch 0: | | 495/? [03:20<00:00, 2.47it/s, train/loss=2.840]
Epoch 0: | | 495/? [03:20<00:00, 2.47it/s, train/loss=4.350]
Epoch 0: | | 496/? [03:20<00:00, 2.47it/s, train/loss=4.350]
Epoch 0: | | 496/? [03:20<00:00, 2.47it/s, train/loss=2.180]
Epoch 0: | | 497/? [03:21<00:00, 2.47it/s, train/loss=2.180]
Epoch 0: | | 497/? [03:21<00:00, 2.47it/s, train/loss=4.350]
Epoch 0: | | 498/? [03:21<00:00, 2.47it/s, train/loss=4.350]
Epoch 0: | | 498/? [03:21<00:00, 2.47it/s, train/loss=0.676]
Epoch 0: | | 499/? [03:21<00:00, 2.48it/s, train/loss=0.676]
Epoch 0: | | 499/? [03:21<00:00, 2.48it/s, train/loss=4.340]
Epoch 0: | | 500/? [03:21<00:00, 2.48it/s, train/loss=4.340]
Epoch 0: | | 500/? [03:21<00:00, 2.48it/s, train/loss=1.350]
Epoch 0: | | 501/? [03:22<00:00, 2.47it/s, train/loss=1.350]
Epoch 0: | | 501/? [03:22<00:00, 2.47it/s, train/loss=1.280]
Epoch 0: | | 502/? [03:23<00:00, 2.47it/s, train/loss=1.280]
Epoch 0: | | 502/? [03:23<00:00, 2.47it/s, train/loss=1.450]
Epoch 0: | | 503/? [03:23<00:00, 2.47it/s, train/loss=1.450]
Epoch 0: | | 503/? [03:23<00:00, 2.47it/s, train/loss=4.360]
Epoch 0: | | 504/? [03:23<00:00, 2.47it/s, train/loss=4.360]
Epoch 0: | | 504/? [03:23<00:00, 2.47it/s, train/loss=2.170]
Epoch 0: | | 505/? [03:23<00:00, 2.48it/s, train/loss=2.170]
Epoch 0: | | 505/? [03:23<00:00, 2.48it/s, train/loss=4.350]
Epoch 0: | | 506/? [03:24<00:00, 2.48it/s, train/loss=4.350]
Epoch 0: | | 506/? [03:24<00:00, 2.48it/s, train/loss=1.810]
Epoch 0: | | 507/? [03:24<00:00, 2.48it/s, train/loss=1.810]
Epoch 0: | | 507/? [03:24<00:00, 2.48it/s, train/loss=4.340]
Epoch 0: | | 508/? [03:24<00:00, 2.48it/s, train/loss=4.340]
Epoch 0: | | 508/? [03:24<00:00, 2.48it/s, train/loss=2.820]
Epoch 0: | | 509/? [03:24<00:00, 2.49it/s, train/loss=2.820]
Epoch 0: | | 509/? [03:24<00:00, 2.49it/s, train/loss=4.320]
Epoch 0: | | 510/? [03:25<00:00, 2.49it/s, train/loss=4.320]
Epoch 0: | | 510/? [03:25<00:00, 2.49it/s, train/loss=1.890]
Epoch 0: | | 511/? [03:25<00:00, 2.48it/s, train/loss=1.890]
Epoch 0: | | 511/? [03:26<00:00, 2.48it/s, train/loss=1.120]
Epoch 0: | | 512/? [03:26<00:00, 2.48it/s, train/loss=1.120]
Epoch 0: | | 512/? [03:26<00:00, 2.48it/s, train/loss=2.630]
Epoch 0: | | 513/? [03:26<00:00, 2.49it/s, train/loss=2.630]
Epoch 0: | | 513/? [03:26<00:00, 2.49it/s, train/loss=4.340]
Epoch 0: | | 514/? [03:26<00:00, 2.49it/s, train/loss=4.340]
Epoch 0: | | 514/? [03:26<00:00, 2.49it/s, train/loss=0.942]
Epoch 0: | | 515/? [03:26<00:00, 2.49it/s, train/loss=0.942]
Epoch 0: | | 515/? [03:26<00:00, 2.49it/s, train/loss=4.340]
Epoch 0: | | 516/? [03:27<00:00, 2.49it/s, train/loss=4.340]
Epoch 0: | | 516/? [03:27<00:00, 2.49it/s, train/loss=1.110]
Epoch 0: | | 517/? [03:27<00:00, 2.49it/s, train/loss=1.110]
Epoch 0: | | 517/? [03:27<00:00, 2.49it/s, train/loss=4.320]
Epoch 0: | | 518/? [03:27<00:00, 2.49it/s, train/loss=4.320]
Epoch 0: | | 518/? [03:27<00:00, 2.49it/s, train/loss=4.760]
Epoch 0: | | 519/? [03:27<00:00, 2.50it/s, train/loss=4.760]
Epoch 0: | | 519/? [03:27<00:00, 2.50it/s, train/loss=4.300]
Epoch 0: | | 520/? [03:28<00:00, 2.50it/s, train/loss=4.300]
Epoch 0: | | 520/? [03:28<00:00, 2.50it/s, train/loss=1.390]
Epoch 0: | | 521/? [03:29<00:00, 2.49it/s, train/loss=1.390]
Epoch 0: | | 521/? [03:29<00:00, 2.49it/s, train/loss=1.430]
Epoch 0: | | 522/? [03:29<00:00, 2.49it/s, train/loss=1.430]
Epoch 0: | | 522/? [03:29<00:00, 2.49it/s, train/loss=1.370]
Epoch 0: | | 523/? [03:29<00:00, 2.50it/s, train/loss=1.370]
Epoch 0: | | 523/? [03:29<00:00, 2.50it/s, train/loss=4.260]
Epoch 0: | | 524/? [03:29<00:00, 2.50it/s, train/loss=4.260]
Epoch 0: | | 524/? [03:29<00:00, 2.50it/s, train/loss=1.990]
Epoch 0: | | 525/? [03:29<00:00, 2.50it/s, train/loss=1.990]
Epoch 0: | | 525/? [03:29<00:00, 2.50it/s, train/loss=4.240]
Epoch 0: | | 526/? [03:30<00:00, 2.50it/s, train/loss=4.240]
Epoch 0: | | 526/? [03:30<00:00, 2.50it/s, train/loss=1.040]
Epoch 0: | | 527/? [03:30<00:00, 2.50it/s, train/loss=1.040]
Epoch 0: | | 527/? [03:30<00:00, 2.50it/s, train/loss=4.210]
Epoch 0: | | 528/? [03:30<00:00, 2.50it/s, train/loss=4.210]
Epoch 0: | | 528/? [03:30<00:00, 2.50it/s, train/loss=1.550]
Epoch 0: | | 529/? [03:30<00:00, 2.51it/s, train/loss=1.550]
Epoch 0: | | 529/? [03:30<00:00, 2.51it/s, train/loss=4.190]
Epoch 0: | | 530/? [03:31<00:00, 2.51it/s, train/loss=4.190]
Epoch 0: | | 530/? [03:31<00:00, 2.51it/s, train/loss=2.190]
Epoch 0: | | 531/? [03:32<00:00, 2.50it/s, train/loss=2.190]
Epoch 0: | | 531/? [03:32<00:00, 2.50it/s, train/loss=2.480]
Epoch 0: | | 532/? [03:32<00:00, 2.50it/s, train/loss=2.480]
Epoch 0: | | 532/? [03:32<00:00, 2.50it/s, train/loss=3.060]
Epoch 0: | | 533/? [03:32<00:00, 2.51it/s, train/loss=3.060]
Epoch 0: | | 533/? [03:32<00:00, 2.51it/s, train/loss=4.170]
Epoch 0: | | 534/? [03:33<00:00, 2.51it/s, train/loss=4.170]
Epoch 0: | | 534/? [03:33<00:00, 2.51it/s, train/loss=1.580]
Epoch 0: | | 535/? [03:33<00:00, 2.51it/s, train/loss=1.580]
Epoch 0: | | 535/? [03:33<00:00, 2.51it/s, train/loss=4.150]
Epoch 0: | | 536/? [03:33<00:00, 2.51it/s, train/loss=4.150]
Epoch 0: | | 536/? [03:33<00:00, 2.51it/s, train/loss=2.330]
Epoch 0: | | 537/? [03:33<00:00, 2.51it/s, train/loss=2.330]
Epoch 0: | | 537/? [03:33<00:00, 2.51it/s, train/loss=4.130]
Epoch 0: | | 538/? [03:33<00:00, 2.51it/s, train/loss=4.130]
Epoch 0: | | 538/? [03:33<00:00, 2.51it/s, train/loss=1.740]
Epoch 0: | | 539/? [03:34<00:00, 2.52it/s, train/loss=1.740]
Epoch 0: | | 539/? [03:34<00:00, 2.52it/s, train/loss=4.120]
Epoch 0: | | 540/? [03:34<00:00, 2.52it/s, train/loss=4.120]
Epoch 0: | | 540/? [03:34<00:00, 2.52it/s, train/loss=2.130]
Epoch 0: | | 541/? [03:35<00:00, 2.51it/s, train/loss=2.130]
Epoch 0: | | 541/? [03:35<00:00, 2.51it/s, train/loss=2.980]
Epoch 0: | | 542/? [03:35<00:00, 2.51it/s, train/loss=2.980]
Epoch 0: | | 542/? [03:35<00:00, 2.51it/s, train/loss=1.930]
Epoch 0: | | 543/? [03:35<00:00, 2.52it/s, train/loss=1.930]
Epoch 0: | | 543/? [03:35<00:00, 2.52it/s, train/loss=4.130]
Epoch 0: | | 544/? [03:36<00:00, 2.52it/s, train/loss=4.130]
Epoch 0: | | 544/? [03:36<00:00, 2.52it/s, train/loss=2.970]
Epoch 0: | | 545/? [03:36<00:00, 2.52it/s, train/loss=2.970]
Epoch 0: | | 545/? [03:36<00:00, 2.52it/s, train/loss=4.130]
Epoch 0: | | 546/? [03:36<00:00, 2.52it/s, train/loss=4.130]
Epoch 0: | | 546/? [03:36<00:00, 2.52it/s, train/loss=1.780]
Epoch 0: | | 547/? [03:36<00:00, 2.52it/s, train/loss=1.780]
Epoch 0: | | 547/? [03:36<00:00, 2.52it/s, train/loss=4.130]
Epoch 0: | | 548/? [03:37<00:00, 2.52it/s, train/loss=4.130]
Epoch 0: | | 548/? [03:37<00:00, 2.52it/s, train/loss=2.270]
Epoch 0: | | 549/? [03:37<00:00, 2.53it/s, train/loss=2.270]
Epoch 0: | | 549/? [03:37<00:00, 2.53it/s, train/loss=4.110]
Epoch 0: | | 550/? [03:37<00:00, 2.53it/s, train/loss=4.110]
Epoch 0: | | 550/? [03:37<00:00, 2.53it/s, train/loss=2.440]
Epoch 0: | | 551/? [03:38<00:00, 2.52it/s, train/loss=2.440]
Epoch 0: | | 551/? [03:38<00:00, 2.52it/s, train/loss=2.390]
Epoch 0: | | 552/? [03:38<00:00, 2.52it/s, train/loss=2.390]
Epoch 0: | | 552/? [03:38<00:00, 2.52it/s, train/loss=1.130]
Epoch 0: | | 553/? [03:38<00:00, 2.53it/s, train/loss=1.130]
Epoch 0: | | 553/? [03:38<00:00, 2.53it/s, train/loss=4.110]
Epoch 0: | | 554/? [03:39<00:00, 2.53it/s, train/loss=4.110]
Epoch 0: | | 554/? [03:39<00:00, 2.53it/s, train/loss=0.801]
Epoch 0: | | 555/? [03:39<00:00, 2.53it/s, train/loss=0.801]
Epoch 0: | | 555/? [03:39<00:00, 2.53it/s, train/loss=4.090]
Epoch 0: | | 556/? [03:39<00:00, 2.53it/s, train/loss=4.090]
Epoch 0: | | 556/? [03:39<00:00, 2.53it/s, train/loss=3.380]
Epoch 0: | | 557/? [03:39<00:00, 2.53it/s, train/loss=3.380]
Epoch 0: | | 557/? [03:39<00:00, 2.53it/s, train/loss=4.070]
Epoch 0: | | 558/? [03:40<00:00, 2.53it/s, train/loss=4.070]
Epoch 0: | | 558/? [03:40<00:00, 2.53it/s, train/loss=2.010]
Epoch 0: | | 559/? [03:40<00:00, 2.54it/s, train/loss=2.010]
Epoch 0: | | 559/? [03:40<00:00, 2.54it/s, train/loss=4.050]
Epoch 0: | | 560/? [03:40<00:00, 2.54it/s, train/loss=4.050]
Epoch 0: | | 560/? [03:40<00:00, 2.54it/s, train/loss=1.340]
Epoch 0: | | 561/? [03:41<00:00, 2.53it/s, train/loss=1.340]
Epoch 0: | | 561/? [03:41<00:00, 2.53it/s, train/loss=2.310]
Epoch 0: | | 562/? [03:42<00:00, 2.53it/s, train/loss=2.310]
Epoch 0: | | 562/? [03:42<00:00, 2.53it/s, train/loss=0.956]
Epoch 0: | | 563/? [03:42<00:00, 2.53it/s, train/loss=0.956]
Epoch 0: | | 563/? [03:42<00:00, 2.53it/s, train/loss=4.030]
Epoch 0: | | 564/? [03:42<00:00, 2.53it/s, train/loss=4.030]
Epoch 0: | | 564/? [03:42<00:00, 2.53it/s, train/loss=3.390]
Epoch 0: | | 565/? [03:42<00:00, 2.54it/s, train/loss=3.390]
Epoch 0: | | 565/? [03:42<00:00, 2.54it/s, train/loss=4.010]
Epoch 0: | | 566/? [03:43<00:00, 2.54it/s, train/loss=4.010]
Epoch 0: | | 566/? [03:43<00:00, 2.54it/s, train/loss=2.930]
Epoch 0: | | 567/? [03:43<00:00, 2.54it/s, train/loss=2.930]
Epoch 0: | | 567/? [03:43<00:00, 2.54it/s, train/loss=4.000]
Epoch 0: | | 568/? [03:43<00:00, 2.54it/s, train/loss=4.000]
Epoch 0: | | 568/? [03:43<00:00, 2.54it/s, train/loss=2.650]
Epoch 0: | | 569/? [03:43<00:00, 2.55it/s, train/loss=2.650]
Epoch 0: | | 569/? [03:43<00:00, 2.55it/s, train/loss=3.990]
Epoch 0: | | 570/? [03:43<00:00, 2.55it/s, train/loss=3.990]
Epoch 0: | | 570/? [03:43<00:00, 2.55it/s, train/loss=0.636]
Epoch 0: | | 571/? [03:44<00:00, 2.54it/s, train/loss=0.636]
Epoch 0: | | 571/? [03:44<00:00, 2.54it/s, train/loss=1.320]
Epoch 0: | | 572/? [03:45<00:00, 2.54it/s, train/loss=1.320]
Epoch 0: | | 572/? [03:45<00:00, 2.54it/s, train/loss=0.937]
Epoch 0: | | 573/? [03:45<00:00, 2.54it/s, train/loss=0.937]
Epoch 0: | | 573/? [03:45<00:00, 2.54it/s, train/loss=4.000]
Epoch 0: | | 574/? [03:45<00:00, 2.54it/s, train/loss=4.000]
Epoch 0: | | 574/? [03:45<00:00, 2.54it/s, train/loss=0.672]
Epoch 0: | | 575/? [03:45<00:00, 2.55it/s, train/loss=0.672]
Epoch 0: | | 575/? [03:45<00:00, 2.55it/s, train/loss=3.980]
Epoch 0: | | 576/? [03:46<00:00, 2.55it/s, train/loss=3.980]
Epoch 0: | | 576/? [03:46<00:00, 2.55it/s, train/loss=2.170]
Epoch 0: | | 577/? [03:46<00:00, 2.55it/s, train/loss=2.170]
Epoch 0: | | 577/? [03:46<00:00, 2.55it/s, train/loss=3.970]
Epoch 0: | | 578/? [03:46<00:00, 2.55it/s, train/loss=3.970]
Epoch 0: | | 578/? [03:46<00:00, 2.55it/s, train/loss=1.480]
Epoch 0: | | 579/? [03:46<00:00, 2.55it/s, train/loss=1.480]
Epoch 0: | | 579/? [03:46<00:00, 2.55it/s, train/loss=3.960]
Epoch 0: | | 580/? [03:47<00:00, 2.55it/s, train/loss=3.960]
Epoch 0: | | 580/? [03:47<00:00, 2.55it/s, train/loss=3.060]
Epoch 0: | | 581/? [03:47<00:00, 2.55it/s, train/loss=3.060]
Epoch 0: | | 581/? [03:48<00:00, 2.55it/s, train/loss=2.920]
Epoch 0: | | 582/? [03:48<00:00, 2.55it/s, train/loss=2.920]
Epoch 0: | | 582/? [03:48<00:00, 2.55it/s, train/loss=0.917]
Epoch 0: | | 583/? [03:48<00:00, 2.55it/s, train/loss=0.917]
Epoch 0: | | 583/? [03:48<00:00, 2.55it/s, train/loss=3.960]
Epoch 0: | | 584/? [03:48<00:00, 2.55it/s, train/loss=3.960]
Epoch 0: | | 584/? [03:48<00:00, 2.55it/s, train/loss=2.450]
Epoch 0: | | 585/? [03:49<00:00, 2.55it/s, train/loss=2.450]
Epoch 0: | | 585/? [03:49<00:00, 2.55it/s, train/loss=3.950]
Epoch 0: | | 586/? [03:49<00:00, 2.55it/s, train/loss=3.950]
Epoch 0: | | 586/? [03:49<00:00, 2.55it/s, train/loss=2.180]
Epoch 0: | | 587/? [03:49<00:00, 2.56it/s, train/loss=2.180]
Epoch 0: | | 587/? [03:49<00:00, 2.56it/s, train/loss=3.920]
Epoch 0: | | 588/? [03:49<00:00, 2.56it/s, train/loss=3.920]
Epoch 0: | | 588/? [03:49<00:00, 2.56it/s, train/loss=2.390]
Epoch 0: | | 589/? [03:49<00:00, 2.56it/s, train/loss=2.390]
Epoch 0: | | 589/? [03:49<00:00, 2.56it/s, train/loss=3.920]
Epoch 0: | | 590/? [03:50<00:00, 2.56it/s, train/loss=3.920]
Epoch 0: | | 590/? [03:50<00:00, 2.56it/s, train/loss=3.030]
Epoch 0: | | 591/? [03:51<00:00, 2.56it/s, train/loss=3.030]
Epoch 0: | | 591/? [03:51<00:00, 2.56it/s, train/loss=1.200]
Epoch 0: | | 592/? [03:51<00:00, 2.56it/s, train/loss=1.200]
Epoch 0: | | 592/? [03:51<00:00, 2.56it/s, train/loss=0.798]
Epoch 0: | | 593/? [03:51<00:00, 2.56it/s, train/loss=0.798]
Epoch 0: | | 593/? [03:51<00:00, 2.56it/s, train/loss=3.990]
Epoch 0: | | 594/? [03:52<00:00, 2.56it/s, train/loss=3.990]
Epoch 0: | | 594/? [03:52<00:00, 2.56it/s, train/loss=1.160]
Epoch 0: | | 595/? [03:52<00:00, 2.56it/s, train/loss=1.160]
Epoch 0: | | 595/? [03:52<00:00, 2.56it/s, train/loss=4.010]
Epoch 0: | | 596/? [03:52<00:00, 2.56it/s, train/loss=4.010]
Epoch 0: | | 596/? [03:52<00:00, 2.56it/s, train/loss=3.640]
Epoch 0: | | 597/? [03:52<00:00, 2.57it/s, train/loss=3.640]
Epoch 0: | | 597/? [03:52<00:00, 2.57it/s, train/loss=4.010]
Epoch 0: | | 598/? [03:53<00:00, 2.57it/s, train/loss=4.010]
Epoch 0: | | 598/? [03:53<00:00, 2.57it/s, train/loss=2.290]
Epoch 0: | | 599/? [03:53<00:00, 2.57it/s, train/loss=2.290]
Epoch 0: | | 599/? [03:53<00:00, 2.57it/s, train/loss=4.020]
Epoch 0: | | 600/? [03:53<00:00, 2.57it/s, train/loss=4.020]
Epoch 0: | | 600/? [03:53<00:00, 2.57it/s, train/loss=2.900]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:04, 8.54it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:04, 8.56it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:04, 8.57it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:04, 8.60it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:04, 8.62it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:03, 8.65it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:03, 8.68it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:03, 8.72it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:01<00:03, 8.75it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:01<00:03, 8.82it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:01<00:03, 8.86it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:03, 8.55it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:03, 8.54it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:03, 8.59it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 8.61it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 8.62it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:02, 8.63it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:02<00:02, 8.66it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:02<00:02, 8.69it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:02<00:02, 8.69it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:02<00:02, 8.71it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:02<00:02, 8.72it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:02<00:01, 8.75it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 8.78it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 8.78it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 8.80it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:03<00:01, 8.81it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:03<00:01, 8.82it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:03<00:01, 8.82it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:03<00:01, 8.83it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:03<00:01, 8.85it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:03<00:00, 8.86it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:03<00:00, 8.86it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:03<00:00, 8.88it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 8.87it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:04<00:00, 8.84it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:04<00:00, 8.83it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:04<00:00, 8.83it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:04<00:00, 8.83it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00, 8.82it/s][A
[A
Epoch 0: | | 600/? [04:04<00:00, 2.46it/s, train/loss=2.900]
Epoch 0: | | 601/? [04:19<00:00, 2.31it/s, train/loss=2.900]
Epoch 0: | | 601/? [04:19<00:00, 2.31it/s, train/loss=1.340]
Epoch 0: | | 602/? [04:19<00:00, 2.32it/s, train/loss=1.340]
Epoch 0: | | 602/? [04:20<00:00, 2.32it/s, train/loss=1.860]
Epoch 0: | | 603/? [04:20<00:00, 2.32it/s, train/loss=1.860]
Epoch 0: | | 603/? [04:20<00:00, 2.32it/s, train/loss=4.060]
Epoch 0: | | 604/? [04:20<00:00, 2.32it/s, train/loss=4.060]
Epoch 0: | | 604/? [04:20<00:00, 2.32it/s, train/loss=2.570]
Epoch 0: | | 605/? [04:20<00:00, 2.32it/s, train/loss=2.570]
Epoch 0: | | 605/? [04:20<00:00, 2.32it/s, train/loss=4.070]
Epoch 0: | | 606/? [04:20<00:00, 2.32it/s, train/loss=4.070]
Epoch 0: | | 606/? [04:20<00:00, 2.32it/s, train/loss=3.590]
Epoch 0: | | 607/? [04:20<00:00, 2.33it/s, train/loss=3.590]
Epoch 0: | | 607/? [04:20<00:00, 2.33it/s, train/loss=4.070]
Epoch 0: | | 608/? [04:21<00:00, 2.33it/s, train/loss=4.070]
Epoch 0: | | 608/? [04:21<00:00, 2.33it/s, train/loss=3.050]
Epoch 0: | | 609/? [04:21<00:00, 2.33it/s, train/loss=3.050]
Epoch 0: | | 609/? [04:21<00:00, 2.33it/s, train/loss=4.060]
Epoch 0: | | 610/? [04:21<00:00, 2.33it/s, train/loss=4.060]
Epoch 0: | | 610/? [04:21<00:00, 2.33it/s, train/loss=1.530]
Epoch 0: | | 611/? [04:22<00:00, 2.33it/s, train/loss=1.530]
Epoch 0: | | 611/? [04:22<00:00, 2.32it/s, train/loss=1.450]
Epoch 0: | | 612/? [04:23<00:00, 2.33it/s, train/loss=1.450]
Epoch 0: | | 612/? [04:23<00:00, 2.33it/s, train/loss=1.410]
Epoch 0: | | 613/? [04:23<00:00, 2.33it/s, train/loss=1.410]
Epoch 0: | | 613/? [04:23<00:00, 2.33it/s, train/loss=4.070]
Epoch 0: | | 614/? [04:23<00:00, 2.33it/s, train/loss=4.070]
Epoch 0: | | 614/? [04:23<00:00, 2.33it/s, train/loss=2.290]
Epoch 0: | | 615/? [04:23<00:00, 2.33it/s, train/loss=2.290]
Epoch 0: | | 615/? [04:23<00:00, 2.33it/s, train/loss=4.050]
Epoch 0: | | 616/? [04:24<00:00, 2.33it/s, train/loss=4.050]
Epoch 0: | | 616/? [04:24<00:00, 2.33it/s, train/loss=2.550]
Epoch 0: | | 617/? [04:24<00:00, 2.34it/s, train/loss=2.550]
Epoch 0: | | 617/? [04:24<00:00, 2.34it/s, train/loss=4.010]
Epoch 0: | | 618/? [04:24<00:00, 2.34it/s, train/loss=4.010]
Epoch 0: | | 618/? [04:24<00:00, 2.34it/s, train/loss=2.220]
Epoch 0: | | 619/? [04:24<00:00, 2.34it/s, train/loss=2.220]
Epoch 0: | | 619/? [04:24<00:00, 2.34it/s, train/loss=3.990]
Epoch 0: | | 620/? [04:25<00:00, 2.34it/s, train/loss=3.990]
Epoch 0: | | 620/? [04:25<00:00, 2.34it/s, train/loss=0.898]
Epoch 0: | | 621/? [04:25<00:00, 2.33it/s, train/loss=0.898]
Epoch 0: | | 621/? [04:26<00:00, 2.33it/s, train/loss=1.590]
Epoch 0: | | 622/? [04:26<00:00, 2.34it/s, train/loss=1.590]
Epoch 0: | | 622/? [04:26<00:00, 2.34it/s, train/loss=0.873]
Epoch 0: | | 623/? [04:26<00:00, 2.34it/s, train/loss=0.873]
Epoch 0: | | 623/? [04:26<00:00, 2.34it/s, train/loss=3.970]
Epoch 0: | | 624/? [04:26<00:00, 2.34it/s, train/loss=3.970]
Epoch 0: | | 624/? [04:26<00:00, 2.34it/s, train/loss=2.080]
Epoch 0: | | 625/? [04:26<00:00, 2.34it/s, train/loss=2.080]
Epoch 0: | | 625/? [04:26<00:00, 2.34it/s, train/loss=3.940]
Epoch 0: | | 626/? [04:27<00:00, 2.34it/s, train/loss=3.940]
Epoch 0: | | 626/? [04:27<00:00, 2.34it/s, train/loss=2.700]
Epoch 0: | | 627/? [04:27<00:00, 2.35it/s, train/loss=2.700]
Epoch 0: | | 627/? [04:27<00:00, 2.35it/s, train/loss=3.920]
Epoch 0: | | 628/? [04:27<00:00, 2.35it/s, train/loss=3.920]
Epoch 0: | | 628/? [04:27<00:00, 2.35it/s, train/loss=1.280]
Epoch 0: | | 629/? [04:27<00:00, 2.35it/s, train/loss=1.280]
Epoch 0: | | 629/? [04:27<00:00, 2.35it/s, train/loss=3.910]
Epoch 0: | | 630/? [04:28<00:00, 2.35it/s, train/loss=3.910]
Epoch 0: | | 630/? [04:28<00:00, 2.35it/s, train/loss=1.190]
Epoch 0: | | 631/? [04:29<00:00, 2.35it/s, train/loss=1.190]
Epoch 0: | | 631/? [04:29<00:00, 2.34it/s, train/loss=0.802]
Epoch 0: | | 632/? [04:29<00:00, 2.35it/s, train/loss=0.802]
Epoch 0: | | 632/? [04:29<00:00, 2.35it/s, train/loss=1.520]
Epoch 0: | | 633/? [04:29<00:00, 2.35it/s, train/loss=1.520]
Epoch 0: | | 633/? [04:29<00:00, 2.35it/s, train/loss=3.940]
Epoch 0: | | 634/? [04:29<00:00, 2.35it/s, train/loss=3.940]
Epoch 0: | | 634/? [04:29<00:00, 2.35it/s, train/loss=3.810]
Epoch 0: | | 635/? [04:29<00:00, 2.35it/s, train/loss=3.810]
Epoch 0: | | 635/? [04:29<00:00, 2.35it/s, train/loss=3.930]
Epoch 0: | | 636/? [04:30<00:00, 2.35it/s, train/loss=3.930]
Epoch 0: | | 636/? [04:30<00:00, 2.35it/s, train/loss=2.680]
Epoch 0: | | 637/? [04:30<00:00, 2.36it/s, train/loss=2.680]
Epoch 0: | | 637/? [04:30<00:00, 2.36it/s, train/loss=3.910]
Epoch 0: | | 638/? [04:30<00:00, 2.36it/s, train/loss=3.910]
Epoch 0: | | 638/? [04:30<00:00, 2.36it/s, train/loss=2.430]
Epoch 0: | | 639/? [04:30<00:00, 2.36it/s, train/loss=2.430]
Epoch 0: | | 639/? [04:30<00:00, 2.36it/s, train/loss=3.890]
Epoch 0: | | 640/? [04:31<00:00, 2.36it/s, train/loss=3.890]
Epoch 0: | | 640/? [04:31<00:00, 2.36it/s, train/loss=3.000]
Epoch 0: | | 641/? [04:32<00:00, 2.36it/s, train/loss=3.000]
Epoch 0: | | 641/? [04:32<00:00, 2.35it/s, train/loss=0.737]
Epoch 0: | | 642/? [04:32<00:00, 2.36it/s, train/loss=0.737]
Epoch 0: | | 642/? [04:32<00:00, 2.36it/s, train/loss=1.870]
Epoch 0: | | 643/? [04:32<00:00, 2.36it/s, train/loss=1.870]
Epoch 0: | | 643/? [04:32<00:00, 2.36it/s, train/loss=3.870]
Epoch 0: | | 644/? [04:33<00:00, 2.36it/s, train/loss=3.870]
Epoch 0: | | 644/? [04:33<00:00, 2.36it/s, train/loss=2.900]
Epoch 0: | | 645/? [04:33<00:00, 2.36it/s, train/loss=2.900]
Epoch 0: | | 645/? [04:33<00:00, 2.36it/s, train/loss=3.850]
Epoch 0: | | 646/? [04:33<00:00, 2.36it/s, train/loss=3.850]
Epoch 0: | | 646/? [04:33<00:00, 2.36it/s, train/loss=2.790]
Epoch 0: | | 647/? [04:33<00:00, 2.37it/s, train/loss=2.790]
Epoch 0: | | 647/? [04:33<00:00, 2.37it/s, train/loss=3.830]
Epoch 0: | | 648/? [04:33<00:00, 2.37it/s, train/loss=3.830]
Epoch 0: | | 648/? [04:33<00:00, 2.37it/s, train/loss=3.090]
Epoch 0: | | 649/? [04:33<00:00, 2.37it/s, train/loss=3.090]
Epoch 0: | | 649/? [04:34<00:00, 2.37it/s, train/loss=3.810]
Epoch 0: | | 650/? [04:34<00:00, 2.37it/s, train/loss=3.810]
Epoch 0: | | 650/? [04:34<00:00, 2.37it/s, train/loss=5.800]
Epoch 0: | | 651/? [04:35<00:00, 2.36it/s, train/loss=5.800]
Epoch 0: | | 651/? [04:35<00:00, 2.36it/s, train/loss=1.430]
Epoch 0: | | 652/? [04:35<00:00, 2.36it/s, train/loss=1.430]
Epoch 0: | | 652/? [04:35<00:00, 2.36it/s, train/loss=0.542]
Epoch 0: | | 653/? [04:35<00:00, 2.37it/s, train/loss=0.542]
Epoch 0: | | 653/? [04:35<00:00, 2.37it/s, train/loss=3.840]
Epoch 0: | | 654/? [04:36<00:00, 2.37it/s, train/loss=3.840]
Epoch 0: | | 654/? [04:36<00:00, 2.37it/s, train/loss=1.890]
Epoch 0: | | 655/? [04:36<00:00, 2.37it/s, train/loss=1.890]
Epoch 0: | | 655/? [04:36<00:00, 2.37it/s, train/loss=3.850]
Epoch 0: | | 656/? [04:36<00:00, 2.37it/s, train/loss=3.850]
Epoch 0: | | 656/? [04:36<00:00, 2.37it/s, train/loss=1.940]
Epoch 0: | | 657/? [04:36<00:00, 2.37it/s, train/loss=1.940]
Epoch 0: | | 657/? [04:36<00:00, 2.37it/s, train/loss=3.850]
Epoch 0: | | 658/? [04:37<00:00, 2.37it/s, train/loss=3.850]
Epoch 0: | | 658/? [04:37<00:00, 2.37it/s, train/loss=2.310]
Epoch 0: | | 659/? [04:37<00:00, 2.38it/s, train/loss=2.310]
Epoch 0: | | 659/? [04:37<00:00, 2.38it/s, train/loss=3.850]
Epoch 0: | | 660/? [04:37<00:00, 2.38it/s, train/loss=3.850]
Epoch 0: | | 660/? [04:37<00:00, 2.38it/s, train/loss=3.240]
Epoch 0: | | 661/? [04:38<00:00, 2.37it/s, train/loss=3.240]
Epoch 0: | | 661/? [04:38<00:00, 2.37it/s, train/loss=1.370]
Epoch 0: | | 662/? [04:38<00:00, 2.37it/s, train/loss=1.370]
Epoch 0: | | 662/? [04:38<00:00, 2.37it/s, train/loss=0.638]
Epoch 0: | | 663/? [04:38<00:00, 2.38it/s, train/loss=0.638]
Epoch 0: | | 663/? [04:38<00:00, 2.38it/s, train/loss=3.890]
Epoch 0: | | 664/? [04:39<00:00, 2.38it/s, train/loss=3.890]
Epoch 0: | | 664/? [04:39<00:00, 2.38it/s, train/loss=2.390]
Epoch 0: | | 665/? [04:39<00:00, 2.38it/s, train/loss=2.390]
Epoch 0: | | 665/? [04:39<00:00, 2.38it/s, train/loss=3.900]
Epoch 0: | | 666/? [04:39<00:00, 2.38it/s, train/loss=3.900]
Epoch 0: | | 666/? [04:39<00:00, 2.38it/s, train/loss=1.330]
Epoch 0: | | 667/? [04:39<00:00, 2.38it/s, train/loss=1.330]
Epoch 0: | | 667/? [04:39<00:00, 2.38it/s, train/loss=3.870]
Epoch 0: | | 668/? [04:40<00:00, 2.38it/s, train/loss=3.870]
Epoch 0: | | 668/? [04:40<00:00, 2.38it/s, train/loss=2.550]
Epoch 0: | | 669/? [04:40<00:00, 2.39it/s, train/loss=2.550]
Epoch 0: | | 669/? [04:40<00:00, 2.39it/s, train/loss=3.870]
Epoch 0: | | 670/? [04:40<00:00, 2.39it/s, train/loss=3.870]
Epoch 0: | | 670/? [04:40<00:00, 2.39it/s, train/loss=1.670]
Epoch 0: | | 671/? [04:41<00:00, 2.38it/s, train/loss=1.670]
Epoch 0: | | 671/? [04:41<00:00, 2.38it/s, train/loss=0.788]
Epoch 0: | | 672/? [04:41<00:00, 2.38it/s, train/loss=0.788]
Epoch 0: | | 672/? [04:42<00:00, 2.38it/s, train/loss=1.160]
Epoch 0: | | 673/? [04:42<00:00, 2.39it/s, train/loss=1.160]
Epoch 0: | | 673/? [04:42<00:00, 2.39it/s, train/loss=3.890]
Epoch 0: | | 674/? [04:42<00:00, 2.39it/s, train/loss=3.890]
Epoch 0: | | 674/? [04:42<00:00, 2.39it/s, train/loss=1.260]
Epoch 0: | | 675/? [04:42<00:00, 2.39it/s, train/loss=1.260]
Epoch 0: | | 675/? [04:42<00:00, 2.39it/s, train/loss=3.880]
Epoch 0: | | 676/? [04:42<00:00, 2.39it/s, train/loss=3.880]
Epoch 0: | | 676/? [04:42<00:00, 2.39it/s, train/loss=3.090]
Epoch 0: | | 677/? [04:43<00:00, 2.39it/s, train/loss=3.090]
Epoch 0: | | 677/? [04:43<00:00, 2.39it/s, train/loss=3.870]
Epoch 0: | | 678/? [04:43<00:00, 2.39it/s, train/loss=3.870]
Epoch 0: | | 678/? [04:43<00:00, 2.39it/s, train/loss=3.090]
Epoch 0: | | 679/? [04:43<00:00, 2.40it/s, train/loss=3.090]
Epoch 0: | | 679/? [04:43<00:00, 2.40it/s, train/loss=3.850]
Epoch 0: | | 680/? [04:43<00:00, 2.40it/s, train/loss=3.850]
Epoch 0: | | 680/? [04:43<00:00, 2.40it/s, train/loss=2.110]
Epoch 0: | | 681/? [04:44<00:00, 2.39it/s, train/loss=2.110]
Epoch 0: | | 681/? [04:44<00:00, 2.39it/s, train/loss=0.638]
Epoch 0: | | 682/? [04:45<00:00, 2.39it/s, train/loss=0.638]
Epoch 0: | | 682/? [04:45<00:00, 2.39it/s, train/loss=1.190]
Epoch 0: | | 683/? [04:45<00:00, 2.39it/s, train/loss=1.190]
Epoch 0: | | 683/? [04:45<00:00, 2.39it/s, train/loss=3.870]
Epoch 0: | | 684/? [04:45<00:00, 2.40it/s, train/loss=3.870]
Epoch 0: | | 684/? [04:45<00:00, 2.40it/s, train/loss=2.190]
Epoch 0: | | 685/? [04:45<00:00, 2.40it/s, train/loss=2.190]
Epoch 0: | | 685/? [04:45<00:00, 2.40it/s, train/loss=3.850]
Epoch 0: | | 686/? [04:46<00:00, 2.40it/s, train/loss=3.850]
Epoch 0: | | 686/? [04:46<00:00, 2.40it/s, train/loss=2.970]
Epoch 0: | | 687/? [04:46<00:00, 2.40it/s, train/loss=2.970]
Epoch 0: | | 687/? [04:46<00:00, 2.40it/s, train/loss=3.830]
Epoch 0: | | 688/? [04:46<00:00, 2.40it/s, train/loss=3.830]
Epoch 0: | | 688/? [04:46<00:00, 2.40it/s, train/loss=3.460]
Epoch 0: | | 689/? [04:46<00:00, 2.40it/s, train/loss=3.460]
Epoch 0: | | 689/? [04:46<00:00, 2.40it/s, train/loss=3.830]
Epoch 0: | | 690/? [04:46<00:00, 2.40it/s, train/loss=3.830]
Epoch 0: | | 690/? [04:46<00:00, 2.40it/s, train/loss=3.190]
Epoch 0: | | 691/? [04:47<00:00, 2.40it/s, train/loss=3.190]
Epoch 0: | | 691/? [04:47<00:00, 2.40it/s, train/loss=5.260]
Epoch 0: | | 692/? [04:48<00:00, 2.40it/s, train/loss=5.260]
Epoch 0: | | 692/? [04:48<00:00, 2.40it/s, train/loss=1.940]
Epoch 0: | | 693/? [04:48<00:00, 2.40it/s, train/loss=1.940]
Epoch 0: | | 693/? [04:48<00:00, 2.40it/s, train/loss=3.870]
Epoch 0: | | 694/? [04:48<00:00, 2.40it/s, train/loss=3.870]
Epoch 0: | | 694/? [04:48<00:00, 2.40it/s, train/loss=1.400]
Epoch 0: | | 695/? [04:48<00:00, 2.41it/s, train/loss=1.400]
Epoch 0: | | 695/? [04:48<00:00, 2.41it/s, train/loss=3.880]
Epoch 0: | | 696/? [04:49<00:00, 2.41it/s, train/loss=3.880]
Epoch 0: | | 696/? [04:49<00:00, 2.41it/s, train/loss=3.600]
Epoch 0: | | 697/? [04:49<00:00, 2.41it/s, train/loss=3.600]
Epoch 0: | | 697/? [04:49<00:00, 2.41it/s, train/loss=3.870]
Epoch 0: | | 698/? [04:49<00:00, 2.41it/s, train/loss=3.870]
Epoch 0: | | 698/? [04:49<00:00, 2.41it/s, train/loss=0.728]
Epoch 0: | | 699/? [04:49<00:00, 2.41it/s, train/loss=0.728]
Epoch 0: | | 699/? [04:49<00:00, 2.41it/s, train/loss=3.880]
Epoch 0: | | 700/? [04:50<00:00, 2.41it/s, train/loss=3.880]
Epoch 0: | | 700/? [04:50<00:00, 2.41it/s, train/loss=4.150]
Epoch 0: | | 701/? [04:50<00:00, 2.41it/s, train/loss=4.150]
Epoch 0: | | 701/? [04:51<00:00, 2.41it/s, train/loss=3.100]
Epoch 0: | | 702/? [04:51<00:00, 2.41it/s, train/loss=3.100]
Epoch 0: | | 702/? [04:51<00:00, 2.41it/s, train/loss=1.620]
Epoch 0: | | 703/? [04:51<00:00, 2.41it/s, train/loss=1.620]
Epoch 0: | | 703/? [04:51<00:00, 2.41it/s, train/loss=3.910]
Epoch 0: | | 704/? [04:51<00:00, 2.41it/s, train/loss=3.910]
Epoch 0: | | 704/? [04:51<00:00, 2.41it/s, train/loss=2.630]
Epoch 0: | | 705/? [04:51<00:00, 2.42it/s, train/loss=2.630]
Epoch 0: | | 705/? [04:51<00:00, 2.42it/s, train/loss=3.910]
Epoch 0: | | 706/? [04:52<00:00, 2.42it/s, train/loss=3.910]
Epoch 0: | | 706/? [04:52<00:00, 2.42it/s, train/loss=2.230]
Epoch 0: | | 707/? [04:52<00:00, 2.42it/s, train/loss=2.230]
Epoch 0: | | 707/? [04:52<00:00, 2.42it/s, train/loss=3.910]
Epoch 0: | | 708/? [04:52<00:00, 2.42it/s, train/loss=3.910]
Epoch 0: | | 708/? [04:52<00:00, 2.42it/s, train/loss=1.250]
Epoch 0: | | 709/? [04:52<00:00, 2.42it/s, train/loss=1.250]
Epoch 0: | | 709/? [04:52<00:00, 2.42it/s, train/loss=3.920]
Epoch 0: | | 710/? [04:53<00:00, 2.42it/s, train/loss=3.920]
Epoch 0: | | 710/? [04:53<00:00, 2.42it/s, train/loss=4.350]
Epoch 0: | | 711/? [04:54<00:00, 2.42it/s, train/loss=4.350]
Epoch 0: | | 711/? [04:54<00:00, 2.42it/s, train/loss=1.360]
Epoch 0: | | 712/? [04:54<00:00, 2.42it/s, train/loss=1.360]
Epoch 0: | | 712/? [04:54<00:00, 2.42it/s, train/loss=0.907]
Epoch 0: | | 713/? [04:54<00:00, 2.42it/s, train/loss=0.907]
Epoch 0: | | 713/? [04:54<00:00, 2.42it/s, train/loss=3.970]
Epoch 0: | | 714/? [04:54<00:00, 2.42it/s, train/loss=3.970]
Epoch 0: | | 714/? [04:54<00:00, 2.42it/s, train/loss=1.470]
Epoch 0: | | 715/? [04:54<00:00, 2.42it/s, train/loss=1.470]
Epoch 0: | | 715/? [04:54<00:00, 2.42it/s, train/loss=3.970]
Epoch 0: | | 716/? [04:55<00:00, 2.42it/s, train/loss=3.970]
Epoch 0: | | 716/? [04:55<00:00, 2.42it/s, train/loss=3.030]
Epoch 0: | | 717/? [04:55<00:00, 2.43it/s, train/loss=3.030]
Epoch 0: | | 717/? [04:55<00:00, 2.43it/s, train/loss=3.970]
Epoch 0: | | 718/? [04:55<00:00, 2.43it/s, train/loss=3.970]
Epoch 0: | | 718/? [04:55<00:00, 2.43it/s, train/loss=3.100]
Epoch 0: | | 719/? [04:55<00:00, 2.43it/s, train/loss=3.100]
Epoch 0: | | 719/? [04:55<00:00, 2.43it/s, train/loss=3.960]
Epoch 0: | | 720/? [04:56<00:00, 2.43it/s, train/loss=3.960]
Epoch 0: | | 720/? [04:56<00:00, 2.43it/s, train/loss=0.764]
Epoch 0: | | 721/? [04:57<00:00, 2.43it/s, train/loss=0.764]
Epoch 0: | | 721/? [04:57<00:00, 2.43it/s, train/loss=1.450]
Epoch 0: | | 722/? [04:57<00:00, 2.43it/s, train/loss=1.450]
Epoch 0: | | 722/? [04:57<00:00, 2.43it/s, train/loss=0.801]
Epoch 0: | | 723/? [04:57<00:00, 2.43it/s, train/loss=0.801]
Epoch 0: | | 723/? [04:57<00:00, 2.43it/s, train/loss=3.990]
Epoch 0: | | 724/? [04:58<00:00, 2.43it/s, train/loss=3.990]
Epoch 0: | | 724/? [04:58<00:00, 2.43it/s, train/loss=4.620]
Epoch 0: | | 725/? [04:58<00:00, 2.43it/s, train/loss=4.620]
Epoch 0: | | 725/? [04:58<00:00, 2.43it/s, train/loss=3.990]
Epoch 0: | | 726/? [04:58<00:00, 2.43it/s, train/loss=3.990]
Epoch 0: | | 726/? [04:58<00:00, 2.43it/s, train/loss=2.560]
Epoch 0: | | 727/? [04:58<00:00, 2.43it/s, train/loss=2.560]
Epoch 0: | | 727/? [04:58<00:00, 2.43it/s, train/loss=3.970]
Epoch 0: | | 728/? [04:58<00:00, 2.44it/s, train/loss=3.970]
Epoch 0: | | 728/? [04:58<00:00, 2.44it/s, train/loss=2.670]
Epoch 0: | | 729/? [04:59<00:00, 2.44it/s, train/loss=2.670]
Epoch 0: | | 729/? [04:59<00:00, 2.44it/s, train/loss=3.950]
Epoch 0: | | 730/? [04:59<00:00, 2.44it/s, train/loss=3.950]
Epoch 0: | | 730/? [04:59<00:00, 2.44it/s, train/loss=1.660]
Epoch 0: | | 731/? [05:00<00:00, 2.43it/s, train/loss=1.660]
Epoch 0: | | 731/? [05:00<00:00, 2.43it/s, train/loss=0.466]
Epoch 0: | | 732/? [05:00<00:00, 2.43it/s, train/loss=0.466]
Epoch 0: | | 732/? [05:00<00:00, 2.43it/s, train/loss=1.160]
Epoch 0: | | 733/? [05:00<00:00, 2.44it/s, train/loss=1.160]
Epoch 0: | | 733/? [05:00<00:00, 2.44it/s, train/loss=3.940]
Epoch 0: | | 734/? [05:01<00:00, 2.44it/s, train/loss=3.940]
Epoch 0: | | 734/? [05:01<00:00, 2.44it/s, train/loss=1.240]
Epoch 0: | | 735/? [05:01<00:00, 2.44it/s, train/loss=1.240]
Epoch 0: | | 735/? [05:01<00:00, 2.44it/s, train/loss=3.910]
Epoch 0: | | 736/? [05:01<00:00, 2.44it/s, train/loss=3.910]
Epoch 0: | | 736/? [05:01<00:00, 2.44it/s, train/loss=1.670]
Epoch 0: | | 737/? [05:01<00:00, 2.44it/s, train/loss=1.670]
Epoch 0: | | 737/? [05:01<00:00, 2.44it/s, train/loss=3.890]
Epoch 0: | | 738/? [05:02<00:00, 2.44it/s, train/loss=3.890]
Epoch 0: | | 738/? [05:02<00:00, 2.44it/s, train/loss=3.870]
Epoch 0: | | 739/? [05:02<00:00, 2.44it/s, train/loss=3.870]
Epoch 0: | | 739/? [05:02<00:00, 2.44it/s, train/loss=3.870]
Epoch 0: | | 740/? [05:02<00:00, 2.44it/s, train/loss=3.870]
Epoch 0: | | 740/? [05:02<00:00, 2.44it/s, train/loss=2.820]
Epoch 0: | | 741/? [05:03<00:00, 2.44it/s, train/loss=2.820]
Epoch 0: | | 741/? [05:03<00:00, 2.44it/s, train/loss=1.030]
Epoch 0: | | 742/? [05:03<00:00, 2.44it/s, train/loss=1.030]
Epoch 0: | | 742/? [05:03<00:00, 2.44it/s, train/loss=4.110]
Epoch 0: | | 743/? [05:04<00:00, 2.44it/s, train/loss=4.110]
Epoch 0: | | 743/? [05:04<00:00, 2.44it/s, train/loss=3.850]
Epoch 0: | | 744/? [05:04<00:00, 2.44it/s, train/loss=3.850]
Epoch 0: | | 744/? [05:04<00:00, 2.44it/s, train/loss=3.620]
Epoch 0: | | 745/? [05:04<00:00, 2.45it/s, train/loss=3.620]
Epoch 0: | | 745/? [05:04<00:00, 2.45it/s, train/loss=3.840]
Epoch 0: | | 746/? [05:04<00:00, 2.45it/s, train/loss=3.840]
Epoch 0: | | 746/? [05:04<00:00, 2.45it/s, train/loss=4.150]
Epoch 0: | | 747/? [05:04<00:00, 2.45it/s, train/loss=4.150]
Epoch 0: | | 747/? [05:04<00:00, 2.45it/s, train/loss=3.830]
Epoch 0: | | 748/? [05:05<00:00, 2.45it/s, train/loss=3.830]
Epoch 0: | | 748/? [05:05<00:00, 2.45it/s, train/loss=2.550]
Epoch 0: | | 749/? [05:05<00:00, 2.45it/s, train/loss=2.550]
Epoch 0: | | 749/? [05:05<00:00, 2.45it/s, train/loss=3.820]
Epoch 0: | | 750/? [05:05<00:00, 2.45it/s, train/loss=3.820]
Epoch 0: | | 750/? [05:05<00:00, 2.45it/s, train/loss=3.150]
Epoch 0: | | 751/? [05:06<00:00, 2.45it/s, train/loss=3.150]
Epoch 0: | | 751/? [05:06<00:00, 2.45it/s, train/loss=1.720]
Epoch 0: | | 752/? [05:07<00:00, 2.45it/s, train/loss=1.720]
Epoch 0: | | 752/? [05:07<00:00, 2.45it/s, train/loss=1.990]
Epoch 0: | | 753/? [05:07<00:00, 2.45it/s, train/loss=1.990]
Epoch 0: | | 753/? [05:07<00:00, 2.45it/s, train/loss=3.870]
Epoch 0: | | 754/? [05:07<00:00, 2.45it/s, train/loss=3.870]
Epoch 0: | | 754/? [05:07<00:00, 2.45it/s, train/loss=1.640]
Epoch 0: | | 755/? [05:07<00:00, 2.45it/s, train/loss=1.640]
Epoch 0: | | 755/? [05:07<00:00, 2.45it/s, train/loss=3.870]
Epoch 0: | | 756/? [05:07<00:00, 2.45it/s, train/loss=3.870]
Epoch 0: | | 756/? [05:07<00:00, 2.45it/s, train/loss=1.770]
Epoch 0: | | 757/? [05:08<00:00, 2.46it/s, train/loss=1.770]
Epoch 0: | | 757/? [05:08<00:00, 2.46it/s, train/loss=3.860]
Epoch 0: | | 758/? [05:08<00:00, 2.46it/s, train/loss=3.860]
Epoch 0: | | 758/? [05:08<00:00, 2.46it/s, train/loss=0.981]
Epoch 0: | | 759/? [05:08<00:00, 2.46it/s, train/loss=0.981]
Epoch 0: | | 759/? [05:08<00:00, 2.46it/s, train/loss=3.860]
Epoch 0: | | 760/? [05:08<00:00, 2.46it/s, train/loss=3.860]
Epoch 0: | | 760/? [05:08<00:00, 2.46it/s, train/loss=0.939]
Epoch 0: | | 761/? [05:09<00:00, 2.46it/s, train/loss=0.939]
Epoch 0: | | 761/? [05:09<00:00, 2.46it/s, train/loss=0.714]
Epoch 0: | | 762/? [05:10<00:00, 2.46it/s, train/loss=0.714]
Epoch 0: | | 762/? [05:10<00:00, 2.46it/s, train/loss=1.130]
Epoch 0: | | 763/? [05:10<00:00, 2.46it/s, train/loss=1.130]
Epoch 0: | | 763/? [05:10<00:00, 2.46it/s, train/loss=3.880]
Epoch 0: | | 764/? [05:10<00:00, 2.46it/s, train/loss=3.880]
Epoch 0: | | 764/? [05:10<00:00, 2.46it/s, train/loss=0.977]
Epoch 0: | | 765/? [05:10<00:00, 2.46it/s, train/loss=0.977]
Epoch 0: | | 765/? [05:10<00:00, 2.46it/s, train/loss=3.870]
Epoch 0: | | 766/? [05:11<00:00, 2.46it/s, train/loss=3.870]
Epoch 0: | | 766/? [05:11<00:00, 2.46it/s, train/loss=0.962]
Epoch 0: | | 767/? [05:11<00:00, 2.47it/s, train/loss=0.962]
Epoch 0: | | 767/? [05:11<00:00, 2.47it/s, train/loss=3.830]
Epoch 0: | | 768/? [05:11<00:00, 2.47it/s, train/loss=3.830]
Epoch 0: | | 768/? [05:11<00:00, 2.47it/s, train/loss=1.210]
Epoch 0: | | 769/? [05:11<00:00, 2.47it/s, train/loss=1.210]
Epoch 0: | | 769/? [05:11<00:00, 2.47it/s, train/loss=3.820]
Epoch 0: | | 770/? [05:11<00:00, 2.47it/s, train/loss=3.820]
Epoch 0: | | 770/? [05:11<00:00, 2.47it/s, train/loss=3.870]
Epoch 0: | | 771/? [05:12<00:00, 2.46it/s, train/loss=3.870]
Epoch 0: | | 771/? [05:12<00:00, 2.46it/s, train/loss=1.360]
Epoch 0: | | 772/? [05:13<00:00, 2.47it/s, train/loss=1.360]
Epoch 0: | | 772/? [05:13<00:00, 2.46it/s, train/loss=3.670]
Epoch 0: | | 773/? [05:13<00:00, 2.47it/s, train/loss=3.670]
Epoch 0: | | 773/? [05:13<00:00, 2.47it/s, train/loss=3.870]
Epoch 0: | | 774/? [05:13<00:00, 2.47it/s, train/loss=3.870]
Epoch 0: | | 774/? [05:13<00:00, 2.47it/s, train/loss=3.310]
Epoch 0: | | 775/? [05:13<00:00, 2.47it/s, train/loss=3.310]
Epoch 0: | | 775/? [05:13<00:00, 2.47it/s, train/loss=3.890]
Epoch 0: | | 776/? [05:14<00:00, 2.47it/s, train/loss=3.890]
Epoch 0: | | 776/? [05:14<00:00, 2.47it/s, train/loss=2.750]
Epoch 0: | | 777/? [05:14<00:00, 2.47it/s, train/loss=2.750]
Epoch 0: | | 777/? [05:14<00:00, 2.47it/s, train/loss=3.880]
Epoch 0: | | 778/? [05:14<00:00, 2.47it/s, train/loss=3.880]
Epoch 0: | | 778/? [05:14<00:00, 2.47it/s, train/loss=2.020]
Epoch 0: | | 779/? [05:14<00:00, 2.48it/s, train/loss=2.020]
Epoch 0: | | 779/? [05:14<00:00, 2.48it/s, train/loss=3.880]
Epoch 0: | | 780/? [05:15<00:00, 2.48it/s, train/loss=3.880]
Epoch 0: | | 780/? [05:15<00:00, 2.48it/s, train/loss=2.680]
Epoch 0: | | 781/? [05:15<00:00, 2.47it/s, train/loss=2.680]
Epoch 0: | | 781/? [05:15<00:00, 2.47it/s, train/loss=0.906]
Epoch 0: | | 782/? [05:16<00:00, 2.47it/s, train/loss=0.906]
Epoch 0: | | 782/? [05:16<00:00, 2.47it/s, train/loss=0.567]
Epoch 0: | | 783/? [05:16<00:00, 2.48it/s, train/loss=0.567]
Epoch 0: | | 783/? [05:16<00:00, 2.48it/s, train/loss=3.910]
Epoch 0: | | 784/? [05:16<00:00, 2.48it/s, train/loss=3.910]
Epoch 0: | | 784/? [05:16<00:00, 2.48it/s, train/loss=1.590]
Epoch 0: | | 785/? [05:16<00:00, 2.48it/s, train/loss=1.590]
Epoch 0: | | 785/? [05:16<00:00, 2.48it/s, train/loss=3.900]
Epoch 0: | | 786/? [05:17<00:00, 2.48it/s, train/loss=3.900]
Epoch 0: | | 786/? [05:17<00:00, 2.48it/s, train/loss=2.630]
Epoch 0: | | 787/? [05:17<00:00, 2.48it/s, train/loss=2.630]
Epoch 0: | | 787/? [05:17<00:00, 2.48it/s, train/loss=3.870]
Epoch 0: | | 788/? [05:17<00:00, 2.48it/s, train/loss=3.870]
Epoch 0: | | 788/? [05:17<00:00, 2.48it/s, train/loss=0.732]
Epoch 0: | | 789/? [05:17<00:00, 2.48it/s, train/loss=0.732]
Epoch 0: | | 789/? [05:17<00:00, 2.48it/s, train/loss=3.840]
Epoch 0: | | 790/? [05:18<00:00, 2.48it/s, train/loss=3.840]
Epoch 0: | | 790/? [05:18<00:00, 2.48it/s, train/loss=3.090]
Epoch 0: | | 791/? [05:19<00:00, 2.48it/s, train/loss=3.090]
Epoch 0: | | 791/? [05:19<00:00, 2.48it/s, train/loss=1.140]
Epoch 0: | | 792/? [05:19<00:00, 2.48it/s, train/loss=1.140]
Epoch 0: | | 792/? [05:19<00:00, 2.48it/s, train/loss=1.070]
Epoch 0: | | 793/? [05:19<00:00, 2.48it/s, train/loss=1.070]
Epoch 0: | | 793/? [05:19<00:00, 2.48it/s, train/loss=3.830]
Epoch 0: | | 794/? [05:19<00:00, 2.48it/s, train/loss=3.830]
Epoch 0: | | 794/? [05:19<00:00, 2.48it/s, train/loss=4.230]
Epoch 0: | | 795/? [05:19<00:00, 2.48it/s, train/loss=4.230]
Epoch 0: | | 795/? [05:19<00:00, 2.48it/s, train/loss=3.810]
Epoch 0: | | 796/? [05:20<00:00, 2.48it/s, train/loss=3.810]
Epoch 0: | | 796/? [05:20<00:00, 2.48it/s, train/loss=3.320]
Epoch 0: | | 797/? [05:20<00:00, 2.49it/s, train/loss=3.320]
Epoch 0: | | 797/? [05:20<00:00, 2.49it/s, train/loss=3.790]
Epoch 0: | | 798/? [05:20<00:00, 2.49it/s, train/loss=3.790]
Epoch 0: | | 798/? [05:20<00:00, 2.49it/s, train/loss=3.670]
Epoch 0: | | 799/? [05:20<00:00, 2.49it/s, train/loss=3.670]
Epoch 0: | | 799/? [05:20<00:00, 2.49it/s, train/loss=3.800]
Epoch 0: | | 800/? [05:21<00:00, 2.49it/s, train/loss=3.800]
Epoch 0: | | 800/? [05:21<00:00, 2.49it/s, train/loss=1.040]
Validation: | | 0/? [00:00<?, ?it/s][A
Validation: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 0%| | 0/40 [00:00<?, ?it/s][A
Validation DataLoader 0: 2%|▎ | 1/40 [00:00<00:04, 8.90it/s][A
Validation DataLoader 0: 5%|▌ | 2/40 [00:00<00:04, 8.71it/s][A
Validation DataLoader 0: 8%|▊ | 3/40 [00:00<00:04, 8.12it/s][A
Validation DataLoader 0: 10%|█ | 4/40 [00:00<00:04, 8.12it/s][A
Validation DataLoader 0: 12%|█▎ | 5/40 [00:00<00:04, 8.32it/s][A
Validation DataLoader 0: 15%|█▌ | 6/40 [00:00<00:04, 8.34it/s][A
Validation DataLoader 0: 18%|█▊ | 7/40 [00:00<00:03, 8.46it/s][A
Validation DataLoader 0: 20%|██ | 8/40 [00:00<00:03, 8.52it/s][A
Validation DataLoader 0: 22%|██▎ | 9/40 [00:01<00:03, 8.57it/s][A
Validation DataLoader 0: 25%|██▌ | 10/40 [00:01<00:03, 8.66it/s][A
Validation DataLoader 0: 28%|██▊ | 11/40 [00:01<00:03, 8.64it/s][A
Validation DataLoader 0: 30%|███ | 12/40 [00:01<00:03, 8.72it/s][A
Validation DataLoader 0: 32%|███▎ | 13/40 [00:01<00:03, 8.78it/s][A
Validation DataLoader 0: 35%|███▌ | 14/40 [00:01<00:02, 8.81it/s][A
Validation DataLoader 0: 38%|███▊ | 15/40 [00:01<00:02, 8.83it/s][A
Validation DataLoader 0: 40%|████ | 16/40 [00:01<00:02, 8.85it/s][A
Validation DataLoader 0: 42%|████▎ | 17/40 [00:01<00:02, 8.88it/s][A
Validation DataLoader 0: 45%|████▌ | 18/40 [00:02<00:02, 8.90it/s][A
Validation DataLoader 0: 48%|████▊ | 19/40 [00:02<00:02, 8.92it/s][A
Validation DataLoader 0: 50%|█████ | 20/40 [00:02<00:02, 8.94it/s][A
Validation DataLoader 0: 52%|█████▎ | 21/40 [00:02<00:02, 8.93it/s][A
Validation DataLoader 0: 55%|█████▌ | 22/40 [00:02<00:02, 8.95it/s][A
Validation DataLoader 0: 57%|█████▊ | 23/40 [00:02<00:01, 8.95it/s][A
Validation DataLoader 0: 60%|██████ | 24/40 [00:02<00:01, 8.97it/s][A
Validation DataLoader 0: 62%|██████▎ | 25/40 [00:02<00:01, 8.99it/s][A
Validation DataLoader 0: 65%|██████▌ | 26/40 [00:02<00:01, 8.99it/s][A
Validation DataLoader 0: 68%|██████▊ | 27/40 [00:02<00:01, 9.01it/s][A
Validation DataLoader 0: 70%|███████ | 28/40 [00:03<00:01, 9.03it/s][A
Validation DataLoader 0: 72%|███████▎ | 29/40 [00:03<00:01, 9.06it/s][A
Validation DataLoader 0: 75%|███████▌ | 30/40 [00:03<00:01, 9.08it/s][A
Validation DataLoader 0: 78%|███████▊ | 31/40 [00:03<00:00, 9.09it/s][A
Validation DataLoader 0: 80%|████████ | 32/40 [00:03<00:00, 9.11it/s][A
Validation DataLoader 0: 82%|████████▎ | 33/40 [00:03<00:00, 9.10it/s][A
Validation DataLoader 0: 85%|████████▌ | 34/40 [00:03<00:00, 9.10it/s][A
Validation DataLoader 0: 88%|████████▊ | 35/40 [00:03<00:00, 9.09it/s][A
Validation DataLoader 0: 90%|█████████ | 36/40 [00:03<00:00, 9.08it/s][A
Validation DataLoader 0: 92%|█████████▎| 37/40 [00:04<00:00, 9.07it/s][A
Validation DataLoader 0: 95%|█████████▌| 38/40 [00:04<00:00, 9.07it/s][A
Validation DataLoader 0: 98%|█████████▊| 39/40 [00:04<00:00, 9.07it/s][A
Validation DataLoader 0: 100%|██████████| 40/40 [00:04<00:00, 9.06it/s][A
[A
Epoch 0: | | 800/? [05:57<00:00, 2.24it/s, train/loss=1.040]
`Trainer.fit` stopped: `max_steps=800` reached.
Epoch 0: | | 800/? [05:57<00:00, 2.24it/s, train/loss=1.040]
Epoch 0: | | 800/? [05:57<00:00, 2.24it/s, train/loss=1.040]
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Testing: | | 0/? [00:00<?, ?it/s]
Testing: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 0%| | 0/120 [00:00<?, ?it/s]
Testing DataLoader 0: 1%| | 1/120 [00:00<00:16, 7.23it/s]
Testing DataLoader 0: 2%|▏ | 2/120 [00:00<00:15, 7.84it/s]
Testing DataLoader 0: 2%|▎ | 3/120 [00:00<00:14, 8.07it/s]
Testing DataLoader 0: 3%|▎ | 4/120 [00:00<00:14, 8.21it/s]
Testing DataLoader 0: 4%|▍ | 5/120 [00:00<00:13, 8.37it/s]
Testing DataLoader 0: 5%|▌ | 6/120 [00:00<00:13, 8.34it/s]
Testing DataLoader 0: 6%|▌ | 7/120 [00:00<00:13, 8.37it/s]
Testing DataLoader 0: 7%|▋ | 8/120 [00:00<00:13, 8.44it/s]
Testing DataLoader 0: 8%|▊ | 9/120 [00:01<00:13, 8.49it/s]
Testing DataLoader 0: 8%|▊ | 10/120 [00:01<00:12, 8.52it/s]
Testing DataLoader 0: 9%|▉ | 11/120 [00:01<00:12, 8.54it/s]
Testing DataLoader 0: 10%|█ | 12/120 [00:01<00:12, 8.55it/s]
Testing DataLoader 0: 11%|█ | 13/120 [00:01<00:12, 8.58it/s]
Testing DataLoader 0: 12%|█▏ | 14/120 [00:01<00:12, 8.61it/s]
Testing DataLoader 0: 12%|█▎ | 15/120 [00:01<00:12, 8.62it/s]
Testing DataLoader 0: 13%|█▎ | 16/120 [00:01<00:12, 8.65it/s]
Testing DataLoader 0: 14%|█▍ | 17/120 [00:01<00:11, 8.63it/s]
Testing DataLoader 0: 15%|█▌ | 18/120 [00:02<00:11, 8.59it/s]
Testing DataLoader 0: 16%|█▌ | 19/120 [00:02<00:11, 8.54it/s]
Testing DataLoader 0: 17%|█▋ | 20/120 [00:02<00:11, 8.50it/s]
Testing DataLoader 0: 18%|█▊ | 21/120 [00:02<00:11, 8.35it/s]
Testing DataLoader 0: 18%|█▊ | 22/120 [00:02<00:11, 8.31it/s]
Testing DataLoader 0: 19%|█▉ | 23/120 [00:02<00:11, 8.34it/s]
Testing DataLoader 0: 20%|██ | 24/120 [00:02<00:11, 8.38it/s]
Testing DataLoader 0: 21%|██ | 25/120 [00:02<00:11, 8.42it/s]
Testing DataLoader 0: 22%|██▏ | 26/120 [00:03<00:11, 8.45it/s]
Testing DataLoader 0: 22%|██▎ | 27/120 [00:03<00:10, 8.47it/s]
Testing DataLoader 0: 23%|██▎ | 28/120 [00:03<00:10, 8.50it/s]
Testing DataLoader 0: 24%|██▍ | 29/120 [00:03<00:10, 8.53it/s]
Testing DataLoader 0: 25%|██▌ | 30/120 [00:03<00:10, 8.55it/s]
Testing DataLoader 0: 26%|██▌ | 31/120 [00:03<00:10, 8.55it/s]
Testing DataLoader 0: 27%|██▋ | 32/120 [00:03<00:10, 8.51it/s]
Testing DataLoader 0: 28%|██▊ | 33/120 [00:03<00:10, 8.53it/s]
Testing DataLoader 0: 28%|██▊ | 34/120 [00:03<00:10, 8.56it/s]
Testing DataLoader 0: 29%|██▉ | 35/120 [00:04<00:09, 8.58it/s]
Testing DataLoader 0: 30%|███ | 36/120 [00:04<00:09, 8.60it/s]
Testing DataLoader 0: 31%|███ | 37/120 [00:04<00:09, 8.54it/s]
Testing DataLoader 0: 32%|███▏ | 38/120 [00:04<00:09, 8.55it/s]
Testing DataLoader 0: 32%|███▎ | 39/120 [00:04<00:09, 8.57it/s]
Testing DataLoader 0: 33%|███▎ | 40/120 [00:04<00:09, 8.58it/s]
Testing DataLoader 0: 34%|███▍ | 41/120 [00:04<00:09, 8.59it/s]
Testing DataLoader 0: 35%|███▌ | 42/120 [00:04<00:09, 8.60it/s]
Testing DataLoader 0: 36%|███▌ | 43/120 [00:04<00:08, 8.60it/s]
Testing DataLoader 0: 37%|███▋ | 44/120 [00:05<00:08, 8.61it/s]
Testing DataLoader 0: 38%|███▊ | 45/120 [00:05<00:08, 8.62it/s]
Testing DataLoader 0: 38%|███▊ | 46/120 [00:05<00:08, 8.63it/s]
Testing DataLoader 0: 39%|███▉ | 47/120 [00:05<00:08, 8.63it/s]
Testing DataLoader 0: 40%|████ | 48/120 [00:05<00:08, 8.64it/s]
Testing DataLoader 0: 41%|████ | 49/120 [00:05<00:08, 8.65it/s]
Testing DataLoader 0: 42%|████▏ | 50/120 [00:05<00:08, 8.66it/s]
Testing DataLoader 0: 42%|████▎ | 51/120 [00:05<00:07, 8.67it/s]
Testing DataLoader 0: 43%|████▎ | 52/120 [00:05<00:07, 8.67it/s]
Testing DataLoader 0: 44%|████▍ | 53/120 [00:06<00:07, 8.68it/s]
Testing DataLoader 0: 45%|████▌ | 54/120 [00:06<00:07, 8.69it/s]
Testing DataLoader 0: 46%|████▌ | 55/120 [00:06<00:07, 8.69it/s]
Testing DataLoader 0: 47%|████▋ | 56/120 [00:06<00:07, 8.70it/s]
Testing DataLoader 0: 48%|████▊ | 57/120 [00:06<00:07, 8.69it/s]
Testing DataLoader 0: 48%|████▊ | 58/120 [00:06<00:07, 8.70it/s]
Testing DataLoader 0: 49%|████▉ | 59/120 [00:06<00:07, 8.71it/s]
Testing DataLoader 0: 50%|█████ | 60/120 [00:06<00:06, 8.72it/s]
Testing DataLoader 0: 51%|█████ | 61/120 [00:06<00:06, 8.73it/s]
Testing DataLoader 0: 52%|█████▏ | 62/120 [00:07<00:06, 8.73it/s]
Testing DataLoader 0: 52%|█████▎ | 63/120 [00:07<00:06, 8.74it/s]
Testing DataLoader 0: 53%|█████▎ | 64/120 [00:07<00:06, 8.75it/s]
Testing DataLoader 0: 54%|█████▍ | 65/120 [00:07<00:06, 8.76it/s]
Testing DataLoader 0: 55%|█████▌ | 66/120 [00:07<00:06, 8.77it/s]
Testing DataLoader 0: 56%|█████▌ | 67/120 [00:07<00:06, 8.75it/s]
Testing DataLoader 0: 57%|█████▋ | 68/120 [00:07<00:05, 8.76it/s]
Testing DataLoader 0: 57%|█████▊ | 69/120 [00:07<00:05, 8.77it/s]
Testing DataLoader 0: 58%|█████▊ | 70/120 [00:07<00:05, 8.78it/s]
Testing DataLoader 0: 59%|█████▉ | 71/120 [00:08<00:05, 8.79it/s]
Testing DataLoader 0: 60%|██████ | 72/120 [00:08<00:05, 8.79it/s]
Testing DataLoader 0: 61%|██████ | 73/120 [00:08<00:05, 8.80it/s]
Testing DataLoader 0: 62%|██████▏ | 74/120 [00:08<00:05, 8.81it/s]
Testing DataLoader 0: 62%|██████▎ | 75/120 [00:08<00:05, 8.81it/s]
Testing DataLoader 0: 63%|██████▎ | 76/120 [00:08<00:04, 8.82it/s]
Testing DataLoader 0: 64%|██████▍ | 77/120 [00:08<00:04, 8.82it/s]
Testing DataLoader 0: 65%|██████▌ | 78/120 [00:08<00:04, 8.82it/s]
Testing DataLoader 0: 66%|██████▌ | 79/120 [00:08<00:04, 8.83it/s]
Testing DataLoader 0: 67%|██████▋ | 80/120 [00:09<00:04, 8.84it/s]
Testing DataLoader 0: 68%|██████▊ | 81/120 [00:09<00:04, 8.84it/s]
Testing DataLoader 0: 68%|██████▊ | 82/120 [00:09<00:04, 8.84it/s]
Testing DataLoader 0: 69%|██████▉ | 83/120 [00:09<00:04, 8.84it/s]
Testing DataLoader 0: 70%|███████ | 84/120 [00:09<00:04, 8.85it/s]
Testing DataLoader 0: 71%|███████ | 85/120 [00:09<00:03, 8.86it/s]
Testing DataLoader 0: 72%|███████▏ | 86/120 [00:09<00:03, 8.87it/s]
Testing DataLoader 0: 72%|███████▎ | 87/120 [00:09<00:03, 8.87it/s]
Testing DataLoader 0: 73%|███████▎ | 88/120 [00:09<00:03, 8.87it/s]
Testing DataLoader 0: 74%|███████▍ | 89/120 [00:10<00:03, 8.88it/s]
Testing DataLoader 0: 75%|███████▌ | 90/120 [00:10<00:03, 8.88it/s]
Testing DataLoader 0: 76%|███████▌ | 91/120 [00:10<00:03, 8.89it/s]
Testing DataLoader 0: 77%|███████▋ | 92/120 [00:10<00:03, 8.89it/s]
Testing DataLoader 0: 78%|███████▊ | 93/120 [00:10<00:03, 8.90it/s]
Testing DataLoader 0: 78%|███████▊ | 94/120 [00:10<00:02, 8.90it/s]
Testing DataLoader 0: 79%|███████▉ | 95/120 [00:10<00:02, 8.91it/s]
Testing DataLoader 0: 80%|████████ | 96/120 [00:10<00:02, 8.91it/s]
Testing DataLoader 0: 81%|████████ | 97/120 [00:10<00:02, 8.92it/s]
Testing DataLoader 0: 82%|████████▏ | 98/120 [00:10<00:02, 8.92it/s]
Testing DataLoader 0: 82%|████████▎ | 99/120 [00:11<00:02, 8.92it/s]
Testing DataLoader 0: 83%|████████▎ | 100/120 [00:11<00:02, 8.92it/s]
Testing DataLoader 0: 84%|████████▍ | 101/120 [00:11<00:02, 8.93it/s]
Testing DataLoader 0: 85%|████████▌ | 102/120 [00:11<00:02, 8.92it/s]
Testing DataLoader 0: 86%|████████▌ | 103/120 [00:11<00:01, 8.92it/s]
Testing DataLoader 0: 87%|████████▋ | 104/120 [00:11<00:01, 8.93it/s]
Testing DataLoader 0: 88%|████████▊ | 105/120 [00:11<00:01, 8.92it/s]
Testing DataLoader 0: 88%|████████▊ | 106/120 [00:11<00:01, 8.92it/s]
Testing DataLoader 0: 89%|████████▉ | 107/120 [00:12<00:01, 8.92it/s]
Testing DataLoader 0: 90%|█████████ | 108/120 [00:12<00:01, 8.91it/s]
Testing DataLoader 0: 91%|█████████ | 109/120 [00:12<00:01, 8.92it/s]
Testing DataLoader 0: 92%|█████████▏| 110/120 [00:12<00:01, 8.92it/s]
Testing DataLoader 0: 92%|█████████▎| 111/120 [00:12<00:01, 8.91it/s]
Testing DataLoader 0: 93%|█████████▎| 112/120 [00:12<00:00, 8.91it/s]
Testing DataLoader 0: 94%|█████████▍| 113/120 [00:12<00:00, 8.91it/s]
Testing DataLoader 0: 95%|█████████▌| 114/120 [00:12<00:00, 8.91it/s]
Testing DataLoader 0: 96%|█████████▌| 115/120 [00:12<00:00, 8.91it/s]
Testing DataLoader 0: 97%|█████████▋| 116/120 [00:13<00:00, 8.91it/s]
Testing DataLoader 0: 98%|█████████▊| 117/120 [00:13<00:00, 8.91it/s]
Testing DataLoader 0: 98%|█████████▊| 118/120 [00:13<00:00, 8.91it/s]
Testing DataLoader 0: 99%|█████████▉| 119/120 [00:13<00:00, 8.91it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:13<00:00, 8.91it/s]
Testing DataLoader 0: 100%|██████████| 120/120 [00:24<00:00, 4.99it/s]
Test results saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save
Running step 5: Exporting meshes
{'name': 'dreamcraft3d-texture', 'description': '', 'tag': 'replicate_user', 'seed': 0, 'use_timestamp': True, 'timestamp': '@20240222-135357', 'exp_root_dir': 'outputs', 'exp_dir': 'outputs/dreamcraft3d-texture', 'trial_name': 'replicate_user@20240222-135357', 'trial_dir': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357', 'n_gpus': 1, 'resume': 'outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt', 'data_type': 'dreamcraft3d-single-image-datamodule', 'data': {'image_path': '/src/outputs/image_rgba.png', 'height': 1024, 'width': 1024, 'default_elevation_deg': 0.0, 'default_azimuth_deg': 0.0, 'default_camera_distance': 3.8, 'default_fovy_deg': 20.0, 'requires_depth': False, 'requires_normal': False, 'use_mixed_camera_config': False, 'random_camera': {'height': 1024, 'width': 1024, 'batch_size': 1, 'eval_height': 1024, 'eval_width': 1024, 'eval_batch_size': 1, 'elevation_range': [-10, 45], 'azimuth_range': [-180, 180], 'camera_distance_range': [3.8, 3.8], 'fovy_range': [20.0, 20.0], 'progressive_until': 0, 'camera_perturb': 0.0, 'center_perturb': 0.0, 'up_perturb': 0.0, 'eval_elevation_deg': 0.0, 'eval_camera_distance': 3.8, 'eval_fovy_deg': 20.0, 'batch_uniform_azimuth': False, 'n_val_views': 40, 'n_test_views': 120}}, 'system_type': 'dreamcraft3d-system', 'system': {'stage': 'texture', 'use_mixed_camera_config': False, 'geometry_convert_inherit_texture': True, 'geometry_type': 'tetrahedra-sdf-grid', 'geometry': {'radius': 2.0, 'isosurface_resolution': 128, 'isosurface_deformable_grid': True, 'isosurface_remove_outliers': True, 'pos_encoding_config': {'otype': 'HashGrid', 'n_levels': 16, 'n_features_per_level': 2, 'log2_hashmap_size': 19, 'base_resolution': 16, 'per_level_scale': 1.447269237440378}, 'fix_geometry': True}, 'material_type': 'no-material', 'material': {'n_output_dims': 3}, 'background_type': 'solid-color-background', 'renderer_type': 'dreamcraft3d-mask-nvdiff-rasterizer', 'renderer': {'context_type': 'cuda'}, 'prompt_processor_type': 'stable-diffusion-prompt-processor', 'prompt_processor': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'prompt': 'A green leafy plant in a striped terracotta pot', 'front_threshold': 30.0, 'back_threshold': 30.0}, 'guidance_type': 'dreamcraft3d-stable-diffusion-bsd-lora-guidance', 'guidance': {'pretrained_model_name_or_path': 'stabilityai/stable-diffusion-2-1-base', 'pretrained_model_name_or_path_lora': 'stabilityai/stable-diffusion-2-1-base', 'guidance_scale': 5.0, 'min_step_percent': 0.05, 'max_step_percent': 0.3, 'only_pretrain_step': 10, 'per_update_pretrain_step': 10}, 'guidance_3d_type': 'stable-zero123-guidance', 'guidance_3d': {'pretrained_model_name_or_path': './models/zero123/stable_zero123.ckpt', 'pretrained_config': './models/zero123/sd-objaverse-finetune-c_concat-256.yaml', 'cond_image_path': '/src/outputs/image_rgba.png', 'cond_elevation_deg': 0.0, 'cond_azimuth_deg': 0.0, 'cond_camera_distance': 3.8, 'guidance_scale': 5.0, 'min_step_percent': 0.2, 'max_step_percent': 0.5}, 'freq': {'n_ref': 2, 'ref_only_steps': 0, 'ref_or_guidance': 'alternate', 'no_diff_steps': -1, 'guidance_eval': 0}, 'loggers': {'wandb': {'enable': False, 'project': 'threestudio'}}, 'loss': {'lambda_vsd': 0.1, 'lambda_lora': 0.1, 'lambda_pretrain': 0.1, 'lambda_3d_sds': 0.01, 'lambda_rgb': 1000.0, 'lambda_mask': 0.0, 'lambda_mask_binary': 0.0, 'lambda_depth': 0.0, 'lambda_depth_rel': 0.0, 'lambda_normal': 0.0, 'lambda_normal_smooth': 0.0, 'lambda_3d_normal_smooth': 0.0, 'lambda_z_variance': 0.0, 'lambda_reg': 0.0}, 'optimizer': {'name': 'AdamW', 'args': {'betas': [0.9, 0.99], 'eps': 0.0001}, 'params': {'geometry.encoding': {'lr': 0.005}, 'geometry.feature_network': {'lr': 0.001}, 'guidance': {'lr': 0.0001}}}, 'geometry_convert_from': 'outputs/dreamcraft3d-geometry/replicate_user@20240222-134756/ckpts/last.ckpt', 'exporter_type': 'mesh-exporter', 'exporter': {'context_type': 'cuda'}}, 'trainer': {'max_steps': 800, 'log_every_n_steps': 1, 'num_sanity_val_steps': 0, 'val_check_interval': 200, 'enable_progress_bar': True, 'precision': 32, 'gradient_clip_val': 1.0}, 'checkpoint': {'save_last': True, 'save_top_k': -1, 'every_n_train_steps': 800}}
Loading Stable Diffusion ...
Loading pipeline components...: 0%| | 0/4 [00:00<?, ?it/s]
Loading pipeline components...: 25%|██▌ | 1/4 [00:01<00:04, 1.37s/it]
Loading pipeline components...: 50%|█████ | 2/4 [00:01<00:01, 1.58it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:01<00:00, 2.57it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:01<00:00, 2.03it/s]
Loading pipeline components...: 0%| | 0/4 [00:00<?, ?it/s]
Loading pipeline components...: 25%|██▌ | 1/4 [00:00<00:02, 1.05it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:01<00:00, 3.13it/s]
Loading pipeline components...: 100%|██████████| 4/4 [00:01<00:00, 2.72it/s]
Loaded Stable Diffusion!
Loading Stable Zero123 ...
get obj from str: extern.ldm_zero123.models.diffusion.ddpm.LatentDiffusion
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.53 M params.
Keeping EMAs of 688.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Loaded Stable Zero123!
Using prompt [A green leafy plant in a striped terracotta pot] and negative prompt []
Using view-dependent prompts [side]:[A green leafy plant in a striped terracotta pot, side view] [front]:[A green leafy plant in a striped terracotta pot, front view] [back]:[A green leafy plant in a striped terracotta pot, back view] [overhead]:[A green leafy plant in a striped terracotta pot, overhead view]
loaded pretrained LPIPS loss from threestudio/utils/lpips/vgg.pth
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
Missing logger folder: /src/lightning_logs
[INFO] single image dataset: load image /src/outputs/image_rgba.png torch.Size([1, 1024, 1024, 3])
Restoring states from the checkpoint path at outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Loaded model weights from the checkpoint at outputs/dreamcraft3d-texture/replicate_user@20240222-135357/ckpts/last.ckpt
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'predict_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=9` in the `DataLoader` to improve performance.
Predicting: | | 0/? [00:00<?, ?it/s]
Predicting: 0%| | 0/120 [00:00<?, ?it/s]
Predicting DataLoader 0: 0%| | 0/120 [00:00<?, ?it/s]
/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/pytorch_lightning/loops/prediction_loop.py:255: predict returned None if it was on purpose, ignore this warning...
Predicting DataLoader 0: 1%| | 1/120 [00:00<00:00, 407.81it/s]
Predicting DataLoader 0: 2%|▏ | 2/120 [00:00<00:00, 196.28it/s]
Predicting DataLoader 0: 2%|▎ | 3/120 [00:00<00:00, 148.91it/s]
Predicting DataLoader 0: 3%|▎ | 4/120 [00:00<00:00, 143.05it/s]
Predicting DataLoader 0: 4%|▍ | 5/120 [00:00<00:00, 139.61it/s]
Predicting DataLoader 0: 5%|▌ | 6/120 [00:00<00:00, 130.72it/s]
Predicting DataLoader 0: 6%|▌ | 7/120 [00:00<00:00, 130.50it/s]
Predicting DataLoader 0: 7%|▋ | 8/120 [00:00<00:01, 102.54it/s]
Predicting DataLoader 0: 8%|▊ | 9/120 [00:00<00:01, 88.50it/s]
Predicting DataLoader 0: 8%|▊ | 10/120 [00:00<00:01, 91.95it/s]
Predicting DataLoader 0: 9%|▉ | 11/120 [00:00<00:01, 94.76it/s]
Predicting DataLoader 0: 10%|█ | 12/120 [00:00<00:01, 97.37it/s]
Predicting DataLoader 0: 11%|█ | 13/120 [00:00<00:01, 99.94it/s]
Predicting DataLoader 0: 12%|█▏ | 14/120 [00:00<00:01, 102.38it/s]
Predicting DataLoader 0: 12%|█▎ | 15/120 [00:00<00:01, 104.49it/s]
Predicting DataLoader 0: 13%|█▎ | 16/120 [00:00<00:00, 106.34it/s]
Predicting DataLoader 0: 14%|█▍ | 17/120 [00:00<00:00, 108.10it/s]
Predicting DataLoader 0: 15%|█▌ | 18/120 [00:00<00:00, 109.78it/s]
Predicting DataLoader 0: 16%|█▌ | 19/120 [00:00<00:00, 111.24it/s]
Predicting DataLoader 0: 17%|█▋ | 20/120 [00:00<00:00, 112.62it/s]
Predicting DataLoader 0: 18%|█▊ | 21/120 [00:00<00:00, 113.88it/s]
Predicting DataLoader 0: 18%|█▊ | 22/120 [00:00<00:00, 115.20it/s]
Predicting DataLoader 0: 19%|█▉ | 23/120 [00:00<00:00, 116.32it/s]
Predicting DataLoader 0: 20%|██ | 24/120 [00:00<00:00, 117.41it/s]
Predicting DataLoader 0: 21%|██ | 25/120 [00:00<00:00, 118.37it/s]
Predicting DataLoader 0: 22%|██▏ | 26/120 [00:00<00:00, 119.12it/s]
Predicting DataLoader 0: 22%|██▎ | 27/120 [00:00<00:00, 119.85it/s]
Predicting DataLoader 0: 23%|██▎ | 28/120 [00:00<00:00, 120.64it/s]
Predicting DataLoader 0: 24%|██▍ | 29/120 [00:00<00:00, 121.31it/s]
Predicting DataLoader 0: 25%|██▌ | 30/120 [00:00<00:00, 122.05it/s]
Predicting DataLoader 0: 26%|██▌ | 31/120 [00:00<00:00, 122.69it/s]
Predicting DataLoader 0: 27%|██▋ | 32/120 [00:00<00:00, 123.33it/s]
Predicting DataLoader 0: 28%|██▊ | 33/120 [00:00<00:00, 123.96it/s]
Predicting DataLoader 0: 28%|██▊ | 34/120 [00:00<00:00, 124.64it/s]
Predicting DataLoader 0: 29%|██▉ | 35/120 [00:00<00:00, 125.25it/s]
Predicting DataLoader 0: 30%|███ | 36/120 [00:00<00:00, 125.84it/s]
Predicting DataLoader 0: 31%|███ | 37/120 [00:00<00:00, 126.35it/s]
Predicting DataLoader 0: 32%|███▏ | 38/120 [00:00<00:00, 126.92it/s]
Predicting DataLoader 0: 32%|███▎ | 39/120 [00:00<00:00, 127.41it/s]
Predicting DataLoader 0: 33%|███▎ | 40/120 [00:00<00:00, 127.85it/s]
Predicting DataLoader 0: 34%|███▍ | 41/120 [00:00<00:00, 128.25it/s]
Predicting DataLoader 0: 35%|███▌ | 42/120 [00:00<00:00, 128.73it/s]
Predicting DataLoader 0: 36%|███▌ | 43/120 [00:00<00:00, 127.98it/s]
Predicting DataLoader 0: 37%|███▋ | 44/120 [00:00<00:00, 128.19it/s]
Predicting DataLoader 0: 38%|███▊ | 45/120 [00:00<00:00, 128.60it/s]
Predicting DataLoader 0: 38%|███▊ | 46/120 [00:00<00:00, 129.02it/s]
Predicting DataLoader 0: 39%|███▉ | 47/120 [00:00<00:00, 129.32it/s]
Predicting DataLoader 0: 40%|████ | 48/120 [00:00<00:00, 129.72it/s]
Predicting DataLoader 0: 41%|████ | 49/120 [00:00<00:00, 130.08it/s]
Predicting DataLoader 0: 42%|████▏ | 50/120 [00:00<00:00, 130.47it/s]
Predicting DataLoader 0: 42%|████▎ | 51/120 [00:00<00:00, 130.80it/s]
Predicting DataLoader 0: 43%|████▎ | 52/120 [00:00<00:00, 131.13it/s]
Predicting DataLoader 0: 44%|████▍ | 53/120 [00:00<00:00, 131.39it/s]
Predicting DataLoader 0: 45%|████▌ | 54/120 [00:00<00:00, 131.53it/s]
Predicting DataLoader 0: 46%|████▌ | 55/120 [00:00<00:00, 131.65it/s]
Predicting DataLoader 0: 47%|████▋ | 56/120 [00:00<00:00, 131.67it/s]
Predicting DataLoader 0: 48%|████▊ | 57/120 [00:00<00:00, 131.69it/s]
Predicting DataLoader 0: 48%|████▊ | 58/120 [00:00<00:00, 131.71it/s]
Predicting DataLoader 0: 49%|████▉ | 59/120 [00:00<00:00, 131.13it/s]
Predicting DataLoader 0: 50%|█████ | 60/120 [00:00<00:00, 131.29it/s]
Predicting DataLoader 0: 51%|█████ | 61/120 [00:00<00:00, 131.44it/s]
Predicting DataLoader 0: 52%|█████▏ | 62/120 [00:00<00:00, 131.67it/s]
Predicting DataLoader 0: 52%|█████▎ | 63/120 [00:00<00:00, 131.82it/s]
Predicting DataLoader 0: 53%|█████▎ | 64/120 [00:00<00:00, 131.98it/s]
Predicting DataLoader 0: 54%|█████▍ | 65/120 [00:00<00:00, 131.16it/s]
Predicting DataLoader 0: 55%|█████▌ | 66/120 [00:00<00:00, 131.34it/s]
Predicting DataLoader 0: 56%|█████▌ | 67/120 [00:00<00:00, 131.48it/s]
Predicting DataLoader 0: 57%|█████▋ | 68/120 [00:00<00:00, 131.62it/s]
Predicting DataLoader 0: 57%|█████▊ | 69/120 [00:00<00:00, 131.74it/s]
Predicting DataLoader 0: 58%|█████▊ | 70/120 [00:00<00:00, 131.94it/s]
Predicting DataLoader 0: 59%|█████▉ | 71/120 [00:00<00:00, 132.02it/s]
Predicting DataLoader 0: 60%|██████ | 72/120 [00:00<00:00, 131.85it/s]
Predicting DataLoader 0: 61%|██████ | 73/120 [00:00<00:00, 131.27it/s]
Predicting DataLoader 0: 62%|██████▏ | 74/120 [00:00<00:00, 128.51it/s]
Predicting DataLoader 0: 62%|██████▎ | 75/120 [00:00<00:00, 128.74it/s]
Predicting DataLoader 0: 63%|██████▎ | 76/120 [00:00<00:00, 128.96it/s]
Predicting DataLoader 0: 64%|██████▍ | 77/120 [00:00<00:00, 129.20it/s]
Predicting DataLoader 0: 65%|██████▌ | 78/120 [00:00<00:00, 129.43it/s]
Predicting DataLoader 0: 66%|██████▌ | 79/120 [00:00<00:00, 129.64it/s]
Predicting DataLoader 0: 67%|██████▋ | 80/120 [00:00<00:00, 129.81it/s]
Predicting DataLoader 0: 68%|██████▊ | 81/120 [00:00<00:00, 130.02it/s]
Predicting DataLoader 0: 68%|██████▊ | 82/120 [00:00<00:00, 130.25it/s]
Predicting DataLoader 0: 69%|██████▉ | 83/120 [00:00<00:00, 130.44it/s]
Predicting DataLoader 0: 70%|███████ | 84/120 [00:00<00:00, 130.62it/s]
Predicting DataLoader 0: 71%|███████ | 85/120 [00:00<00:00, 130.73it/s]
Predicting DataLoader 0: 72%|███████▏ | 86/120 [00:00<00:00, 130.88it/s]
Predicting DataLoader 0: 72%|███████▎ | 87/120 [00:00<00:00, 130.96it/s]
Predicting DataLoader 0: 73%|███████▎ | 88/120 [00:00<00:00, 131.09it/s]
Predicting DataLoader 0: 74%|███████▍ | 89/120 [00:00<00:00, 131.20it/s]
Predicting DataLoader 0: 75%|███████▌ | 90/120 [00:00<00:00, 131.34it/s]
Predicting DataLoader 0: 76%|███████▌ | 91/120 [00:00<00:00, 131.45it/s]
Predicting DataLoader 0: 77%|███████▋ | 92/120 [00:00<00:00, 131.57it/s]
Predicting DataLoader 0: 78%|███████▊ | 93/120 [00:00<00:00, 131.68it/s]
Predicting DataLoader 0: 78%|███████▊ | 94/120 [00:00<00:00, 131.79it/s]
Predicting DataLoader 0: 79%|███████▉ | 95/120 [00:00<00:00, 131.88it/s]
Predicting DataLoader 0: 80%|████████ | 96/120 [00:00<00:00, 131.98it/s]
Predicting DataLoader 0: 81%|████████ | 97/120 [00:00<00:00, 132.05it/s]
Predicting DataLoader 0: 82%|████████▏ | 98/120 [00:00<00:00, 132.12it/s]
Predicting DataLoader 0: 82%|████████▎ | 99/120 [00:00<00:00, 132.17it/s]
Predicting DataLoader 0: 83%|████████▎ | 100/120 [00:00<00:00, 132.24it/s]
Predicting DataLoader 0: 84%|████████▍ | 101/120 [00:00<00:00, 132.29it/s]
Predicting DataLoader 0: 85%|████████▌ | 102/120 [00:00<00:00, 132.38it/s]
Predicting DataLoader 0: 86%|████████▌ | 103/120 [00:00<00:00, 132.45it/s]
Predicting DataLoader 0: 87%|████████▋ | 104/120 [00:00<00:00, 132.51it/s]
Predicting DataLoader 0: 88%|████████▊ | 105/120 [00:00<00:00, 132.58it/s]
Predicting DataLoader 0: 88%|████████▊ | 106/120 [00:00<00:00, 132.68it/s]
Predicting DataLoader 0: 89%|████████▉ | 107/120 [00:00<00:00, 132.72it/s]
Predicting DataLoader 0: 90%|█████████ | 108/120 [00:00<00:00, 132.77it/s]
Predicting DataLoader 0: 91%|█████████ | 109/120 [00:00<00:00, 132.83it/s]
Predicting DataLoader 0: 92%|█████████▏| 110/120 [00:00<00:00, 132.93it/s]
Predicting DataLoader 0: 92%|█████████▎| 111/120 [00:00<00:00, 132.98it/s]
Predicting DataLoader 0: 93%|█████████▎| 112/120 [00:00<00:00, 133.03it/s]
Predicting DataLoader 0: 94%|█████████▍| 113/120 [00:00<00:00, 133.08it/s]
Predicting DataLoader 0: 95%|█████████▌| 114/120 [00:00<00:00, 133.18it/s]
Predicting DataLoader 0: 96%|█████████▌| 115/120 [00:00<00:00, 133.22it/s]
Predicting DataLoader 0: 97%|█████████▋| 116/120 [00:00<00:00, 133.28it/s]
Predicting DataLoader 0: 98%|█████████▊| 117/120 [00:00<00:00, 133.36it/s]
Predicting DataLoader 0: 98%|█████████▊| 118/120 [00:00<00:00, 133.44it/s]
Predicting DataLoader 0: 99%|█████████▉| 119/120 [00:00<00:00, 133.47it/s]
Using xatlas to perform UV unwrapping, may take a while ...
Exporting textures ...
Perform UV padding on texture maps to avoid seams, may take a while ...
Predicting DataLoader 0: 100%|██████████| 120/120 [00:00<00:00, 133.53it/s]
Predicting DataLoader 0: 100%|██████████| 120/120 [01:06<00:00, 1.81it/s]
Export assets saved to outputs/dreamcraft3d-texture/replicate_user@20240222-135357/save
Version Details
- Version ID
cf19b73a3c605ffa94c29d95971cb89823a0faa5f2ba830a3e1579fa61577c30- Version Created
- February 21, 2024