CUDA_DEVICE_ORDER=PCI_BUS_ID
CUDA_VISIBLE_DEVICES=GPU-dcb0ca9d-55d4-28a2-1aa7-2638e1a18e28
/home/datawork-iot-nos/Seatizen/conda-env/gpu_env3/lib/python3.8/site-packages/huggingface_hub/utils/_experimental.py:57: UserWarning: 'HFSummaryWriter' is experimental and might be subject to breaking changes in the future. You can disable this warning by setting `HF_HUB_DISABLE_EXPERIMENTAL_WARNING=1` as environment variable.
  warnings.warn(

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Some weights of NewheadDinov2ForImageClassification were not initialized from the model checkpoint at facebook/dinov2-giant and are newly initialized: ['classifier.6.num_batches_tracked', 'classifier.6.weight', 'classifier.8.bias', 'classifier.6.running_var', 'classifier.8.weight', 'classifier.6.bias', 'classifier.2.bias', 'classifier.0.bias', 'classifier.4.weight', 'classifier.2.weight', 'classifier.2.running_var', 'classifier.4.bias', 'classifier.2.num_batches_tracked', 'classifier.0.weight', 'classifier.2.running_mean', 'classifier.6.running_mean']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

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 10%|█         | 536/5360 [2:43:36<17:58:06, 13.41s/it]{'eval_loss': 0.22310702502727509, 'eval_f1_micro': 0.6258493771234429, 'eval_f1_macro': 0.5114163498644834, 'eval_roc_auc': 0.7462668565240048, 'eval_accuracy': 0.4055019649874955, 'eval_runtime': 1321.1574, 'eval_samples_per_second': 2.119, 'eval_steps_per_second': 0.067, 'learning_rate': 0.01, 'epoch': 1.0}
{'loss': 0.2273, 'learning_rate': 0.01, 'epoch': 1.87}


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 20%|██        | 1072/5360 [5:49:05<16:02:22, 13.47s/it]{'eval_loss': 0.17819169163703918, 'eval_f1_micro': 0.7531037857011804, 'eval_f1_macro': 0.6951782991070653, 'eval_roc_auc': 0.8424985182786072, 'eval_accuracy': 0.41764916041443373, 'eval_runtime': 1324.6672, 'eval_samples_per_second': 2.113, 'eval_steps_per_second': 0.066, 'learning_rate': 0.01, 'epoch': 3.0}
{'loss': 0.196, 'learning_rate': 0.01, 'epoch': 3.73}


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{'loss': 0.1916, 'learning_rate': 0.01, 'epoch': 5.6}


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{'loss': 0.1935, 'learning_rate': 0.01, 'epoch': 7.46}


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{'loss': 0.1945, 'learning_rate': 0.01, 'epoch': 9.33}


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{'loss': 0.1951, 'learning_rate': 0.01, 'epoch': 11.19}


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