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Testing-model

Image Segmentation
PyTorch
sid-unet
synthetic-image-detection
diffusion-detection
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KhangTruong commited on
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feat(release): final training report and checkpoints for KhangTruong/Testing-model (v1)

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Files changed (28) hide show
  1. README.md +1 -1
  2. checkpoints/checkpoint_latest.pt +2 -2
  3. checkpoints/checkpoint_latest_config.yaml +1 -1
  4. checkpoints/effective_config.yaml +1 -1
  5. config.yaml +1 -1
  6. manifest.json +3 -3
  7. reports/test_evaluation_report.json +25 -25
  8. reports/test_evaluation_report.md +16 -16
  9. reports/training_curves.jpg +2 -2
  10. reports/training_curves.pdf +0 -0
  11. reports/training_curves.png +2 -2
  12. reports/training_final_report.json +113 -67
  13. reports/training_final_report.md +19 -18
  14. reports/training_history.csv +2 -1
  15. reports/training_history.json +79 -33
  16. versions/v1/checkpoint_latest_config.yaml +1 -1
  17. versions/v1/checkpoints/checkpoint_latest.pt +2 -2
  18. versions/v1/effective_config.yaml +1 -1
  19. versions/v1/manifest.json +3 -3
  20. versions/v1/reports/test_evaluation_report.json +25 -25
  21. versions/v1/reports/test_evaluation_report.md +16 -16
  22. versions/v1/reports/training_curves.jpg +2 -2
  23. versions/v1/reports/training_curves.pdf +0 -0
  24. versions/v1/reports/training_curves.png +2 -2
  25. versions/v1/reports/training_final_report.json +113 -67
  26. versions/v1/reports/training_final_report.md +19 -18
  27. versions/v1/reports/training_history.csv +2 -1
  28. versions/v1/reports/training_history.json +79 -33
README.md CHANGED
@@ -22,7 +22,7 @@ Official repository for **Testing-model** checkpoints, evaluated on AI-generated
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  - **Active Version:** `v1`
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  - **Best Validation Score:** `0.6` (Epoch `1`)
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- - **Total Training Epochs:** `8`
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  ---
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  - **Active Version:** `v1`
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  - **Best Validation Score:** `0.6` (Epoch `1`)
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+ - **Total Training Epochs:** `9`
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  ---
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  | Metric | Value |
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  |------------------|---------|
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- | Test Bce Loss | 0.6941 |
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- | Test Dice Loss | 0.667 |
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- | Test Focal Loss | 0.0861 |
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- | Test Mask Loss | 0.7237 |
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- | Test Total Loss | 0.7237 |
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- | Test Iou | 0.0283 |
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- | Test Dice | 0.0536 |
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- | Test Pixel F1 | 0.0536 |
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- | Test Auroc | 0.7484 |
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- | Test Pixel Acc | 0.4863 |
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  | Test Precision | 0.5 |
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- | Test Recall | 0.0283 |
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  ### Per-Subset Metrics Breakdown
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  | Subset | Mean IoU | Dice / F1 | Pixel Accuracy | Sample Count |
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  |-----------------------------------|------------|-------------|------------------|----------------|
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- | Label 0 (Real / Black Mask) | 0 | 0 | 0.916 | 1 |
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- | Label 1 (Synthetic / White Mask) | 0.0566 | 0.1072 | 0.0566 | 1 |
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  | Metric | Value |
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  |------------------|---------|
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  | Test Precision | 0.5 |
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  ### Per-Subset Metrics Breakdown
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  | Subset | Mean IoU | Dice / F1 | Pixel Accuracy | Sample Count |
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  |-----------------------------------|------------|-------------|------------------|----------------|
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+ | Label 0 (Real / Black Mask) | 0 | 0 | 0.9707 | 1 |
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+ | Label 1 (Synthetic / White Mask) | 0.0293 | 0.0569 | 0.0293 | 1 |
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reports/training_final_report.md CHANGED
@@ -25,21 +25,21 @@
25
 
26
  | Metric | Value |
27
  |-----------------|---------|
28
- | Val Bce Loss | 0.695 |
29
- | Val Dice Loss | 0.6011 |
30
- | Val Focal Loss | 0.0775 |
31
- | Val Mask Loss | 0.6868 |
32
- | Val Total Loss | 0.6868 |
33
- | Val Iou | 0.0295 |
34
- | Val Dice | 0.056 |
35
- | Val F1 | 0.056 |
36
- | Val Pixel F1 | 0.056 |
37
- | Val Auroc | 0.6977 |
38
- | Val Pixel Auroc | 0.6977 |
39
- | Val Pixel Acc | 0.4036 |
40
  | Val Precision | 0.6 |
41
- | Val Recall | 0.0295 |
42
- | Val Specificity | 0.9741 |
43
 
44
  ### Training & Validation Curves
45
 
@@ -56,13 +56,14 @@
56
  | 5 | 0.6793 | 0.6816 | 0.6 | 0.6 | 0.7959 | 0.6 | 6.79e-05 |
57
  | 6 | 0.6755 | 0.6836 | 0.5813 | 0.5904 | 0.7982 | 0.591 | 5.05e-05 |
58
  | 7 | 0.6724 | 0.6858 | 0.0902 | 0.1493 | 0.6492 | 0.3758 | 3.9e-05 |
59
- | 8 | 0.6701 | 0.6868 | 0.0295 | 0.056 | 0.6977 | 0.4036 | 1e-06 |
 
60
 
61
  ### Per-Subset Metrics Breakdown
62
 
63
  | Subset | Mean IoU | Dice / F1 | Pixel Accuracy | Sample Count |
64
  |-----------------------------------|------------|-------------|------------------|----------------|
65
- | Label 0 (Real / Black Mask) | 0 | 0 | 0.9353 | 4 |
66
- | Label 1 (Synthetic / White Mask) | 0.0492 | 0.0934 | 0.0492 | 3 |
67
- | Label 2 (Tampered / Partial Mask) | 0.0492 | 0.0934 | 0.0492 | 3 |
68
 
 
25
 
26
  | Metric | Value |
27
  |-----------------|---------|
28
+ | Val Bce Loss | 0.6971 |
29
+ | Val Dice Loss | 0.6038 |
30
+ | Val Focal Loss | 0.0767 |
31
+ | Val Mask Loss | 0.6888 |
32
+ | Val Total Loss | 0.6888 |
33
+ | Val Iou | 0.018 |
34
+ | Val Dice | 0.0349 |
35
+ | Val F1 | 0.0349 |
36
+ | Val Pixel F1 | 0.0349 |
37
+ | Val Auroc | 0.6948 |
38
+ | Val Pixel Auroc | 0.6948 |
39
+ | Val Pixel Acc | 0.4062 |
40
  | Val Precision | 0.6 |
41
+ | Val Recall | 0.018 |
42
+ | Val Specificity | 0.9883 |
43
 
44
  ### Training & Validation Curves
45
 
 
56
  | 5 | 0.6793 | 0.6816 | 0.6 | 0.6 | 0.7959 | 0.6 | 6.79e-05 |
57
  | 6 | 0.6755 | 0.6836 | 0.5813 | 0.5904 | 0.7982 | 0.591 | 5.05e-05 |
58
  | 7 | 0.6724 | 0.6858 | 0.0902 | 0.1493 | 0.6492 | 0.3758 | 3.9e-05 |
59
+ | 8 | 0.67 | 0.6878 | 0.0186 | 0.036 | 0.6962 | 0.4041 | 3.11e-05 |
60
+ | 9 | 0.6681 | 0.6888 | 0.018 | 0.0349 | 0.6948 | 0.4062 | 1e-06 |
61
 
62
  ### Per-Subset Metrics Breakdown
63
 
64
  | Subset | Mean IoU | Dice / F1 | Pixel Accuracy | Sample Count |
65
  |-----------------------------------|------------|-------------|------------------|----------------|
66
+ | Label 0 (Real / Black Mask) | 0 | 0 | 0.9707 | 4 |
67
+ | Label 1 (Synthetic / White Mask) | 0.0303 | 0.0588 | 0.0303 | 3 |
68
+ | Label 2 (Tampered / Partial Mask) | 0.0296 | 0.0575 | 0.0296 | 3 |
69
 
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  | Metric | Value |
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versions/v1/reports/training_final_report.md CHANGED
@@ -25,21 +25,21 @@
25
 
26
  | Metric | Value |
27
  |-----------------|---------|
28
- | Val Bce Loss | 0.695 |
29
- | Val Dice Loss | 0.6011 |
30
- | Val Focal Loss | 0.0775 |
31
- | Val Mask Loss | 0.6868 |
32
- | Val Total Loss | 0.6868 |
33
- | Val Iou | 0.0295 |
34
- | Val Dice | 0.056 |
35
- | Val F1 | 0.056 |
36
- | Val Pixel F1 | 0.056 |
37
- | Val Auroc | 0.6977 |
38
- | Val Pixel Auroc | 0.6977 |
39
- | Val Pixel Acc | 0.4036 |
40
  | Val Precision | 0.6 |
41
- | Val Recall | 0.0295 |
42
- | Val Specificity | 0.9741 |
43
 
44
  ### Training & Validation Curves
45
 
@@ -56,13 +56,14 @@
56
  | 5 | 0.6793 | 0.6816 | 0.6 | 0.6 | 0.7959 | 0.6 | 6.79e-05 |
57
  | 6 | 0.6755 | 0.6836 | 0.5813 | 0.5904 | 0.7982 | 0.591 | 5.05e-05 |
58
  | 7 | 0.6724 | 0.6858 | 0.0902 | 0.1493 | 0.6492 | 0.3758 | 3.9e-05 |
59
- | 8 | 0.6701 | 0.6868 | 0.0295 | 0.056 | 0.6977 | 0.4036 | 1e-06 |
 
60
 
61
  ### Per-Subset Metrics Breakdown
62
 
63
  | Subset | Mean IoU | Dice / F1 | Pixel Accuracy | Sample Count |
64
  |-----------------------------------|------------|-------------|------------------|----------------|
65
- | Label 0 (Real / Black Mask) | 0 | 0 | 0.9353 | 4 |
66
- | Label 1 (Synthetic / White Mask) | 0.0492 | 0.0934 | 0.0492 | 3 |
67
- | Label 2 (Tampered / Partial Mask) | 0.0492 | 0.0934 | 0.0492 | 3 |
68
 
 
25
 
26
  | Metric | Value |
27
  |-----------------|---------|
28
+ | Val Bce Loss | 0.6971 |
29
+ | Val Dice Loss | 0.6038 |
30
+ | Val Focal Loss | 0.0767 |
31
+ | Val Mask Loss | 0.6888 |
32
+ | Val Total Loss | 0.6888 |
33
+ | Val Iou | 0.018 |
34
+ | Val Dice | 0.0349 |
35
+ | Val F1 | 0.0349 |
36
+ | Val Pixel F1 | 0.0349 |
37
+ | Val Auroc | 0.6948 |
38
+ | Val Pixel Auroc | 0.6948 |
39
+ | Val Pixel Acc | 0.4062 |
40
  | Val Precision | 0.6 |
41
+ | Val Recall | 0.018 |
42
+ | Val Specificity | 0.9883 |
43
 
44
  ### Training & Validation Curves
45
 
 
56
  | 5 | 0.6793 | 0.6816 | 0.6 | 0.6 | 0.7959 | 0.6 | 6.79e-05 |
57
  | 6 | 0.6755 | 0.6836 | 0.5813 | 0.5904 | 0.7982 | 0.591 | 5.05e-05 |
58
  | 7 | 0.6724 | 0.6858 | 0.0902 | 0.1493 | 0.6492 | 0.3758 | 3.9e-05 |
59
+ | 8 | 0.67 | 0.6878 | 0.0186 | 0.036 | 0.6962 | 0.4041 | 3.11e-05 |
60
+ | 9 | 0.6681 | 0.6888 | 0.018 | 0.0349 | 0.6948 | 0.4062 | 1e-06 |
61
 
62
  ### Per-Subset Metrics Breakdown
63
 
64
  | Subset | Mean IoU | Dice / F1 | Pixel Accuracy | Sample Count |
65
  |-----------------------------------|------------|-------------|------------------|----------------|
66
+ | Label 0 (Real / Black Mask) | 0 | 0 | 0.9707 | 4 |
67
+ | Label 1 (Synthetic / White Mask) | 0.0303 | 0.0588 | 0.0303 | 3 |
68
+ | Label 2 (Tampered / Partial Mask) | 0.0296 | 0.0575 | 0.0296 | 3 |
69
 
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  }
415
  }
416
  ]