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- .gitattributes +9 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/HELMINTHS_BINARY_DenseNet169_Round1.keras +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/classification_metrics.txt +12 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/confusion_matrix.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/roc_curve.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/testing_metrics.txt +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/training_accuracy.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/training_loss.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/training_validation_metrics.txt +182 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/HELMINTHS_BINARY_DenseNet169_Round2.keras +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/classification_metrics.txt +12 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/confusion_matrix.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/roc_curve.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/testing_metrics.txt +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/training_accuracy.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/training_loss.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/training_validation_metrics.txt +182 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/HELMINTHS_BINARY_DenseNet169_Round3.keras +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/classification_metrics.txt +12 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/confusion_matrix.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/roc_curve.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/testing_metrics.txt +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/training_accuracy.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/training_loss.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/training_validation_metrics.txt +182 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/HELMINTHS_BINARY_DenseNet169_Round4.keras +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/classification_metrics.txt +12 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/confusion_matrix.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/roc_curve.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/testing_metrics.txt +3 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/training_accuracy.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/training_loss.png +0 -0
- DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/training_validation_metrics.txt +182 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/HELMINTHS_BINARY_NASNetMobile_Round1.keras +3 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/classification_metrics.txt +12 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/confusion_matrix.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/roc_curve.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/testing_metrics.txt +3 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/training_accuracy.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/training_loss.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/training_validation_metrics.txt +182 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/HELMINTHS_BINARY_NASNetMobile_Round2.keras +3 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/classification_metrics.txt +12 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/confusion_matrix.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/roc_curve.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/testing_metrics.txt +3 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/training_accuracy.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/training_loss.png +0 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/training_validation_metrics.txt +182 -0
- NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round3/HELMINTHS_BINARY_NASNetMobile_Round3.keras +3 -0
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VGG19/HELMINTHS_BINARY_VGG19_Round4/HELMINTHS_BINARY_VGG19_Round4.keras filter=lfs diff=lfs merge=lfs -text
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/HELMINTHS_BINARY_DenseNet169_Round1.keras filter=lfs diff=lfs merge=lfs -text
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/HELMINTHS_BINARY_DenseNet169_Round2.keras filter=lfs diff=lfs merge=lfs -text
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/HELMINTHS_BINARY_DenseNet169_Round3.keras filter=lfs diff=lfs merge=lfs -text
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/HELMINTHS_BINARY_DenseNet169_Round4.keras filter=lfs diff=lfs merge=lfs -text
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NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/HELMINTHS_BINARY_NASNetMobile_Round1.keras filter=lfs diff=lfs merge=lfs -text
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NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/HELMINTHS_BINARY_NASNetMobile_Round2.keras filter=lfs diff=lfs merge=lfs -text
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NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round4/HELMINTHS_BINARY_NASNetMobile_Round4.keras filter=lfs diff=lfs merge=lfs -text
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NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round5/HELMINTHS_BINARY_NASNetMobile_Round5.keras filter=lfs diff=lfs merge=lfs -text
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/HELMINTHS_BINARY_DenseNet169_Round1.keras
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version https://git-lfs.github.com/spec/v1
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size 57791210
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/classification_metrics.txt
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Precision: 1.0000
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Recall: 1.0000
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Sensitivity: 1.0000
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Specificity: 1.0000
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F1-Score: 1.0000
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AUC: 1.0000
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MCC: 1.0000
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Cohen's Kappa: 1.0000
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Balanced Accuracy: 1.0000
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Jaccard Index: 1.0000
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Log Loss: 0.0000
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F0.5-Score: 1.0000
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/confusion_matrix.png
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/roc_curve.png
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/testing_metrics.txt
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accuracy: 1.0000
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auc: 1.0000
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loss: 0.0000
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/training_accuracy.png
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/training_loss.png
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DenseNet169/HELMINTHS_BINARY_DenseNet169_Round1/training_validation_metrics.txt
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| 1 |
+
Training and Validation Metrics Per Epoch
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| 2 |
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==================================================
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| 3 |
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Epoch 1
|
| 4 |
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Training Accuracy: 0.9832
|
| 5 |
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Validation Accuracy: 0.9928
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| 6 |
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Training Loss: 0.0548
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| 7 |
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Validation Loss: 0.0193
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| 8 |
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--------------------------------------------------
|
| 9 |
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Epoch 2
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| 10 |
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Training Accuracy: 0.9968
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| 11 |
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Validation Accuracy: 0.9980
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| 12 |
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Training Loss: 0.0111
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| 13 |
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Validation Loss: 0.0066
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| 14 |
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--------------------------------------------------
|
| 15 |
+
Epoch 3
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| 16 |
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Training Accuracy: 0.9984
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| 17 |
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Validation Accuracy: 0.9997
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| 18 |
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Training Loss: 0.0061
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| 19 |
+
Validation Loss: 0.0034
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| 20 |
+
--------------------------------------------------
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| 21 |
+
Epoch 4
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| 22 |
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Training Accuracy: 0.9990
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| 23 |
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Validation Accuracy: 0.9997
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| 24 |
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Training Loss: 0.0038
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| 25 |
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Validation Loss: 0.0020
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
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| 28 |
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Training Accuracy: 0.9996
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| 29 |
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Validation Accuracy: 0.9997
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| 30 |
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Training Loss: 0.0024
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| 31 |
+
Validation Loss: 0.0013
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
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| 34 |
+
Training Accuracy: 0.9995
|
| 35 |
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Validation Accuracy: 1.0000
|
| 36 |
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Training Loss: 0.0022
|
| 37 |
+
Validation Loss: 0.0010
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
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| 40 |
+
Training Accuracy: 0.9997
|
| 41 |
+
Validation Accuracy: 1.0000
|
| 42 |
+
Training Loss: 0.0015
|
| 43 |
+
Validation Loss: 0.0008
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9997
|
| 47 |
+
Validation Accuracy: 1.0000
|
| 48 |
+
Training Loss: 0.0012
|
| 49 |
+
Validation Loss: 0.0006
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9997
|
| 53 |
+
Validation Accuracy: 1.0000
|
| 54 |
+
Training Loss: 0.0009
|
| 55 |
+
Validation Loss: 0.0004
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9999
|
| 59 |
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Validation Accuracy: 1.0000
|
| 60 |
+
Training Loss: 0.0008
|
| 61 |
+
Validation Loss: 0.0004
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 1.0000
|
| 66 |
+
Training Loss: 0.0005
|
| 67 |
+
Validation Loss: 0.0003
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9998
|
| 71 |
+
Validation Accuracy: 1.0000
|
| 72 |
+
Training Loss: 0.0007
|
| 73 |
+
Validation Loss: 0.0003
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 1.0000
|
| 78 |
+
Training Loss: 0.0004
|
| 79 |
+
Validation Loss: 0.0004
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 1.0000
|
| 83 |
+
Validation Accuracy: 1.0000
|
| 84 |
+
Training Loss: 0.0003
|
| 85 |
+
Validation Loss: 0.0002
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9998
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0006
|
| 91 |
+
Validation Loss: 0.0002
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 1.0000
|
| 96 |
+
Training Loss: 0.0006
|
| 97 |
+
Validation Loss: 0.0002
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 1.0000
|
| 101 |
+
Validation Accuracy: 1.0000
|
| 102 |
+
Training Loss: 0.0003
|
| 103 |
+
Validation Loss: 0.0001
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
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Training Accuracy: 1.0000
|
| 107 |
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Validation Accuracy: 1.0000
|
| 108 |
+
Training Loss: 0.0001
|
| 109 |
+
Validation Loss: 0.0001
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9999
|
| 113 |
+
Validation Accuracy: 1.0000
|
| 114 |
+
Training Loss: 0.0002
|
| 115 |
+
Validation Loss: 0.0004
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9999
|
| 119 |
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Validation Accuracy: 1.0000
|
| 120 |
+
Training Loss: 0.0003
|
| 121 |
+
Validation Loss: 0.0002
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 1.0000
|
| 125 |
+
Validation Accuracy: 1.0000
|
| 126 |
+
Training Loss: 0.0003
|
| 127 |
+
Validation Loss: 0.0001
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9999
|
| 131 |
+
Validation Accuracy: 1.0000
|
| 132 |
+
Training Loss: 0.0003
|
| 133 |
+
Validation Loss: 0.0001
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 1.0000
|
| 138 |
+
Training Loss: 0.0001
|
| 139 |
+
Validation Loss: 0.0001
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 1.0000
|
| 144 |
+
Training Loss: 0.0001
|
| 145 |
+
Validation Loss: 0.0001
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 1.0000
|
| 149 |
+
Validation Accuracy: 1.0000
|
| 150 |
+
Training Loss: 0.0001
|
| 151 |
+
Validation Loss: 0.0001
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
+
Validation Accuracy: 1.0000
|
| 156 |
+
Training Loss: 0.0001
|
| 157 |
+
Validation Loss: 0.0001
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 1.0000
|
| 161 |
+
Validation Accuracy: 1.0000
|
| 162 |
+
Training Loss: 0.0000
|
| 163 |
+
Validation Loss: 0.0001
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 1.0000
|
| 167 |
+
Validation Accuracy: 1.0000
|
| 168 |
+
Training Loss: 0.0000
|
| 169 |
+
Validation Loss: 0.0001
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 1.0000
|
| 174 |
+
Training Loss: 0.0000
|
| 175 |
+
Validation Loss: 0.0000
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 1.0000
|
| 179 |
+
Validation Accuracy: 1.0000
|
| 180 |
+
Training Loss: 0.0000
|
| 181 |
+
Validation Loss: 0.0000
|
| 182 |
+
--------------------------------------------------
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/HELMINTHS_BINARY_DenseNet169_Round2.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:71bc3d52ccfd9c55ef89fe0db700c976055ed2f87e156b0a9abd6a6a82fff289
|
| 3 |
+
size 57791210
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/classification_metrics.txt
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Precision: 1.0000
|
| 2 |
+
Recall: 1.0000
|
| 3 |
+
Sensitivity: 1.0000
|
| 4 |
+
Specificity: 1.0000
|
| 5 |
+
F1-Score: 1.0000
|
| 6 |
+
AUC: 1.0000
|
| 7 |
+
MCC: 1.0000
|
| 8 |
+
Cohen's Kappa: 1.0000
|
| 9 |
+
Balanced Accuracy: 1.0000
|
| 10 |
+
Jaccard Index: 1.0000
|
| 11 |
+
Log Loss: 0.0002
|
| 12 |
+
F0.5-Score: 1.0000
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/confusion_matrix.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/roc_curve.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0002
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/training_accuracy.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/training_loss.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round2/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
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|
|
|
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|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
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|
|
|
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|
|
|
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|
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|
|
|
|
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9756
|
| 5 |
+
Validation Accuracy: 0.9921
|
| 6 |
+
Training Loss: 0.0681
|
| 7 |
+
Validation Loss: 0.0263
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9965
|
| 11 |
+
Validation Accuracy: 0.9967
|
| 12 |
+
Training Loss: 0.0140
|
| 13 |
+
Validation Loss: 0.0102
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9982
|
| 17 |
+
Validation Accuracy: 0.9993
|
| 18 |
+
Training Loss: 0.0080
|
| 19 |
+
Validation Loss: 0.0050
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9989
|
| 23 |
+
Validation Accuracy: 0.9993
|
| 24 |
+
Training Loss: 0.0055
|
| 25 |
+
Validation Loss: 0.0033
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9993
|
| 29 |
+
Validation Accuracy: 0.9997
|
| 30 |
+
Training Loss: 0.0029
|
| 31 |
+
Validation Loss: 0.0020
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9993
|
| 35 |
+
Validation Accuracy: 0.9993
|
| 36 |
+
Training Loss: 0.0025
|
| 37 |
+
Validation Loss: 0.0015
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9998
|
| 41 |
+
Validation Accuracy: 1.0000
|
| 42 |
+
Training Loss: 0.0015
|
| 43 |
+
Validation Loss: 0.0014
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9999
|
| 47 |
+
Validation Accuracy: 1.0000
|
| 48 |
+
Training Loss: 0.0011
|
| 49 |
+
Validation Loss: 0.0009
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9997
|
| 53 |
+
Validation Accuracy: 0.9997
|
| 54 |
+
Training Loss: 0.0011
|
| 55 |
+
Validation Loss: 0.0009
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9997
|
| 59 |
+
Validation Accuracy: 1.0000
|
| 60 |
+
Training Loss: 0.0009
|
| 61 |
+
Validation Loss: 0.0009
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 1.0000
|
| 66 |
+
Training Loss: 0.0006
|
| 67 |
+
Validation Loss: 0.0008
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9999
|
| 71 |
+
Validation Accuracy: 1.0000
|
| 72 |
+
Training Loss: 0.0006
|
| 73 |
+
Validation Loss: 0.0005
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 1.0000
|
| 78 |
+
Training Loss: 0.0004
|
| 79 |
+
Validation Loss: 0.0005
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9998
|
| 83 |
+
Validation Accuracy: 1.0000
|
| 84 |
+
Training Loss: 0.0007
|
| 85 |
+
Validation Loss: 0.0008
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9998
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0007
|
| 91 |
+
Validation Loss: 0.0008
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 1.0000
|
| 96 |
+
Training Loss: 0.0004
|
| 97 |
+
Validation Loss: 0.0006
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 1.0000
|
| 101 |
+
Validation Accuracy: 1.0000
|
| 102 |
+
Training Loss: 0.0003
|
| 103 |
+
Validation Loss: 0.0002
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 1.0000
|
| 107 |
+
Validation Accuracy: 1.0000
|
| 108 |
+
Training Loss: 0.0002
|
| 109 |
+
Validation Loss: 0.0004
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 1.0000
|
| 113 |
+
Validation Accuracy: 1.0000
|
| 114 |
+
Training Loss: 0.0003
|
| 115 |
+
Validation Loss: 0.0006
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 1.0000
|
| 119 |
+
Validation Accuracy: 0.9997
|
| 120 |
+
Training Loss: 0.0002
|
| 121 |
+
Validation Loss: 0.0007
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 1.0000
|
| 125 |
+
Validation Accuracy: 1.0000
|
| 126 |
+
Training Loss: 0.0001
|
| 127 |
+
Validation Loss: 0.0004
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9999
|
| 131 |
+
Validation Accuracy: 1.0000
|
| 132 |
+
Training Loss: 0.0003
|
| 133 |
+
Validation Loss: 0.0002
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 0.9999
|
| 137 |
+
Validation Accuracy: 1.0000
|
| 138 |
+
Training Loss: 0.0003
|
| 139 |
+
Validation Loss: 0.0002
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 1.0000
|
| 144 |
+
Training Loss: 0.0001
|
| 145 |
+
Validation Loss: 0.0001
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 1.0000
|
| 149 |
+
Validation Accuracy: 1.0000
|
| 150 |
+
Training Loss: 0.0001
|
| 151 |
+
Validation Loss: 0.0002
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 0.9999
|
| 155 |
+
Validation Accuracy: 1.0000
|
| 156 |
+
Training Loss: 0.0003
|
| 157 |
+
Validation Loss: 0.0001
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 1.0000
|
| 161 |
+
Validation Accuracy: 1.0000
|
| 162 |
+
Training Loss: 0.0001
|
| 163 |
+
Validation Loss: 0.0004
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 1.0000
|
| 167 |
+
Validation Accuracy: 1.0000
|
| 168 |
+
Training Loss: 0.0001
|
| 169 |
+
Validation Loss: 0.0001
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 1.0000
|
| 174 |
+
Training Loss: 0.0001
|
| 175 |
+
Validation Loss: 0.0002
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 1.0000
|
| 179 |
+
Validation Accuracy: 1.0000
|
| 180 |
+
Training Loss: 0.0001
|
| 181 |
+
Validation Loss: 0.0004
|
| 182 |
+
--------------------------------------------------
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/HELMINTHS_BINARY_DenseNet169_Round3.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2343c4f2fd57bea32688b3505271911c77fed3db306a741d42f02a7ac9e4c991
|
| 3 |
+
size 57791210
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/classification_metrics.txt
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Precision: 1.0000
|
| 2 |
+
Recall: 1.0000
|
| 3 |
+
Sensitivity: 1.0000
|
| 4 |
+
Specificity: 1.0000
|
| 5 |
+
F1-Score: 1.0000
|
| 6 |
+
AUC: 1.0000
|
| 7 |
+
MCC: 1.0000
|
| 8 |
+
Cohen's Kappa: 1.0000
|
| 9 |
+
Balanced Accuracy: 1.0000
|
| 10 |
+
Jaccard Index: 1.0000
|
| 11 |
+
Log Loss: 0.0001
|
| 12 |
+
F0.5-Score: 1.0000
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/confusion_matrix.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/roc_curve.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0001
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/training_accuracy.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/training_loss.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round3/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
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|
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|
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|
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|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9844
|
| 5 |
+
Validation Accuracy: 0.9931
|
| 6 |
+
Training Loss: 0.0551
|
| 7 |
+
Validation Loss: 0.0224
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9966
|
| 11 |
+
Validation Accuracy: 0.9964
|
| 12 |
+
Training Loss: 0.0125
|
| 13 |
+
Validation Loss: 0.0080
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9979
|
| 17 |
+
Validation Accuracy: 0.9993
|
| 18 |
+
Training Loss: 0.0073
|
| 19 |
+
Validation Loss: 0.0038
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9992
|
| 23 |
+
Validation Accuracy: 0.9993
|
| 24 |
+
Training Loss: 0.0042
|
| 25 |
+
Validation Loss: 0.0032
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9994
|
| 29 |
+
Validation Accuracy: 1.0000
|
| 30 |
+
Training Loss: 0.0030
|
| 31 |
+
Validation Loss: 0.0014
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9997
|
| 35 |
+
Validation Accuracy: 1.0000
|
| 36 |
+
Training Loss: 0.0019
|
| 37 |
+
Validation Loss: 0.0010
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9997
|
| 41 |
+
Validation Accuracy: 1.0000
|
| 42 |
+
Training Loss: 0.0014
|
| 43 |
+
Validation Loss: 0.0008
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9996
|
| 47 |
+
Validation Accuracy: 1.0000
|
| 48 |
+
Training Loss: 0.0016
|
| 49 |
+
Validation Loss: 0.0006
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9999
|
| 53 |
+
Validation Accuracy: 1.0000
|
| 54 |
+
Training Loss: 0.0007
|
| 55 |
+
Validation Loss: 0.0005
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9998
|
| 59 |
+
Validation Accuracy: 1.0000
|
| 60 |
+
Training Loss: 0.0009
|
| 61 |
+
Validation Loss: 0.0005
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9998
|
| 65 |
+
Validation Accuracy: 1.0000
|
| 66 |
+
Training Loss: 0.0008
|
| 67 |
+
Validation Loss: 0.0003
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 1.0000
|
| 71 |
+
Validation Accuracy: 1.0000
|
| 72 |
+
Training Loss: 0.0005
|
| 73 |
+
Validation Loss: 0.0003
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9998
|
| 77 |
+
Validation Accuracy: 1.0000
|
| 78 |
+
Training Loss: 0.0007
|
| 79 |
+
Validation Loss: 0.0004
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9996
|
| 83 |
+
Validation Accuracy: 1.0000
|
| 84 |
+
Training Loss: 0.0011
|
| 85 |
+
Validation Loss: 0.0003
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 1.0000
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0003
|
| 91 |
+
Validation Loss: 0.0002
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 1.0000
|
| 95 |
+
Validation Accuracy: 1.0000
|
| 96 |
+
Training Loss: 0.0001
|
| 97 |
+
Validation Loss: 0.0002
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9999
|
| 101 |
+
Validation Accuracy: 1.0000
|
| 102 |
+
Training Loss: 0.0003
|
| 103 |
+
Validation Loss: 0.0002
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 0.9999
|
| 107 |
+
Validation Accuracy: 1.0000
|
| 108 |
+
Training Loss: 0.0003
|
| 109 |
+
Validation Loss: 0.0002
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9999
|
| 113 |
+
Validation Accuracy: 1.0000
|
| 114 |
+
Training Loss: 0.0003
|
| 115 |
+
Validation Loss: 0.0001
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 1.0000
|
| 119 |
+
Validation Accuracy: 1.0000
|
| 120 |
+
Training Loss: 0.0001
|
| 121 |
+
Validation Loss: 0.0002
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 1.0000
|
| 125 |
+
Validation Accuracy: 1.0000
|
| 126 |
+
Training Loss: 0.0002
|
| 127 |
+
Validation Loss: 0.0001
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 1.0000
|
| 131 |
+
Validation Accuracy: 1.0000
|
| 132 |
+
Training Loss: 0.0001
|
| 133 |
+
Validation Loss: 0.0001
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 1.0000
|
| 138 |
+
Training Loss: 0.0001
|
| 139 |
+
Validation Loss: 0.0001
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 1.0000
|
| 144 |
+
Training Loss: 0.0003
|
| 145 |
+
Validation Loss: 0.0003
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 0.9996
|
| 149 |
+
Validation Accuracy: 1.0000
|
| 150 |
+
Training Loss: 0.0008
|
| 151 |
+
Validation Loss: 0.0001
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
+
Validation Accuracy: 1.0000
|
| 156 |
+
Training Loss: 0.0001
|
| 157 |
+
Validation Loss: 0.0001
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 1.0000
|
| 161 |
+
Validation Accuracy: 1.0000
|
| 162 |
+
Training Loss: 0.0001
|
| 163 |
+
Validation Loss: 0.0001
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9999
|
| 167 |
+
Validation Accuracy: 1.0000
|
| 168 |
+
Training Loss: 0.0001
|
| 169 |
+
Validation Loss: 0.0001
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 1.0000
|
| 174 |
+
Training Loss: 0.0001
|
| 175 |
+
Validation Loss: 0.0000
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 1.0000
|
| 179 |
+
Validation Accuracy: 1.0000
|
| 180 |
+
Training Loss: 0.0001
|
| 181 |
+
Validation Loss: 0.0001
|
| 182 |
+
--------------------------------------------------
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/HELMINTHS_BINARY_DenseNet169_Round4.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a3ea919cb5fa8c654d49c6d83bdfdd345084b7d39a7135011c326f5c92c7589d
|
| 3 |
+
size 57791210
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/classification_metrics.txt
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Precision: 0.9952
|
| 2 |
+
Recall: 1.0000
|
| 3 |
+
Sensitivity: 1.0000
|
| 4 |
+
Specificity: 0.9992
|
| 5 |
+
F1-Score: 0.9976
|
| 6 |
+
AUC: 1.0000
|
| 7 |
+
MCC: 0.9972
|
| 8 |
+
Cohen's Kappa: 0.9972
|
| 9 |
+
Balanced Accuracy: 0.9996
|
| 10 |
+
Jaccard Index: 0.9952
|
| 11 |
+
Log Loss: 0.0008
|
| 12 |
+
F0.5-Score: 0.9961
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/confusion_matrix.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/roc_curve.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 0.9993
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0008
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/training_accuracy.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/training_loss.png
ADDED
|
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round4/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9655
|
| 5 |
+
Validation Accuracy: 0.9938
|
| 6 |
+
Training Loss: 0.0983
|
| 7 |
+
Validation Loss: 0.0260
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9962
|
| 11 |
+
Validation Accuracy: 0.9970
|
| 12 |
+
Training Loss: 0.0163
|
| 13 |
+
Validation Loss: 0.0109
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9979
|
| 17 |
+
Validation Accuracy: 0.9997
|
| 18 |
+
Training Loss: 0.0080
|
| 19 |
+
Validation Loss: 0.0058
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9986
|
| 23 |
+
Validation Accuracy: 0.9997
|
| 24 |
+
Training Loss: 0.0056
|
| 25 |
+
Validation Loss: 0.0034
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9993
|
| 29 |
+
Validation Accuracy: 1.0000
|
| 30 |
+
Training Loss: 0.0033
|
| 31 |
+
Validation Loss: 0.0023
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9993
|
| 35 |
+
Validation Accuracy: 1.0000
|
| 36 |
+
Training Loss: 0.0028
|
| 37 |
+
Validation Loss: 0.0019
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9996
|
| 41 |
+
Validation Accuracy: 1.0000
|
| 42 |
+
Training Loss: 0.0021
|
| 43 |
+
Validation Loss: 0.0011
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9995
|
| 47 |
+
Validation Accuracy: 1.0000
|
| 48 |
+
Training Loss: 0.0017
|
| 49 |
+
Validation Loss: 0.0014
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9996
|
| 53 |
+
Validation Accuracy: 1.0000
|
| 54 |
+
Training Loss: 0.0013
|
| 55 |
+
Validation Loss: 0.0010
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9998
|
| 59 |
+
Validation Accuracy: 1.0000
|
| 60 |
+
Training Loss: 0.0008
|
| 61 |
+
Validation Loss: 0.0009
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9998
|
| 65 |
+
Validation Accuracy: 1.0000
|
| 66 |
+
Training Loss: 0.0009
|
| 67 |
+
Validation Loss: 0.0006
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9998
|
| 71 |
+
Validation Accuracy: 1.0000
|
| 72 |
+
Training Loss: 0.0007
|
| 73 |
+
Validation Loss: 0.0006
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9993
|
| 78 |
+
Training Loss: 0.0007
|
| 79 |
+
Validation Loss: 0.0016
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9999
|
| 83 |
+
Validation Accuracy: 1.0000
|
| 84 |
+
Training Loss: 0.0005
|
| 85 |
+
Validation Loss: 0.0007
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 1.0000
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0003
|
| 91 |
+
Validation Loss: 0.0009
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9997
|
| 95 |
+
Validation Accuracy: 1.0000
|
| 96 |
+
Training Loss: 0.0006
|
| 97 |
+
Validation Loss: 0.0009
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 1.0000
|
| 101 |
+
Validation Accuracy: 1.0000
|
| 102 |
+
Training Loss: 0.0003
|
| 103 |
+
Validation Loss: 0.0004
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 0.9999
|
| 107 |
+
Validation Accuracy: 0.9997
|
| 108 |
+
Training Loss: 0.0003
|
| 109 |
+
Validation Loss: 0.0010
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 1.0000
|
| 113 |
+
Validation Accuracy: 1.0000
|
| 114 |
+
Training Loss: 0.0002
|
| 115 |
+
Validation Loss: 0.0002
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 1.0000
|
| 119 |
+
Validation Accuracy: 1.0000
|
| 120 |
+
Training Loss: 0.0001
|
| 121 |
+
Validation Loss: 0.0002
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 1.0000
|
| 125 |
+
Validation Accuracy: 1.0000
|
| 126 |
+
Training Loss: 0.0003
|
| 127 |
+
Validation Loss: 0.0005
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 1.0000
|
| 131 |
+
Validation Accuracy: 1.0000
|
| 132 |
+
Training Loss: 0.0001
|
| 133 |
+
Validation Loss: 0.0001
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 0.9999
|
| 137 |
+
Validation Accuracy: 0.9990
|
| 138 |
+
Training Loss: 0.0002
|
| 139 |
+
Validation Loss: 0.0015
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 1.0000
|
| 144 |
+
Training Loss: 0.0001
|
| 145 |
+
Validation Loss: 0.0002
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 1.0000
|
| 149 |
+
Validation Accuracy: 1.0000
|
| 150 |
+
Training Loss: 0.0001
|
| 151 |
+
Validation Loss: 0.0001
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
+
Validation Accuracy: 1.0000
|
| 156 |
+
Training Loss: 0.0001
|
| 157 |
+
Validation Loss: 0.0003
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 1.0000
|
| 161 |
+
Validation Accuracy: 1.0000
|
| 162 |
+
Training Loss: 0.0002
|
| 163 |
+
Validation Loss: 0.0001
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9999
|
| 167 |
+
Validation Accuracy: 1.0000
|
| 168 |
+
Training Loss: 0.0002
|
| 169 |
+
Validation Loss: 0.0002
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 1.0000
|
| 174 |
+
Training Loss: 0.0001
|
| 175 |
+
Validation Loss: 0.0009
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 0.9999
|
| 179 |
+
Validation Accuracy: 0.9993
|
| 180 |
+
Training Loss: 0.0002
|
| 181 |
+
Validation Loss: 0.0012
|
| 182 |
+
--------------------------------------------------
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/HELMINTHS_BINARY_NASNetMobile_Round1.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:75f0fcbf5991b06a4987137afd8d1da7ad8d473eefc5a4951fff7667b89fb4e9
|
| 3 |
+
size 23074075
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/classification_metrics.txt
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Precision: 1.0000
|
| 2 |
+
Recall: 0.9806
|
| 3 |
+
Sensitivity: 0.9806
|
| 4 |
+
Specificity: 1.0000
|
| 5 |
+
F1-Score: 0.9902
|
| 6 |
+
AUC: 1.0000
|
| 7 |
+
MCC: 0.9887
|
| 8 |
+
Cohen's Kappa: 0.9887
|
| 9 |
+
Balanced Accuracy: 0.9903
|
| 10 |
+
Jaccard Index: 0.9806
|
| 11 |
+
Log Loss: 0.0069
|
| 12 |
+
F0.5-Score: 0.9961
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/confusion_matrix.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/roc_curve.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 0.9974
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0069
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/training_accuracy.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/training_loss.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round1/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
|
|
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|
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|
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|
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|
|
|
|
|
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|
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|
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|
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|
|
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|
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|
|
|
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|
|
|
|
|
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|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9788
|
| 5 |
+
Validation Accuracy: 0.9908
|
| 6 |
+
Training Loss: 0.0738
|
| 7 |
+
Validation Loss: 0.0386
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9931
|
| 11 |
+
Validation Accuracy: 0.9921
|
| 12 |
+
Training Loss: 0.0235
|
| 13 |
+
Validation Loss: 0.0263
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9950
|
| 17 |
+
Validation Accuracy: 0.9938
|
| 18 |
+
Training Loss: 0.0169
|
| 19 |
+
Validation Loss: 0.0200
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9967
|
| 23 |
+
Validation Accuracy: 0.9944
|
| 24 |
+
Training Loss: 0.0120
|
| 25 |
+
Validation Loss: 0.0167
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9978
|
| 29 |
+
Validation Accuracy: 0.9951
|
| 30 |
+
Training Loss: 0.0091
|
| 31 |
+
Validation Loss: 0.0140
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9975
|
| 35 |
+
Validation Accuracy: 0.9954
|
| 36 |
+
Training Loss: 0.0085
|
| 37 |
+
Validation Loss: 0.0126
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9977
|
| 41 |
+
Validation Accuracy: 0.9954
|
| 42 |
+
Training Loss: 0.0081
|
| 43 |
+
Validation Loss: 0.0114
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9986
|
| 47 |
+
Validation Accuracy: 0.9964
|
| 48 |
+
Training Loss: 0.0060
|
| 49 |
+
Validation Loss: 0.0109
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9985
|
| 53 |
+
Validation Accuracy: 0.9964
|
| 54 |
+
Training Loss: 0.0055
|
| 55 |
+
Validation Loss: 0.0101
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9983
|
| 59 |
+
Validation Accuracy: 0.9964
|
| 60 |
+
Training Loss: 0.0055
|
| 61 |
+
Validation Loss: 0.0093
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9984
|
| 65 |
+
Validation Accuracy: 0.9964
|
| 66 |
+
Training Loss: 0.0053
|
| 67 |
+
Validation Loss: 0.0086
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9987
|
| 71 |
+
Validation Accuracy: 0.9970
|
| 72 |
+
Training Loss: 0.0051
|
| 73 |
+
Validation Loss: 0.0081
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9984
|
| 77 |
+
Validation Accuracy: 0.9967
|
| 78 |
+
Training Loss: 0.0044
|
| 79 |
+
Validation Loss: 0.0078
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9988
|
| 83 |
+
Validation Accuracy: 0.9964
|
| 84 |
+
Training Loss: 0.0037
|
| 85 |
+
Validation Loss: 0.0074
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9993
|
| 89 |
+
Validation Accuracy: 0.9967
|
| 90 |
+
Training Loss: 0.0035
|
| 91 |
+
Validation Loss: 0.0070
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9987
|
| 95 |
+
Validation Accuracy: 0.9967
|
| 96 |
+
Training Loss: 0.0049
|
| 97 |
+
Validation Loss: 0.0077
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9992
|
| 101 |
+
Validation Accuracy: 0.9967
|
| 102 |
+
Training Loss: 0.0031
|
| 103 |
+
Validation Loss: 0.0069
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 0.9989
|
| 107 |
+
Validation Accuracy: 0.9970
|
| 108 |
+
Training Loss: 0.0037
|
| 109 |
+
Validation Loss: 0.0077
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9995
|
| 113 |
+
Validation Accuracy: 0.9974
|
| 114 |
+
Training Loss: 0.0020
|
| 115 |
+
Validation Loss: 0.0068
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9993
|
| 119 |
+
Validation Accuracy: 0.9977
|
| 120 |
+
Training Loss: 0.0029
|
| 121 |
+
Validation Loss: 0.0056
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 0.9993
|
| 125 |
+
Validation Accuracy: 0.9974
|
| 126 |
+
Training Loss: 0.0025
|
| 127 |
+
Validation Loss: 0.0056
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9993
|
| 131 |
+
Validation Accuracy: 0.9980
|
| 132 |
+
Training Loss: 0.0025
|
| 133 |
+
Validation Loss: 0.0050
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 0.9990
|
| 137 |
+
Validation Accuracy: 0.9980
|
| 138 |
+
Training Loss: 0.0033
|
| 139 |
+
Validation Loss: 0.0056
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 0.9995
|
| 143 |
+
Validation Accuracy: 0.9984
|
| 144 |
+
Training Loss: 0.0020
|
| 145 |
+
Validation Loss: 0.0050
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 0.9996
|
| 149 |
+
Validation Accuracy: 0.9980
|
| 150 |
+
Training Loss: 0.0020
|
| 151 |
+
Validation Loss: 0.0045
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 0.9995
|
| 155 |
+
Validation Accuracy: 0.9984
|
| 156 |
+
Training Loss: 0.0017
|
| 157 |
+
Validation Loss: 0.0047
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 0.9994
|
| 161 |
+
Validation Accuracy: 0.9980
|
| 162 |
+
Training Loss: 0.0020
|
| 163 |
+
Validation Loss: 0.0051
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9995
|
| 167 |
+
Validation Accuracy: 0.9977
|
| 168 |
+
Training Loss: 0.0022
|
| 169 |
+
Validation Loss: 0.0062
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 0.9994
|
| 173 |
+
Validation Accuracy: 0.9980
|
| 174 |
+
Training Loss: 0.0019
|
| 175 |
+
Validation Loss: 0.0052
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 0.9991
|
| 179 |
+
Validation Accuracy: 0.9984
|
| 180 |
+
Training Loss: 0.0026
|
| 181 |
+
Validation Loss: 0.0047
|
| 182 |
+
--------------------------------------------------
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/HELMINTHS_BINARY_NASNetMobile_Round2.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4df506bb58594c0d5724eb0c490954427ce177ecefd697c01ebb046176138d98
|
| 3 |
+
size 23074075
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/classification_metrics.txt
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Precision: 0.9951
|
| 2 |
+
Recall: 0.9903
|
| 3 |
+
Sensitivity: 0.9903
|
| 4 |
+
Specificity: 0.9992
|
| 5 |
+
F1-Score: 0.9927
|
| 6 |
+
AUC: 0.9999
|
| 7 |
+
MCC: 0.9916
|
| 8 |
+
Cohen's Kappa: 0.9916
|
| 9 |
+
Balanced Accuracy: 0.9948
|
| 10 |
+
Jaccard Index: 0.9855
|
| 11 |
+
Log Loss: 0.0063
|
| 12 |
+
F0.5-Score: 0.9942
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/confusion_matrix.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/roc_curve.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 0.9980
|
| 2 |
+
auc: 0.9999
|
| 3 |
+
loss: 0.0063
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/training_accuracy.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/training_loss.png
ADDED
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round2/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
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|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9737
|
| 5 |
+
Validation Accuracy: 0.9898
|
| 6 |
+
Training Loss: 0.0872
|
| 7 |
+
Validation Loss: 0.0451
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9928
|
| 11 |
+
Validation Accuracy: 0.9908
|
| 12 |
+
Training Loss: 0.0273
|
| 13 |
+
Validation Loss: 0.0304
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9950
|
| 17 |
+
Validation Accuracy: 0.9928
|
| 18 |
+
Training Loss: 0.0179
|
| 19 |
+
Validation Loss: 0.0228
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9959
|
| 23 |
+
Validation Accuracy: 0.9938
|
| 24 |
+
Training Loss: 0.0140
|
| 25 |
+
Validation Loss: 0.0187
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9971
|
| 29 |
+
Validation Accuracy: 0.9941
|
| 30 |
+
Training Loss: 0.0108
|
| 31 |
+
Validation Loss: 0.0163
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9976
|
| 35 |
+
Validation Accuracy: 0.9951
|
| 36 |
+
Training Loss: 0.0096
|
| 37 |
+
Validation Loss: 0.0148
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9978
|
| 41 |
+
Validation Accuracy: 0.9954
|
| 42 |
+
Training Loss: 0.0069
|
| 43 |
+
Validation Loss: 0.0128
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9981
|
| 47 |
+
Validation Accuracy: 0.9951
|
| 48 |
+
Training Loss: 0.0076
|
| 49 |
+
Validation Loss: 0.0119
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9985
|
| 53 |
+
Validation Accuracy: 0.9954
|
| 54 |
+
Training Loss: 0.0063
|
| 55 |
+
Validation Loss: 0.0111
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9978
|
| 59 |
+
Validation Accuracy: 0.9954
|
| 60 |
+
Training Loss: 0.0068
|
| 61 |
+
Validation Loss: 0.0102
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9983
|
| 65 |
+
Validation Accuracy: 0.9954
|
| 66 |
+
Training Loss: 0.0056
|
| 67 |
+
Validation Loss: 0.0098
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9992
|
| 71 |
+
Validation Accuracy: 0.9961
|
| 72 |
+
Training Loss: 0.0035
|
| 73 |
+
Validation Loss: 0.0098
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9986
|
| 77 |
+
Validation Accuracy: 0.9957
|
| 78 |
+
Training Loss: 0.0043
|
| 79 |
+
Validation Loss: 0.0094
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9993
|
| 83 |
+
Validation Accuracy: 0.9957
|
| 84 |
+
Training Loss: 0.0038
|
| 85 |
+
Validation Loss: 0.0107
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9993
|
| 89 |
+
Validation Accuracy: 0.9964
|
| 90 |
+
Training Loss: 0.0033
|
| 91 |
+
Validation Loss: 0.0086
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9982
|
| 95 |
+
Validation Accuracy: 0.9964
|
| 96 |
+
Training Loss: 0.0043
|
| 97 |
+
Validation Loss: 0.0083
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9987
|
| 101 |
+
Validation Accuracy: 0.9964
|
| 102 |
+
Training Loss: 0.0039
|
| 103 |
+
Validation Loss: 0.0080
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 0.9996
|
| 107 |
+
Validation Accuracy: 0.9967
|
| 108 |
+
Training Loss: 0.0022
|
| 109 |
+
Validation Loss: 0.0081
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9993
|
| 113 |
+
Validation Accuracy: 0.9961
|
| 114 |
+
Training Loss: 0.0030
|
| 115 |
+
Validation Loss: 0.0077
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9992
|
| 119 |
+
Validation Accuracy: 0.9961
|
| 120 |
+
Training Loss: 0.0030
|
| 121 |
+
Validation Loss: 0.0081
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 0.9992
|
| 125 |
+
Validation Accuracy: 0.9967
|
| 126 |
+
Training Loss: 0.0020
|
| 127 |
+
Validation Loss: 0.0062
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9993
|
| 131 |
+
Validation Accuracy: 0.9964
|
| 132 |
+
Training Loss: 0.0027
|
| 133 |
+
Validation Loss: 0.0067
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 0.9993
|
| 137 |
+
Validation Accuracy: 0.9977
|
| 138 |
+
Training Loss: 0.0029
|
| 139 |
+
Validation Loss: 0.0060
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 0.9989
|
| 143 |
+
Validation Accuracy: 0.9984
|
| 144 |
+
Training Loss: 0.0035
|
| 145 |
+
Validation Loss: 0.0047
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 0.9987
|
| 149 |
+
Validation Accuracy: 0.9974
|
| 150 |
+
Training Loss: 0.0037
|
| 151 |
+
Validation Loss: 0.0061
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 0.9992
|
| 155 |
+
Validation Accuracy: 0.9980
|
| 156 |
+
Training Loss: 0.0023
|
| 157 |
+
Validation Loss: 0.0053
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 0.9995
|
| 161 |
+
Validation Accuracy: 0.9980
|
| 162 |
+
Training Loss: 0.0016
|
| 163 |
+
Validation Loss: 0.0057
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9994
|
| 167 |
+
Validation Accuracy: 0.9977
|
| 168 |
+
Training Loss: 0.0020
|
| 169 |
+
Validation Loss: 0.0045
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 0.9994
|
| 173 |
+
Validation Accuracy: 0.9977
|
| 174 |
+
Training Loss: 0.0023
|
| 175 |
+
Validation Loss: 0.0052
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 0.9997
|
| 179 |
+
Validation Accuracy: 0.9977
|
| 180 |
+
Training Loss: 0.0014
|
| 181 |
+
Validation Loss: 0.0043
|
| 182 |
+
--------------------------------------------------
|
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round3/HELMINTHS_BINARY_NASNetMobile_Round3.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b4e7c6d52bb1a923f67b0d97dd68f8798b95f87a3a8f5f10b260ca51582a8045
|
| 3 |
+
size 23074075
|