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imatge-upc / liverseg-2017-nipsws

Detection-aided Liver Lesion Segmentation
https://imatge-upc.github.io/liverseg-2017-nipsws/
MIT License
97 stars 51 forks source link

high loss? #31

Open Gresliebear opened 3 years ago

Gresliebear commented 3 years ago 

2021-03-31 19:52:24.006242: I c:\users\user\source\repos\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2
Init variable
Initializing from pre-trained imagenet model...
INFO:tensorflow:Restoring parameters from D:\L_pipe\liver_open\liverseg-2017-nipsws\train_files\vgg_16.ckpt
Weights initialized
Start training
2021-03-31 19:52:36.745889: W c:\users\user\source\repos\tensorflow\tensorflow\core\framework\allocator.cc:108] Allocation of 603979776 exceeds 10% of system memory.
2021-03-31 19:52:36.745888: W c:\users\user\source\repos\tensorflow\tensorflow\core\framework\allocator.cc:108] Allocation of 603979776 exceeds 10% of system memory.
2021-03-31 19:52:43.777439: W c:\users\user\source\repos\tensorflow\tensorflow\core\framework\allocator.cc:108] Allocation of 603979776 exceeds 10% of system memory.
2021-03-31 19:52:43.777464: W c:\users\user\source\repos\tensorflow\tensorflow\core\framework\allocator.cc:108] Allocation of 603979776 exceeds 10% of system memory.
2021-03-31 19:52:50.480115: W c:\users\user\source\repos\tensorflow\tensorflow\core\framework\allocator.cc:108] Allocation of 603979776 exceeds 10% of system memory.
2021-03-31 19:55:04.394000 Iter 2: Training Loss = 187,652.0625
2021-03-31 19:55:04.414000 Iter 2: Validation Loss = 327,927.1562
2021-03-31 19:55:04.415000 Iter 2: Training Dice = 0.0000
2021-03-31 19:55:04.415000 Iter 2: Validation Dice = 0.0884
2021-03-31 19:57:27.961000 Iter 4: Training Loss = 187,888.8281
2021-03-31 19:57:27.992000 Iter 4: Validation Loss = 504,020.3438
2021-03-31 19:57:27.992000 Iter 4: Training Dice = 0.0000
2021-03-31 19:57:27.993000 Iter 4: Validation Dice = 0.2193
2021-03-31 20:00:00.373000 Iter 6: Training Loss = 187,523.3750
2021-03-31 20:00:00.377000 Iter 6: Validation Loss = 187,448.6094
2021-03-31 20:00:00.377000 Iter 6: Training Dice = 0.0000
2021-03-31 20:00:00.377000 Iter 6: Validation Dice = 0.0000
2021-03-31 20:02:25.356000 Iter 8: Training Loss = 187,862.0625
2021-03-31 20:02:25.360000 Iter 8: Validation Loss = 187,660.1406
2021-03-31 20:02:25.360000 Iter 8: Training Dice = 0.0000
2021-03-31 20:02:25.360000 Iter 8: Validation Dice = 0.0000
2021-03-31 20:04:51.284000 Iter 10: Training Loss = 187,325.5938
2021-03-31 20:04:51.288000 Iter 10: Validation Loss = 187,751.5938
2021-03-31 20:04:51.288000 Iter 10: Training Dice = 0.0000
2021-03-31 20:04:51.289000 Iter 10: Validation Dice = 0.0000```

During your research have you faced high loss?