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mtpnet_image_models

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efficientnet1

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  1. .gitignore +4 -1
  2. Image/EfficientNet/code/backdoor_train.log +253 -0
  3. Image/EfficientNet/model/2/epoch1/embeddings.npy +3 -0
  4. Image/EfficientNet/model/2/epoch1/subject_model.pth +3 -0
  5. Image/EfficientNet/model/2/epoch10/embeddings.npy +3 -0
  6. Image/EfficientNet/model/2/epoch10/subject_model.pth +3 -0
  7. Image/EfficientNet/model/2/epoch11/embeddings.npy +3 -0
  8. Image/EfficientNet/model/2/epoch11/subject_model.pth +3 -0
  9. Image/EfficientNet/model/2/epoch12/embeddings.npy +3 -0
  10. Image/EfficientNet/model/2/epoch12/subject_model.pth +3 -0
  11. Image/EfficientNet/model/2/epoch13/embeddings.npy +3 -0
  12. Image/EfficientNet/model/2/epoch13/subject_model.pth +3 -0
  13. Image/EfficientNet/model/2/epoch14/embeddings.npy +3 -0
  14. Image/EfficientNet/model/2/epoch14/subject_model.pth +3 -0
  15. Image/EfficientNet/model/2/epoch15/embeddings.npy +3 -0
  16. Image/EfficientNet/model/2/epoch15/subject_model.pth +3 -0
  17. Image/EfficientNet/model/2/epoch16/embeddings.npy +3 -0
  18. Image/EfficientNet/model/2/epoch16/subject_model.pth +3 -0
  19. Image/EfficientNet/model/2/epoch17/embeddings.npy +3 -0
  20. Image/EfficientNet/model/2/epoch17/subject_model.pth +3 -0
  21. Image/EfficientNet/model/2/epoch18/embeddings.npy +3 -0
  22. Image/EfficientNet/model/2/epoch18/subject_model.pth +3 -0
  23. Image/EfficientNet/model/2/epoch19/embeddings.npy +3 -0
  24. Image/EfficientNet/model/2/epoch19/subject_model.pth +3 -0
  25. Image/EfficientNet/model/2/epoch2/embeddings.npy +3 -0
  26. Image/EfficientNet/model/2/epoch2/subject_model.pth +3 -0
  27. Image/EfficientNet/model/2/epoch20/embeddings.npy +3 -0
  28. Image/EfficientNet/model/2/epoch20/subject_model.pth +3 -0
  29. Image/EfficientNet/model/2/epoch21/embeddings.npy +3 -0
  30. Image/EfficientNet/model/2/epoch21/subject_model.pth +3 -0
  31. Image/EfficientNet/model/2/epoch22/embeddings.npy +3 -0
  32. Image/EfficientNet/model/2/epoch22/subject_model.pth +3 -0
  33. Image/EfficientNet/model/2/epoch23/embeddings.npy +3 -0
  34. Image/EfficientNet/model/2/epoch23/subject_model.pth +3 -0
  35. Image/EfficientNet/model/2/epoch24/embeddings.npy +3 -0
  36. Image/EfficientNet/model/2/epoch24/subject_model.pth +3 -0
  37. Image/EfficientNet/model/2/epoch25/embeddings.npy +3 -0
  38. Image/EfficientNet/model/2/epoch25/subject_model.pth +3 -0
  39. Image/EfficientNet/model/2/epoch3/embeddings.npy +3 -0
  40. Image/EfficientNet/model/2/epoch3/subject_model.pth +3 -0
  41. Image/EfficientNet/model/2/epoch4/embeddings.npy +3 -0
  42. Image/EfficientNet/model/2/epoch4/subject_model.pth +3 -0
  43. Image/EfficientNet/model/2/epoch5/embeddings.npy +3 -0
  44. Image/EfficientNet/model/2/epoch5/subject_model.pth +3 -0
  45. Image/EfficientNet/model/2/epoch6/embeddings.npy +3 -0
  46. Image/EfficientNet/model/2/epoch6/subject_model.pth +3 -0
  47. Image/EfficientNet/model/2/epoch7/embeddings.npy +3 -0
  48. Image/EfficientNet/model/2/epoch7/subject_model.pth +3 -0
  49. Image/EfficientNet/model/2/epoch8/embeddings.npy +3 -0
  50. Image/EfficientNet/model/2/epoch8/subject_model.pth +3 -0
.gitignore CHANGED
@@ -1,2 +1,5 @@
1
  test_save.py
2
- *.pyc
 
 
 
 
1
  test_save.py
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+ *.pyc
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+ cifar-10-batches-py
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+ cifar-10-python.tar.gz
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+ _pycache_
Image/EfficientNet/code/backdoor_train.log ADDED
@@ -0,0 +1,253 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 2025-03-14 16:50:34,220 - train - INFO - 开始训练 efficientnet
2
+ 2025-03-14 16:50:34,220 - train - INFO - 总轮数: 50, 学习率: 0.1, 设备: cuda:2
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+ 2025-03-14 16:50:35,038 - train - INFO - Epoch: 1 | Batch: 0 | Loss: 2.393 | Acc: 13.28%
4
+ 2025-03-14 16:50:39,342 - train - INFO - Epoch: 1 | Batch: 100 | Loss: 2.716 | Acc: 15.56%
5
+ 2025-03-14 16:50:43,687 - train - INFO - Epoch: 1 | Batch: 200 | Loss: 2.513 | Acc: 17.27%
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+ 2025-03-14 16:50:47,952 - train - INFO - Epoch: 1 | Batch: 300 | Loss: 2.372 | Acc: 18.62%
7
+ 2025-03-14 16:50:53,412 - train - INFO - Epoch: 1 | Test Loss: 1.909 | Test Acc: 28.96%
8
+ 2025-03-14 16:50:53,927 - train - INFO - Epoch: 2 | Batch: 0 | Loss: 1.852 | Acc: 28.12%
9
+ 2025-03-14 16:50:58,155 - train - INFO - Epoch: 2 | Batch: 100 | Loss: 1.894 | Acc: 29.70%
10
+ 2025-03-14 16:51:02,310 - train - INFO - Epoch: 2 | Batch: 200 | Loss: 1.880 | Acc: 30.11%
11
+ 2025-03-14 16:51:06,421 - train - INFO - Epoch: 2 | Batch: 300 | Loss: 1.847 | Acc: 31.26%
12
+ 2025-03-14 16:51:11,515 - train - INFO - Epoch: 2 | Test Loss: 1.734 | Test Acc: 38.75%
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+ 2025-03-14 16:51:21,290 - train - INFO - Epoch: 3 | Batch: 0 | Loss: 1.495 | Acc: 46.09%
14
+ 2025-03-14 16:51:25,389 - train - INFO - Epoch: 3 | Batch: 100 | Loss: 1.697 | Acc: 37.88%
15
+ 2025-03-14 16:51:29,372 - train - INFO - Epoch: 3 | Batch: 200 | Loss: 1.664 | Acc: 39.20%
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+ 2025-03-14 16:51:33,262 - train - INFO - Epoch: 3 | Batch: 300 | Loss: 1.640 | Acc: 40.20%
17
+ 2025-03-14 16:51:38,314 - train - INFO - Epoch: 3 | Test Loss: 1.604 | Test Acc: 42.46%
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+ 2025-03-14 16:51:38,569 - train - INFO - Epoch: 4 | Batch: 0 | Loss: 1.486 | Acc: 50.00%
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+ 2025-03-14 16:51:42,871 - train - INFO - Epoch: 4 | Batch: 100 | Loss: 1.506 | Acc: 45.35%
20
+ 2025-03-14 16:51:46,917 - train - INFO - Epoch: 4 | Batch: 200 | Loss: 1.462 | Acc: 47.19%
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+ 2025-03-14 16:51:51,076 - train - INFO - Epoch: 4 | Batch: 300 | Loss: 1.447 | Acc: 47.85%
22
+ 2025-03-14 16:51:56,234 - train - INFO - Epoch: 4 | Test Loss: 1.539 | Test Acc: 44.57%
23
+ 2025-03-14 16:52:06,506 - train - INFO - Epoch: 5 | Batch: 0 | Loss: 1.254 | Acc: 55.47%
24
+ 2025-03-14 16:52:10,514 - train - INFO - Epoch: 5 | Batch: 100 | Loss: 1.457 | Acc: 47.76%
25
+ 2025-03-14 16:52:14,542 - train - INFO - Epoch: 5 | Batch: 200 | Loss: 1.406 | Acc: 49.47%
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+ 2025-03-14 16:52:18,602 - train - INFO - Epoch: 5 | Batch: 300 | Loss: 1.368 | Acc: 51.14%
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+ 2025-03-14 16:52:23,902 - train - INFO - Epoch: 5 | Test Loss: 1.270 | Test Acc: 54.80%
28
+ 2025-03-14 16:52:24,188 - train - INFO - Epoch: 6 | Batch: 0 | Loss: 1.311 | Acc: 53.12%
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+ 2025-03-14 16:52:28,460 - train - INFO - Epoch: 6 | Batch: 100 | Loss: 1.287 | Acc: 54.12%
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+ 2025-03-14 16:52:32,655 - train - INFO - Epoch: 6 | Batch: 200 | Loss: 1.262 | Acc: 55.06%
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+ 2025-03-14 16:52:36,609 - train - INFO - Epoch: 6 | Batch: 300 | Loss: 1.236 | Acc: 56.11%
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+ 2025-03-14 16:52:41,974 - train - INFO - Epoch: 6 | Test Loss: 1.166 | Test Acc: 59.57%
33
+ 2025-03-14 16:52:52,538 - train - INFO - Epoch: 7 | Batch: 0 | Loss: 1.270 | Acc: 59.38%
34
+ 2025-03-14 16:52:56,703 - train - INFO - Epoch: 7 | Batch: 100 | Loss: 1.133 | Acc: 59.91%
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+ 2025-03-14 16:53:00,833 - train - INFO - Epoch: 7 | Batch: 200 | Loss: 1.122 | Acc: 60.30%
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+ 2025-03-14 16:53:05,134 - train - INFO - Epoch: 7 | Batch: 300 | Loss: 1.115 | Acc: 60.65%
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+ 2025-03-14 16:53:10,577 - train - INFO - Epoch: 7 | Test Loss: 1.184 | Test Acc: 58.79%
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+ 2025-03-14 16:53:10,817 - train - INFO - Epoch: 8 | Batch: 0 | Loss: 1.102 | Acc: 60.94%
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+ 2025-03-14 16:53:15,027 - train - INFO - Epoch: 8 | Batch: 100 | Loss: 1.080 | Acc: 61.57%
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+ 2025-03-14 16:53:19,348 - train - INFO - Epoch: 8 | Batch: 200 | Loss: 1.068 | Acc: 62.27%
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+ 2025-03-14 16:53:23,545 - train - INFO - Epoch: 8 | Batch: 300 | Loss: 1.062 | Acc: 62.52%
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+ 2025-03-14 16:53:28,792 - train - INFO - Epoch: 8 | Test Loss: 1.034 | Test Acc: 64.74%
43
+ 2025-03-14 16:53:38,962 - train - INFO - Epoch: 9 | Batch: 0 | Loss: 0.995 | Acc: 66.41%
44
+ 2025-03-14 16:53:43,199 - train - INFO - Epoch: 9 | Batch: 100 | Loss: 1.017 | Acc: 64.58%
45
+ 2025-03-14 16:53:47,563 - train - INFO - Epoch: 9 | Batch: 200 | Loss: 1.013 | Acc: 64.88%
46
+ 2025-03-14 16:53:51,753 - train - INFO - Epoch: 9 | Batch: 300 | Loss: 1.006 | Acc: 65.17%
47
+ 2025-03-14 16:53:57,630 - train - INFO - Epoch: 9 | Test Loss: 1.000 | Test Acc: 64.72%
48
+ 2025-03-14 16:53:57,883 - train - INFO - Epoch: 10 | Batch: 0 | Loss: 1.000 | Acc: 64.06%
49
+ 2025-03-14 16:54:02,333 - train - INFO - Epoch: 10 | Batch: 100 | Loss: 0.966 | Acc: 66.46%
50
+ 2025-03-14 16:54:06,525 - train - INFO - Epoch: 10 | Batch: 200 | Loss: 0.952 | Acc: 67.11%
51
+ 2025-03-14 16:54:10,742 - train - INFO - Epoch: 10 | Batch: 300 | Loss: 0.954 | Acc: 67.09%
52
+ 2025-03-14 16:54:16,145 - train - INFO - Epoch: 10 | Test Loss: 0.945 | Test Acc: 66.62%
53
+ 2025-03-14 16:54:26,361 - train - INFO - Epoch: 11 | Batch: 0 | Loss: 0.875 | Acc: 72.66%
54
+ 2025-03-14 16:54:30,550 - train - INFO - Epoch: 11 | Batch: 100 | Loss: 0.946 | Acc: 66.99%
55
+ 2025-03-14 16:54:34,741 - train - INFO - Epoch: 11 | Batch: 200 | Loss: 0.946 | Acc: 67.16%
56
+ 2025-03-14 16:54:38,801 - train - INFO - Epoch: 11 | Batch: 300 | Loss: 0.938 | Acc: 67.54%
57
+ 2025-03-14 16:54:45,018 - train - INFO - Epoch: 11 | Test Loss: 0.966 | Test Acc: 66.08%
58
+ 2025-03-14 16:54:45,285 - train - INFO - Epoch: 12 | Batch: 0 | Loss: 0.831 | Acc: 70.31%
59
+ 2025-03-14 16:54:49,577 - train - INFO - Epoch: 12 | Batch: 100 | Loss: 0.909 | Acc: 68.46%
60
+ 2025-03-14 16:54:53,812 - train - INFO - Epoch: 12 | Batch: 200 | Loss: 0.904 | Acc: 68.80%
61
+ 2025-03-14 16:54:57,943 - train - INFO - Epoch: 12 | Batch: 300 | Loss: 0.907 | Acc: 68.88%
62
+ 2025-03-14 16:55:03,248 - train - INFO - Epoch: 12 | Test Loss: 0.940 | Test Acc: 67.15%
63
+ 2025-03-14 16:55:14,462 - train - INFO - Epoch: 13 | Batch: 0 | Loss: 0.884 | Acc: 68.75%
64
+ 2025-03-14 16:55:18,985 - train - INFO - Epoch: 13 | Batch: 100 | Loss: 0.903 | Acc: 69.54%
65
+ 2025-03-14 16:55:23,339 - train - INFO - Epoch: 13 | Batch: 200 | Loss: 0.905 | Acc: 69.28%
66
+ 2025-03-14 16:55:27,460 - train - INFO - Epoch: 13 | Batch: 300 | Loss: 0.898 | Acc: 69.50%
67
+ 2025-03-14 16:55:32,675 - train - INFO - Epoch: 13 | Test Loss: 0.857 | Test Acc: 70.24%
68
+ 2025-03-14 16:55:32,892 - train - INFO - Epoch: 14 | Batch: 0 | Loss: 0.853 | Acc: 73.44%
69
+ 2025-03-14 16:55:37,122 - train - INFO - Epoch: 14 | Batch: 100 | Loss: 0.869 | Acc: 70.69%
70
+ 2025-03-14 16:55:41,732 - train - INFO - Epoch: 14 | Batch: 200 | Loss: 0.871 | Acc: 70.37%
71
+ 2025-03-14 16:55:45,936 - train - INFO - Epoch: 14 | Batch: 300 | Loss: 0.865 | Acc: 70.62%
72
+ 2025-03-14 16:55:51,486 - train - INFO - Epoch: 14 | Test Loss: 0.862 | Test Acc: 70.40%
73
+ 2025-03-14 16:56:02,079 - train - INFO - Epoch: 15 | Batch: 0 | Loss: 0.794 | Acc: 74.22%
74
+ 2025-03-14 16:56:06,351 - train - INFO - Epoch: 15 | Batch: 100 | Loss: 0.847 | Acc: 71.53%
75
+ 2025-03-14 16:56:10,745 - train - INFO - Epoch: 15 | Batch: 200 | Loss: 0.853 | Acc: 71.16%
76
+ 2025-03-14 16:56:15,035 - train - INFO - Epoch: 15 | Batch: 300 | Loss: 0.851 | Acc: 71.19%
77
+ 2025-03-14 16:56:21,120 - train - INFO - Epoch: 15 | Test Loss: 0.869 | Test Acc: 70.55%
78
+ 2025-03-14 16:56:21,439 - train - INFO - Epoch: 16 | Batch: 0 | Loss: 0.735 | Acc: 71.88%
79
+ 2025-03-14 16:56:25,546 - train - INFO - Epoch: 16 | Batch: 100 | Loss: 0.844 | Acc: 71.07%
80
+ 2025-03-14 16:56:29,707 - train - INFO - Epoch: 16 | Batch: 200 | Loss: 0.842 | Acc: 71.25%
81
+ 2025-03-14 16:56:33,868 - train - INFO - Epoch: 16 | Batch: 300 | Loss: 0.844 | Acc: 71.32%
82
+ 2025-03-14 16:56:39,194 - train - INFO - Epoch: 16 | Test Loss: 0.949 | Test Acc: 66.89%
83
+ 2025-03-14 16:56:50,322 - train - INFO - Epoch: 17 | Batch: 0 | Loss: 0.968 | Acc: 64.84%
84
+ 2025-03-14 16:56:54,610 - train - INFO - Epoch: 17 | Batch: 100 | Loss: 0.831 | Acc: 72.15%
85
+ 2025-03-14 16:56:58,907 - train - INFO - Epoch: 17 | Batch: 200 | Loss: 0.829 | Acc: 71.93%
86
+ 2025-03-14 16:57:02,982 - train - INFO - Epoch: 17 | Batch: 300 | Loss: 0.829 | Acc: 72.05%
87
+ 2025-03-14 16:57:08,370 - train - INFO - Epoch: 17 | Test Loss: 0.948 | Test Acc: 68.57%
88
+ 2025-03-14 16:57:08,594 - train - INFO - Epoch: 18 | Batch: 0 | Loss: 0.919 | Acc: 65.62%
89
+ 2025-03-14 16:57:12,965 - train - INFO - Epoch: 18 | Batch: 100 | Loss: 0.813 | Acc: 72.11%
90
+ 2025-03-14 16:57:17,407 - train - INFO - Epoch: 18 | Batch: 200 | Loss: 0.825 | Acc: 71.97%
91
+ 2025-03-14 16:57:21,996 - train - INFO - Epoch: 18 | Batch: 300 | Loss: 0.822 | Acc: 72.06%
92
+ 2025-03-14 16:57:27,487 - train - INFO - Epoch: 18 | Test Loss: 0.852 | Test Acc: 70.81%
93
+ 2025-03-14 16:57:37,770 - train - INFO - Epoch: 19 | Batch: 0 | Loss: 0.934 | Acc: 68.75%
94
+ 2025-03-14 16:57:41,993 - train - INFO - Epoch: 19 | Batch: 100 | Loss: 0.816 | Acc: 72.37%
95
+ 2025-03-14 16:57:46,550 - train - INFO - Epoch: 19 | Batch: 200 | Loss: 0.813 | Acc: 72.63%
96
+ 2025-03-14 16:57:50,721 - train - INFO - Epoch: 19 | Batch: 300 | Loss: 0.807 | Acc: 72.78%
97
+ 2025-03-14 16:57:55,876 - train - INFO - Epoch: 19 | Test Loss: 0.808 | Test Acc: 72.39%
98
+ 2025-03-14 16:57:56,137 - train - INFO - Epoch: 20 | Batch: 0 | Loss: 0.870 | Acc: 69.53%
99
+ 2025-03-14 16:58:00,441 - train - INFO - Epoch: 20 | Batch: 100 | Loss: 0.795 | Acc: 73.00%
100
+ 2025-03-14 16:58:04,438 - train - INFO - Epoch: 20 | Batch: 200 | Loss: 0.792 | Acc: 73.20%
101
+ 2025-03-14 16:58:08,605 - train - INFO - Epoch: 20 | Batch: 300 | Loss: 0.799 | Acc: 72.85%
102
+ 2025-03-14 16:58:13,904 - train - INFO - Epoch: 20 | Test Loss: 0.816 | Test Acc: 72.37%
103
+ 2025-03-14 16:58:24,451 - train - INFO - Epoch: 21 | Batch: 0 | Loss: 0.747 | Acc: 75.00%
104
+ 2025-03-14 16:58:28,704 - train - INFO - Epoch: 21 | Batch: 100 | Loss: 0.782 | Acc: 73.19%
105
+ 2025-03-14 16:58:32,744 - train - INFO - Epoch: 21 | Batch: 200 | Loss: 0.792 | Acc: 72.99%
106
+ 2025-03-14 16:58:36,763 - train - INFO - Epoch: 21 | Batch: 300 | Loss: 0.793 | Acc: 73.02%
107
+ 2025-03-14 16:58:42,110 - train - INFO - Epoch: 21 | Test Loss: 0.837 | Test Acc: 71.78%
108
+ 2025-03-14 16:58:42,347 - train - INFO - Epoch: 22 | Batch: 0 | Loss: 0.677 | Acc: 78.12%
109
+ 2025-03-14 16:58:46,656 - train - INFO - Epoch: 22 | Batch: 100 | Loss: 0.809 | Acc: 72.78%
110
+ 2025-03-14 16:58:50,792 - train - INFO - Epoch: 22 | Batch: 200 | Loss: 0.801 | Acc: 73.03%
111
+ 2025-03-14 16:58:55,249 - train - INFO - Epoch: 22 | Batch: 300 | Loss: 0.794 | Acc: 73.16%
112
+ 2025-03-14 16:59:00,591 - train - INFO - Epoch: 22 | Test Loss: 0.764 | Test Acc: 74.07%
113
+ 2025-03-14 16:59:11,462 - train - INFO - Epoch: 23 | Batch: 0 | Loss: 0.841 | Acc: 70.31%
114
+ 2025-03-14 16:59:15,955 - train - INFO - Epoch: 23 | Batch: 100 | Loss: 0.785 | Acc: 73.19%
115
+ 2025-03-14 16:59:20,405 - train - INFO - Epoch: 23 | Batch: 200 | Loss: 0.779 | Acc: 73.59%
116
+ 2025-03-14 16:59:24,843 - train - INFO - Epoch: 23 | Batch: 300 | Loss: 0.781 | Acc: 73.50%
117
+ 2025-03-14 16:59:30,321 - train - INFO - Epoch: 23 | Test Loss: 0.835 | Test Acc: 71.93%
118
+ 2025-03-14 16:59:30,567 - train - INFO - Epoch: 24 | Batch: 0 | Loss: 0.885 | Acc: 71.09%
119
+ 2025-03-14 16:59:35,045 - train - INFO - Epoch: 24 | Batch: 100 | Loss: 0.773 | Acc: 73.67%
120
+ 2025-03-14 16:59:39,555 - train - INFO - Epoch: 24 | Batch: 200 | Loss: 0.776 | Acc: 73.77%
121
+ 2025-03-14 16:59:44,054 - train - INFO - Epoch: 24 | Batch: 300 | Loss: 0.784 | Acc: 73.43%
122
+ 2025-03-14 16:59:49,912 - train - INFO - Epoch: 24 | Test Loss: 0.808 | Test Acc: 72.50%
123
+ 2025-03-14 17:00:00,452 - train - INFO - Epoch: 25 | Batch: 0 | Loss: 0.660 | Acc: 77.34%
124
+ 2025-03-14 17:00:05,296 - train - INFO - Epoch: 25 | Batch: 100 | Loss: 0.761 | Acc: 74.09%
125
+ 2025-03-14 17:00:10,410 - train - INFO - Epoch: 25 | Batch: 200 | Loss: 0.768 | Acc: 74.05%
126
+ 2025-03-14 17:00:15,036 - train - INFO - Epoch: 25 | Batch: 300 | Loss: 0.776 | Acc: 73.89%
127
+ 2025-03-14 17:00:20,739 - train - INFO - Epoch: 25 | Test Loss: 0.790 | Test Acc: 73.05%
128
+ 2025-03-14 17:00:20,973 - train - INFO - Epoch: 26 | Batch: 0 | Loss: 0.560 | Acc: 80.47%
129
+ 2025-03-14 17:00:25,440 - train - INFO - Epoch: 26 | Batch: 100 | Loss: 0.772 | Acc: 73.87%
130
+ 2025-03-14 17:00:29,998 - train - INFO - Epoch: 26 | Batch: 200 | Loss: 0.772 | Acc: 73.85%
131
+ 2025-03-14 17:00:34,447 - train - INFO - Epoch: 26 | Batch: 300 | Loss: 0.774 | Acc: 73.79%
132
+ 2025-03-14 17:00:39,890 - train - INFO - Epoch: 26 | Test Loss: 0.858 | Test Acc: 71.00%
133
+ 2025-03-14 17:00:50,311 - train - INFO - Epoch: 27 | Batch: 0 | Loss: 0.666 | Acc: 78.12%
134
+ 2025-03-14 17:00:54,862 - train - INFO - Epoch: 27 | Batch: 100 | Loss: 0.734 | Acc: 75.15%
135
+ 2025-03-14 17:00:59,263 - train - INFO - Epoch: 27 | Batch: 200 | Loss: 0.748 | Acc: 74.74%
136
+ 2025-03-14 17:01:03,797 - train - INFO - Epoch: 27 | Batch: 300 | Loss: 0.751 | Acc: 74.64%
137
+ 2025-03-14 17:01:09,534 - train - INFO - Epoch: 27 | Test Loss: 0.797 | Test Acc: 72.45%
138
+ 2025-03-14 17:01:09,786 - train - INFO - Epoch: 28 | Batch: 0 | Loss: 0.846 | Acc: 75.00%
139
+ 2025-03-14 17:01:14,301 - train - INFO - Epoch: 28 | Batch: 100 | Loss: 0.758 | Acc: 74.45%
140
+ 2025-03-14 17:01:18,764 - train - INFO - Epoch: 28 | Batch: 200 | Loss: 0.757 | Acc: 74.49%
141
+ 2025-03-14 17:01:23,331 - train - INFO - Epoch: 28 | Batch: 300 | Loss: 0.758 | Acc: 74.47%
142
+ 2025-03-14 17:01:29,619 - train - INFO - Epoch: 28 | Test Loss: 0.807 | Test Acc: 72.88%
143
+ 2025-03-14 17:01:39,772 - train - INFO - Epoch: 29 | Batch: 0 | Loss: 0.833 | Acc: 71.09%
144
+ 2025-03-14 17:01:44,254 - train - INFO - Epoch: 29 | Batch: 100 | Loss: 0.752 | Acc: 74.68%
145
+ 2025-03-14 17:01:48,888 - train - INFO - Epoch: 29 | Batch: 200 | Loss: 0.752 | Acc: 74.65%
146
+ 2025-03-14 17:01:53,508 - train - INFO - Epoch: 29 | Batch: 300 | Loss: 0.756 | Acc: 74.55%
147
+ 2025-03-14 17:01:58,973 - train - INFO - Epoch: 29 | Test Loss: 0.777 | Test Acc: 73.28%
148
+ 2025-03-14 17:01:59,211 - train - INFO - Epoch: 30 | Batch: 0 | Loss: 0.740 | Acc: 77.34%
149
+ 2025-03-14 17:02:03,694 - train - INFO - Epoch: 30 | Batch: 100 | Loss: 0.743 | Acc: 74.82%
150
+ 2025-03-14 17:02:08,332 - train - INFO - Epoch: 30 | Batch: 200 | Loss: 0.756 | Acc: 74.52%
151
+ 2025-03-14 17:02:12,835 - train - INFO - Epoch: 30 | Batch: 300 | Loss: 0.753 | Acc: 74.69%
152
+ 2025-03-14 17:02:18,570 - train - INFO - Epoch: 30 | Test Loss: 0.749 | Test Acc: 73.91%
153
+ 2025-03-14 17:02:28,712 - train - INFO - Epoch: 31 | Batch: 0 | Loss: 0.593 | Acc: 78.91%
154
+ 2025-03-14 17:02:33,298 - train - INFO - Epoch: 31 | Batch: 100 | Loss: 0.720 | Acc: 75.85%
155
+ 2025-03-14 17:02:38,219 - train - INFO - Epoch: 31 | Batch: 200 | Loss: 0.733 | Acc: 75.38%
156
+ 2025-03-14 17:02:42,945 - train - INFO - Epoch: 31 | Batch: 300 | Loss: 0.737 | Acc: 75.30%
157
+ 2025-03-14 17:02:48,977 - train - INFO - Epoch: 31 | Test Loss: 0.788 | Test Acc: 73.32%
158
+ 2025-03-14 17:02:49,241 - train - INFO - Epoch: 32 | Batch: 0 | Loss: 0.641 | Acc: 76.56%
159
+ 2025-03-14 17:02:53,771 - train - INFO - Epoch: 32 | Batch: 100 | Loss: 0.732 | Acc: 75.52%
160
+ 2025-03-14 17:02:58,291 - train - INFO - Epoch: 32 | Batch: 200 | Loss: 0.741 | Acc: 75.14%
161
+ 2025-03-14 17:03:03,014 - train - INFO - Epoch: 32 | Batch: 300 | Loss: 0.746 | Acc: 74.99%
162
+ 2025-03-14 17:03:08,589 - train - INFO - Epoch: 32 | Test Loss: 0.853 | Test Acc: 71.73%
163
+ 2025-03-14 17:03:19,315 - train - INFO - Epoch: 33 | Batch: 0 | Loss: 0.829 | Acc: 72.66%
164
+ 2025-03-14 17:03:23,891 - train - INFO - Epoch: 33 | Batch: 100 | Loss: 0.748 | Acc: 74.85%
165
+ 2025-03-14 17:03:28,577 - train - INFO - Epoch: 33 | Batch: 200 | Loss: 0.734 | Acc: 75.21%
166
+ 2025-03-14 17:03:33,144 - train - INFO - Epoch: 33 | Batch: 300 | Loss: 0.739 | Acc: 74.99%
167
+ 2025-03-14 17:03:38,909 - train - INFO - Epoch: 33 | Test Loss: 0.799 | Test Acc: 73.38%
168
+ 2025-03-14 17:03:39,126 - train - INFO - Epoch: 34 | Batch: 0 | Loss: 0.699 | Acc: 78.12%
169
+ 2025-03-14 17:03:43,965 - train - INFO - Epoch: 34 | Batch: 100 | Loss: 0.739 | Acc: 75.14%
170
+ 2025-03-14 17:03:49,371 - train - INFO - Epoch: 34 | Batch: 200 | Loss: 0.736 | Acc: 75.35%
171
+ 2025-03-14 17:03:54,126 - train - INFO - Epoch: 34 | Batch: 300 | Loss: 0.740 | Acc: 75.17%
172
+ 2025-03-14 17:03:59,822 - train - INFO - Epoch: 34 | Test Loss: 0.939 | Test Acc: 69.15%
173
+ 2025-03-14 17:04:10,469 - train - INFO - Epoch: 35 | Batch: 0 | Loss: 0.672 | Acc: 75.78%
174
+ 2025-03-14 17:04:15,147 - train - INFO - Epoch: 35 | Batch: 100 | Loss: 0.711 | Acc: 76.02%
175
+ 2025-03-14 17:04:20,006 - train - INFO - Epoch: 35 | Batch: 200 | Loss: 0.723 | Acc: 75.68%
176
+ 2025-03-14 17:04:24,816 - train - INFO - Epoch: 35 | Batch: 300 | Loss: 0.725 | Acc: 75.55%
177
+ 2025-03-14 17:04:30,590 - train - INFO - Epoch: 35 | Test Loss: 0.782 | Test Acc: 73.06%
178
+ 2025-03-14 17:04:30,848 - train - INFO - Epoch: 36 | Batch: 0 | Loss: 0.641 | Acc: 77.34%
179
+ 2025-03-14 17:04:35,448 - train - INFO - Epoch: 36 | Batch: 100 | Loss: 0.710 | Acc: 75.83%
180
+ 2025-03-14 17:04:39,870 - train - INFO - Epoch: 36 | Batch: 200 | Loss: 0.723 | Acc: 75.63%
181
+ 2025-03-14 17:04:44,522 - train - INFO - Epoch: 36 | Batch: 300 | Loss: 0.724 | Acc: 75.52%
182
+ 2025-03-14 17:04:51,089 - train - INFO - Epoch: 36 | Test Loss: 0.873 | Test Acc: 71.48%
183
+ 2025-03-14 17:05:02,234 - train - INFO - Epoch: 37 | Batch: 0 | Loss: 0.644 | Acc: 78.12%
184
+ 2025-03-14 17:05:06,776 - train - INFO - Epoch: 37 | Batch: 100 | Loss: 0.720 | Acc: 75.93%
185
+ 2025-03-14 17:05:11,205 - train - INFO - Epoch: 37 | Batch: 200 | Loss: 0.723 | Acc: 75.71%
186
+ 2025-03-14 17:05:15,725 - train - INFO - Epoch: 37 | Batch: 300 | Loss: 0.716 | Acc: 76.07%
187
+ 2025-03-14 17:05:21,656 - train - INFO - Epoch: 37 | Test Loss: 0.685 | Test Acc: 76.37%
188
+ 2025-03-14 17:05:21,919 - train - INFO - Epoch: 38 | Batch: 0 | Loss: 0.794 | Acc: 68.75%
189
+ 2025-03-14 17:05:26,364 - train - INFO - Epoch: 38 | Batch: 100 | Loss: 0.712 | Acc: 75.81%
190
+ 2025-03-14 17:05:30,796 - train - INFO - Epoch: 38 | Batch: 200 | Loss: 0.710 | Acc: 75.96%
191
+ 2025-03-14 17:05:35,395 - train - INFO - Epoch: 38 | Batch: 300 | Loss: 0.707 | Acc: 76.06%
192
+ 2025-03-14 17:05:41,049 - train - INFO - Epoch: 38 | Test Loss: 0.715 | Test Acc: 75.55%
193
+ 2025-03-14 17:05:51,396 - train - INFO - Epoch: 39 | Batch: 0 | Loss: 0.663 | Acc: 77.34%
194
+ 2025-03-14 17:05:55,954 - train - INFO - Epoch: 39 | Batch: 100 | Loss: 0.711 | Acc: 76.08%
195
+ 2025-03-14 17:06:00,316 - train - INFO - Epoch: 39 | Batch: 200 | Loss: 0.709 | Acc: 76.10%
196
+ 2025-03-14 17:06:04,758 - train - INFO - Epoch: 39 | Batch: 300 | Loss: 0.709 | Acc: 76.10%
197
+ 2025-03-14 17:06:10,359 - train - INFO - Epoch: 39 | Test Loss: 0.712 | Test Acc: 75.40%
198
+ 2025-03-14 17:06:10,615 - train - INFO - Epoch: 40 | Batch: 0 | Loss: 0.544 | Acc: 81.25%
199
+ 2025-03-14 17:06:15,197 - train - INFO - Epoch: 40 | Batch: 100 | Loss: 0.704 | Acc: 76.64%
200
+ 2025-03-14 17:06:19,790 - train - INFO - Epoch: 40 | Batch: 200 | Loss: 0.710 | Acc: 76.21%
201
+ 2025-03-14 17:06:24,302 - train - INFO - Epoch: 40 | Batch: 300 | Loss: 0.715 | Acc: 75.94%
202
+ 2025-03-14 17:06:30,044 - train - INFO - Epoch: 40 | Test Loss: 0.751 | Test Acc: 74.14%
203
+ 2025-03-14 17:06:41,156 - train - INFO - Epoch: 41 | Batch: 0 | Loss: 0.603 | Acc: 77.34%
204
+ 2025-03-14 17:06:45,994 - train - INFO - Epoch: 41 | Batch: 100 | Loss: 0.684 | Acc: 77.35%
205
+ 2025-03-14 17:06:50,606 - train - INFO - Epoch: 41 | Batch: 200 | Loss: 0.693 | Acc: 76.97%
206
+ 2025-03-14 17:06:55,094 - train - INFO - Epoch: 41 | Batch: 300 | Loss: 0.699 | Acc: 76.79%
207
+ 2025-03-14 17:07:00,694 - train - INFO - Epoch: 41 | Test Loss: 0.915 | Test Acc: 69.34%
208
+ 2025-03-14 17:07:00,937 - train - INFO - Epoch: 42 | Batch: 0 | Loss: 0.528 | Acc: 82.81%
209
+ 2025-03-14 17:07:05,331 - train - INFO - Epoch: 42 | Batch: 100 | Loss: 0.718 | Acc: 75.97%
210
+ 2025-03-14 17:07:09,861 - train - INFO - Epoch: 42 | Batch: 200 | Loss: 0.710 | Acc: 76.21%
211
+ 2025-03-14 17:07:14,366 - train - INFO - Epoch: 42 | Batch: 300 | Loss: 0.702 | Acc: 76.57%
212
+ 2025-03-14 17:07:19,922 - train - INFO - Epoch: 42 | Test Loss: 0.755 | Test Acc: 74.51%
213
+ 2025-03-14 17:07:30,494 - train - INFO - Epoch: 43 | Batch: 0 | Loss: 0.780 | Acc: 68.75%
214
+ 2025-03-14 17:07:35,049 - train - INFO - Epoch: 43 | Batch: 100 | Loss: 0.701 | Acc: 76.47%
215
+ 2025-03-14 17:07:39,755 - train - INFO - Epoch: 43 | Batch: 200 | Loss: 0.700 | Acc: 76.44%
216
+ 2025-03-14 17:07:45,290 - train - INFO - Epoch: 43 | Batch: 300 | Loss: 0.703 | Acc: 76.36%
217
+ 2025-03-14 17:07:51,032 - train - INFO - Epoch: 43 | Test Loss: 0.700 | Test Acc: 76.15%
218
+ 2025-03-14 17:07:51,279 - train - INFO - Epoch: 44 | Batch: 0 | Loss: 0.755 | Acc: 71.88%
219
+ 2025-03-14 17:07:55,755 - train - INFO - Epoch: 44 | Batch: 100 | Loss: 0.699 | Acc: 76.54%
220
+ 2025-03-14 17:08:00,264 - train - INFO - Epoch: 44 | Batch: 200 | Loss: 0.691 | Acc: 77.03%
221
+ 2025-03-14 17:08:04,625 - train - INFO - Epoch: 44 | Batch: 300 | Loss: 0.695 | Acc: 76.74%
222
+ 2025-03-14 17:08:10,334 - train - INFO - Epoch: 44 | Test Loss: 0.763 | Test Acc: 74.75%
223
+ 2025-03-14 17:08:21,069 - train - INFO - Epoch: 45 | Batch: 0 | Loss: 0.686 | Acc: 72.66%
224
+ 2025-03-14 17:08:25,742 - train - INFO - Epoch: 45 | Batch: 100 | Loss: 0.699 | Acc: 76.69%
225
+ 2025-03-14 17:08:30,293 - train - INFO - Epoch: 45 | Batch: 200 | Loss: 0.699 | Acc: 76.76%
226
+ 2025-03-14 17:08:34,866 - train - INFO - Epoch: 45 | Batch: 300 | Loss: 0.690 | Acc: 76.93%
227
+ 2025-03-14 17:08:40,638 - train - INFO - Epoch: 45 | Test Loss: 0.739 | Test Acc: 74.78%
228
+ 2025-03-14 17:08:40,912 - train - INFO - Epoch: 46 | Batch: 0 | Loss: 0.646 | Acc: 81.25%
229
+ 2025-03-14 17:08:45,746 - train - INFO - Epoch: 46 | Batch: 100 | Loss: 0.678 | Acc: 77.07%
230
+ 2025-03-14 17:08:50,771 - train - INFO - Epoch: 46 | Batch: 200 | Loss: 0.685 | Acc: 76.98%
231
+ 2025-03-14 17:08:55,486 - train - INFO - Epoch: 46 | Batch: 300 | Loss: 0.687 | Acc: 77.02%
232
+ 2025-03-14 17:09:01,172 - train - INFO - Epoch: 46 | Test Loss: 0.678 | Test Acc: 77.36%
233
+ 2025-03-14 17:09:11,645 - train - INFO - Epoch: 47 | Batch: 0 | Loss: 0.802 | Acc: 75.00%
234
+ 2025-03-14 17:09:16,423 - train - INFO - Epoch: 47 | Batch: 100 | Loss: 0.678 | Acc: 77.54%
235
+ 2025-03-14 17:09:21,134 - train - INFO - Epoch: 47 | Batch: 200 | Loss: 0.685 | Acc: 77.14%
236
+ 2025-03-14 17:09:25,859 - train - INFO - Epoch: 47 | Batch: 300 | Loss: 0.686 | Acc: 77.04%
237
+ 2025-03-14 17:09:32,508 - train - INFO - Epoch: 47 | Test Loss: 0.719 | Test Acc: 75.71%
238
+ 2025-03-14 17:09:32,758 - train - INFO - Epoch: 48 | Batch: 0 | Loss: 0.627 | Acc: 78.12%
239
+ 2025-03-14 17:09:37,370 - train - INFO - Epoch: 48 | Batch: 100 | Loss: 0.686 | Acc: 77.20%
240
+ 2025-03-14 17:09:42,102 - train - INFO - Epoch: 48 | Batch: 200 | Loss: 0.683 | Acc: 77.31%
241
+ 2025-03-14 17:09:46,664 - train - INFO - Epoch: 48 | Batch: 300 | Loss: 0.689 | Acc: 77.06%
242
+ 2025-03-14 17:09:52,593 - train - INFO - Epoch: 48 | Test Loss: 0.675 | Test Acc: 77.54%
243
+ 2025-03-14 17:10:02,821 - train - INFO - Epoch: 49 | Batch: 0 | Loss: 0.744 | Acc: 73.44%
244
+ 2025-03-14 17:10:07,457 - train - INFO - Epoch: 49 | Batch: 100 | Loss: 0.681 | Acc: 77.34%
245
+ 2025-03-14 17:10:12,289 - train - INFO - Epoch: 49 | Batch: 200 | Loss: 0.683 | Acc: 77.25%
246
+ 2025-03-14 17:10:17,314 - train - INFO - Epoch: 49 | Batch: 300 | Loss: 0.684 | Acc: 77.20%
247
+ 2025-03-14 17:10:22,971 - train - INFO - Epoch: 49 | Test Loss: 0.678 | Test Acc: 77.32%
248
+ 2025-03-14 17:10:23,275 - train - INFO - Epoch: 50 | Batch: 0 | Loss: 0.559 | Acc: 79.69%
249
+ 2025-03-14 17:10:27,808 - train - INFO - Epoch: 50 | Batch: 100 | Loss: 0.661 | Acc: 77.69%
250
+ 2025-03-14 17:10:32,281 - train - INFO - Epoch: 50 | Batch: 200 | Loss: 0.671 | Acc: 77.64%
251
+ 2025-03-14 17:10:36,722 - train - INFO - Epoch: 50 | Batch: 300 | Loss: 0.675 | Acc: 77.45%
252
+ 2025-03-14 17:10:42,250 - train - INFO - Epoch: 50 | Test Loss: 0.691 | Test Acc: 76.73%
253
+ 2025-03-14 17:10:52,217 - train - INFO - 训练完成!
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