ensemblemodelsFiles / convnextStage1 /convnextv2-large-70-10-20-split.log
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[{"stream_name":"stderr","time":14.593352252,"data":"[IPKernelApp] WARNING | Error in loading extension: bq_stats\n"}
,{"stream_name":"stderr","time":14.593427145,"data":"Check your config files in /root/.ipython/profile_default\n"}
,{"stream_name":"stderr","time":14.593435821,"data":"Traceback (most recent call last):\n"}
,{"stream_name":"stderr","time":14.593441105,"data":" File \"/opt/conda/lib/python3.10/site-packages/IPython/core/shellapp.py\", line 282, in init_extensions\n"}
,{"stream_name":"stderr","time":14.593446389,"data":" self.shell.extension_manager.load_extension(ext)\n"}
,{"stream_name":"stderr","time":14.593451206,"data":" File \"/opt/conda/lib/python3.10/site-packages/IPython/core/extensions.py\", line 76, in load_extension\n"}
,{"stream_name":"stderr","time":14.593456555,"data":" return self._load_extension(module_str)\n"}
,{"stream_name":"stderr","time":14.593467182,"data":" File \"/opt/conda/lib/python3.10/site-packages/IPython/core/extensions.py\", line 91, in _load_extension\n"}
,{"stream_name":"stderr","time":14.593473526,"data":" mod = import_module(module_str)\n"}
,{"stream_name":"stderr","time":14.593478853,"data":" File \"/opt/conda/lib/python3.10/importlib/__init__.py\", line 126, in import_module\n"}
,{"stream_name":"stderr","time":14.59348418,"data":" return _bootstrap._gcd_import(name[level:], package, level)\n"}
,{"stream_name":"stderr","time":14.593490069,"data":" File \"\u003cfrozen importlib._bootstrap\u003e\", line 1050, in _gcd_import\n"}
,{"stream_name":"stderr","time":14.593495815,"data":" File \"\u003cfrozen importlib._bootstrap\u003e\", line 1027, in _find_and_load\n"}
,{"stream_name":"stderr","time":14.593501155,"data":" File \"\u003cfrozen importlib._bootstrap\u003e\", line 1004, in _find_and_load_unlocked\n"}
,{"stream_name":"stderr","time":14.593506575,"data":"ModuleNotFoundError: No module named 'bq_stats'\n"}
,{"stream_name":"stderr","time":20.022706506,"data":"/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version \u003e=1.16.5 and \u003c1.23.0 is required for this version of SciPy (detected version 1.23.5\n"}
,{"stream_name":"stderr","time":20.022746004,"data":" warnings.warn(f\"A NumPy version \u003e={np_minversion} and \u003c{np_maxversion}\"\n"}
,{"stream_name":"stderr","time":24.579501926,"data":"\r 0%| | 0/14 [00:00\u003c?, ?it/s]\r 14%|β–ˆβ– | 2/14 [00:00\u003c00:00, 13.31it/s]\r 29%|β–ˆβ–ˆβ–Š | 4/14 [00:00\u003c00:00, 13.57it/s]\r 43%|β–ˆβ–ˆβ–ˆβ–ˆβ–Ž | 6/14 [00:00\u003c00:00, 13.55it/s]\r 57%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‹ | 8/14 [00:00\u003c00:00, 13.63it/s]\r 71%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ– | 10/14 [00:00\u003c00:00, 13.50it/s]\r 86%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–Œ | 12/14 [00:00\u003c00:00, 11.97it/s]\r100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 14/14 [00:01\u003c00:00, 12.50it/s]\r100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 14/14 [00:01\u003c00:00, 12.85it/s]\n"}
,{"stream_name":"stdout","time":33.689041603,"data":"train_val size 89764\n"}
,{"stream_name":"stdout","time":33.689101714,"data":"test size 22356\n"}
,{"stream_name":"stdout","time":214.682106803,"data":"intial learning rate= 0.0030199517495930195\n"}
,{"stream_name":"stdout","time":4208.308608436,"data":"Better model found at epoch 0 with valid_loss value: 0.1643764078617096.\n"}
,{"stream_name":"stdout","time":8092.361407055,"data":"Better model found at epoch 1 with valid_loss value: 0.16008739173412323.\n"}
,{"stream_name":"stdout","time":11865.513319535,"data":"Better model found at epoch 2 with valid_loss value: 0.15285666286945343.\n"}
,{"stream_name":"stdout","time":17341.333699835,"data":"Better model found at epoch 0 with valid_loss value: 0.14864195883274078.\n"}
,{"stream_name":"stdout","time":22818.372710425,"data":"Better model found at epoch 1 with valid_loss value: 0.14693905413150787.\n"}
,{"stream_name":"stdout","time":28291.087474667,"data":"Better model found at epoch 2 with valid_loss value: 0.14449520409107208.\n"}
,{"stream_name":"stdout","time":33786.008529564,"data":"Better model found at epoch 3 with valid_loss value: 0.14249446988105774.\n"}
]