Upload folder using huggingface_hub
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- .gitattributes +5 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/HELMINTHS_BINARY_EfficientNetB0_Round1.keras +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/classification_metrics.txt +12 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/confusion_matrix.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/roc_curve.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/testing_metrics.txt +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/training_accuracy.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/training_loss.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/training_validation_metrics.txt +182 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/HELMINTHS_BINARY_EfficientNetB0_Round2.keras +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/classification_metrics.txt +12 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/confusion_matrix.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/roc_curve.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/testing_metrics.txt +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/training_accuracy.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/training_loss.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/training_validation_metrics.txt +182 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/HELMINTHS_BINARY_EfficientNetB0_Round3.keras +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/classification_metrics.txt +12 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/confusion_matrix.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/roc_curve.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/testing_metrics.txt +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/training_accuracy.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/training_loss.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/training_validation_metrics.txt +182 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/HELMINTHS_BINARY_EfficientNetB0_Round4.keras +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/classification_metrics.txt +12 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/confusion_matrix.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/roc_curve.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/testing_metrics.txt +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/training_accuracy.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/training_loss.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/training_validation_metrics.txt +182 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/HELMINTHS_BINARY_EfficientNetB0_Round5.keras +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/classification_metrics.txt +12 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/confusion_matrix.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/roc_curve.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/testing_metrics.txt +3 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/training_accuracy.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/training_loss.png +0 -0
- EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/training_validation_metrics.txt +182 -0
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/HELMINTHS_BINARY_ResNet50_Round1.keras +1 -1
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/classification_metrics.txt +9 -9
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/confusion_matrix.png +0 -0
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/testing_metrics.txt +2 -2
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/training_accuracy.png +0 -0
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/training_loss.png +0 -0
- ResNet50/HELMINTHS_BINARY_ResNet50_Round1/training_validation_metrics.txt +94 -94
- ResNet50/HELMINTHS_BINARY_ResNet50_Round2/HELMINTHS_BINARY_ResNet50_Round2.keras +1 -1
- ResNet50/HELMINTHS_BINARY_ResNet50_Round2/classification_metrics.txt +9 -9
.gitattributes
CHANGED
|
@@ -58,3 +58,8 @@ NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round3/HELMINTHS_BINARY_NASNetMobile_
|
|
| 58 |
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round4/HELMINTHS_BINARY_NASNetMobile_Round4.keras filter=lfs diff=lfs merge=lfs -text
|
| 59 |
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round5/HELMINTHS_BINARY_NASNetMobile_Round5.keras filter=lfs diff=lfs merge=lfs -text
|
| 60 |
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round5/HELMINTHS_BINARY_DenseNet169_Round5.keras filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 58 |
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round4/HELMINTHS_BINARY_NASNetMobile_Round4.keras filter=lfs diff=lfs merge=lfs -text
|
| 59 |
NASNetMobile/HELMINTHS_BINARY_NASNetMobile_Round5/HELMINTHS_BINARY_NASNetMobile_Round5.keras filter=lfs diff=lfs merge=lfs -text
|
| 60 |
DenseNet169/HELMINTHS_BINARY_DenseNet169_Round5/HELMINTHS_BINARY_DenseNet169_Round5.keras filter=lfs diff=lfs merge=lfs -text
|
| 61 |
+
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/HELMINTHS_BINARY_EfficientNetB0_Round1.keras filter=lfs diff=lfs merge=lfs -text
|
| 62 |
+
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/HELMINTHS_BINARY_EfficientNetB0_Round2.keras filter=lfs diff=lfs merge=lfs -text
|
| 63 |
+
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/HELMINTHS_BINARY_EfficientNetB0_Round3.keras filter=lfs diff=lfs merge=lfs -text
|
| 64 |
+
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/HELMINTHS_BINARY_EfficientNetB0_Round4.keras filter=lfs diff=lfs merge=lfs -text
|
| 65 |
+
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/HELMINTHS_BINARY_EfficientNetB0_Round5.keras filter=lfs diff=lfs merge=lfs -text
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/HELMINTHS_BINARY_EfficientNetB0_Round1.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b510692462b7d31fabd99083bf444eaa2b0c908b2964f4614db68051ed2fee6d
|
| 3 |
+
size 20986130
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/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: 0.0000
|
| 12 |
+
F0.5-Score: 1.0000
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/confusion_matrix.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/roc_curve.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0000
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/training_accuracy.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/training_loss.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round1/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9870
|
| 5 |
+
Validation Accuracy: 0.9996
|
| 6 |
+
Training Loss: 0.0417
|
| 7 |
+
Validation Loss: 0.0045
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9991
|
| 11 |
+
Validation Accuracy: 0.9996
|
| 12 |
+
Training Loss: 0.0058
|
| 13 |
+
Validation Loss: 0.0021
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9996
|
| 17 |
+
Validation Accuracy: 0.9994
|
| 18 |
+
Training Loss: 0.0027
|
| 19 |
+
Validation Loss: 0.0025
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9999
|
| 23 |
+
Validation Accuracy: 0.9996
|
| 24 |
+
Training Loss: 0.0016
|
| 25 |
+
Validation Loss: 0.0018
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9997
|
| 29 |
+
Validation Accuracy: 1.0000
|
| 30 |
+
Training Loss: 0.0015
|
| 31 |
+
Validation Loss: 0.0005
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9998
|
| 35 |
+
Validation Accuracy: 0.9997
|
| 36 |
+
Training Loss: 0.0010
|
| 37 |
+
Validation Loss: 0.0009
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9997
|
| 41 |
+
Validation Accuracy: 0.9996
|
| 42 |
+
Training Loss: 0.0009
|
| 43 |
+
Validation Loss: 0.0016
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9999
|
| 47 |
+
Validation Accuracy: 0.9996
|
| 48 |
+
Training Loss: 0.0007
|
| 49 |
+
Validation Loss: 0.0007
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9999
|
| 53 |
+
Validation Accuracy: 0.9996
|
| 54 |
+
Training Loss: 0.0006
|
| 55 |
+
Validation Loss: 0.0009
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9999
|
| 59 |
+
Validation Accuracy: 0.9996
|
| 60 |
+
Training Loss: 0.0006
|
| 61 |
+
Validation Loss: 0.0007
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 0.9994
|
| 66 |
+
Training Loss: 0.0004
|
| 67 |
+
Validation Loss: 0.0018
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9998
|
| 71 |
+
Validation Accuracy: 0.9996
|
| 72 |
+
Training Loss: 0.0006
|
| 73 |
+
Validation Loss: 0.0010
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9997
|
| 78 |
+
Training Loss: 0.0005
|
| 79 |
+
Validation Loss: 0.0006
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9999
|
| 83 |
+
Validation Accuracy: 0.9999
|
| 84 |
+
Training Loss: 0.0003
|
| 85 |
+
Validation Loss: 0.0002
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9999
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0004
|
| 91 |
+
Validation Loss: 0.0002
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 0.9995
|
| 96 |
+
Training Loss: 0.0005
|
| 97 |
+
Validation Loss: 0.0013
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9999
|
| 101 |
+
Validation Accuracy: 1.0000
|
| 102 |
+
Training Loss: 0.0004
|
| 103 |
+
Validation Loss: 0.0003
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 1.0000
|
| 107 |
+
Validation Accuracy: 1.0000
|
| 108 |
+
Training Loss: 0.0002
|
| 109 |
+
Validation Loss: 0.0002
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9998
|
| 113 |
+
Validation Accuracy: 0.9996
|
| 114 |
+
Training Loss: 0.0005
|
| 115 |
+
Validation Loss: 0.0009
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9999
|
| 119 |
+
Validation Accuracy: 0.9996
|
| 120 |
+
Training Loss: 0.0004
|
| 121 |
+
Validation Loss: 0.0008
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 1.0000
|
| 125 |
+
Validation Accuracy: 0.9999
|
| 126 |
+
Training Loss: 0.0001
|
| 127 |
+
Validation Loss: 0.0003
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 1.0000
|
| 131 |
+
Validation Accuracy: 0.9997
|
| 132 |
+
Training Loss: 0.0001
|
| 133 |
+
Validation Loss: 0.0005
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 0.9997
|
| 138 |
+
Training Loss: 0.0001
|
| 139 |
+
Validation Loss: 0.0006
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 0.9996
|
| 144 |
+
Training Loss: 0.0001
|
| 145 |
+
Validation Loss: 0.0010
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 0.9999
|
| 149 |
+
Validation Accuracy: 0.9997
|
| 150 |
+
Training Loss: 0.0002
|
| 151 |
+
Validation Loss: 0.0004
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
+
Validation Accuracy: 0.9995
|
| 156 |
+
Training Loss: 0.0001
|
| 157 |
+
Validation Loss: 0.0016
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 0.9998
|
| 161 |
+
Validation Accuracy: 0.9996
|
| 162 |
+
Training Loss: 0.0003
|
| 163 |
+
Validation Loss: 0.0009
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9999
|
| 167 |
+
Validation Accuracy: 0.9999
|
| 168 |
+
Training Loss: 0.0003
|
| 169 |
+
Validation Loss: 0.0003
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 0.9999
|
| 173 |
+
Validation Accuracy: 0.9997
|
| 174 |
+
Training Loss: 0.0003
|
| 175 |
+
Validation Loss: 0.0006
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 0.9999
|
| 179 |
+
Validation Accuracy: 0.9999
|
| 180 |
+
Training Loss: 0.0002
|
| 181 |
+
Validation Loss: 0.0006
|
| 182 |
+
--------------------------------------------------
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/HELMINTHS_BINARY_EfficientNetB0_Round2.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9fb7dbd694fd5769791c4916bbb5589e082743e8cbe4836c8cf5b97909b2df74
|
| 3 |
+
size 20986130
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/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: 0.0000
|
| 12 |
+
F0.5-Score: 1.0000
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/confusion_matrix.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/roc_curve.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0000
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/training_accuracy.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/training_loss.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round2/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9859
|
| 5 |
+
Validation Accuracy: 0.9991
|
| 6 |
+
Training Loss: 0.0462
|
| 7 |
+
Validation Loss: 0.0062
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9987
|
| 11 |
+
Validation Accuracy: 0.9999
|
| 12 |
+
Training Loss: 0.0062
|
| 13 |
+
Validation Loss: 0.0020
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9994
|
| 17 |
+
Validation Accuracy: 0.9999
|
| 18 |
+
Training Loss: 0.0033
|
| 19 |
+
Validation Loss: 0.0013
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9996
|
| 23 |
+
Validation Accuracy: 1.0000
|
| 24 |
+
Training Loss: 0.0023
|
| 25 |
+
Validation Loss: 0.0007
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9997
|
| 29 |
+
Validation Accuracy: 0.9996
|
| 30 |
+
Training Loss: 0.0014
|
| 31 |
+
Validation Loss: 0.0013
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9997
|
| 35 |
+
Validation Accuracy: 0.9997
|
| 36 |
+
Training Loss: 0.0011
|
| 37 |
+
Validation Loss: 0.0008
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9996
|
| 41 |
+
Validation Accuracy: 0.9997
|
| 42 |
+
Training Loss: 0.0013
|
| 43 |
+
Validation Loss: 0.0009
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9999
|
| 47 |
+
Validation Accuracy: 0.9997
|
| 48 |
+
Training Loss: 0.0007
|
| 49 |
+
Validation Loss: 0.0006
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 1.0000
|
| 53 |
+
Validation Accuracy: 0.9999
|
| 54 |
+
Training Loss: 0.0004
|
| 55 |
+
Validation Loss: 0.0004
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9999
|
| 59 |
+
Validation Accuracy: 0.9996
|
| 60 |
+
Training Loss: 0.0004
|
| 61 |
+
Validation Loss: 0.0008
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 0.9997
|
| 66 |
+
Training Loss: 0.0005
|
| 67 |
+
Validation Loss: 0.0005
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9999
|
| 71 |
+
Validation Accuracy: 0.9996
|
| 72 |
+
Training Loss: 0.0004
|
| 73 |
+
Validation Loss: 0.0013
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9997
|
| 78 |
+
Training Loss: 0.0005
|
| 79 |
+
Validation Loss: 0.0004
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 1.0000
|
| 83 |
+
Validation Accuracy: 0.9997
|
| 84 |
+
Training Loss: 0.0002
|
| 85 |
+
Validation Loss: 0.0009
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 1.0000
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0001
|
| 91 |
+
Validation Loss: 0.0002
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 0.9991
|
| 96 |
+
Training Loss: 0.0002
|
| 97 |
+
Validation Loss: 0.0024
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9998
|
| 101 |
+
Validation Accuracy: 0.9997
|
| 102 |
+
Training Loss: 0.0007
|
| 103 |
+
Validation Loss: 0.0007
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 0.9999
|
| 107 |
+
Validation Accuracy: 0.9997
|
| 108 |
+
Training Loss: 0.0002
|
| 109 |
+
Validation Loss: 0.0004
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 1.0000
|
| 113 |
+
Validation Accuracy: 0.9997
|
| 114 |
+
Training Loss: 0.0002
|
| 115 |
+
Validation Loss: 0.0012
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 1.0000
|
| 119 |
+
Validation Accuracy: 0.9997
|
| 120 |
+
Training Loss: 0.0001
|
| 121 |
+
Validation Loss: 0.0009
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 0.9999
|
| 125 |
+
Validation Accuracy: 0.9997
|
| 126 |
+
Training Loss: 0.0002
|
| 127 |
+
Validation Loss: 0.0004
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9999
|
| 131 |
+
Validation Accuracy: 1.0000
|
| 132 |
+
Training Loss: 0.0005
|
| 133 |
+
Validation Loss: 0.0001
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 0.9997
|
| 138 |
+
Training Loss: 0.0001
|
| 139 |
+
Validation Loss: 0.0004
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 0.9999
|
| 143 |
+
Validation Accuracy: 0.9997
|
| 144 |
+
Training Loss: 0.0004
|
| 145 |
+
Validation Loss: 0.0004
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 1.0000
|
| 149 |
+
Validation Accuracy: 0.9997
|
| 150 |
+
Training Loss: 0.0003
|
| 151 |
+
Validation Loss: 0.0008
|
| 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: 0.9999
|
| 161 |
+
Validation Accuracy: 0.9999
|
| 162 |
+
Training Loss: 0.0003
|
| 163 |
+
Validation Loss: 0.0002
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9998
|
| 167 |
+
Validation Accuracy: 0.9999
|
| 168 |
+
Training Loss: 0.0004
|
| 169 |
+
Validation Loss: 0.0003
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 0.9997
|
| 174 |
+
Training Loss: 0.0001
|
| 175 |
+
Validation Loss: 0.0003
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 1.0000
|
| 179 |
+
Validation Accuracy: 0.9997
|
| 180 |
+
Training Loss: 0.0001
|
| 181 |
+
Validation Loss: 0.0003
|
| 182 |
+
--------------------------------------------------
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/HELMINTHS_BINARY_EfficientNetB0_Round3.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3593f58e8809bba1e5e75fbbf4bdae450d61e81f2452c7943b6829db1ce6145b
|
| 3 |
+
size 20986130
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_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
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/confusion_matrix.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/roc_curve.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0001
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/training_accuracy.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/training_loss.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round3/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9855
|
| 5 |
+
Validation Accuracy: 0.9994
|
| 6 |
+
Training Loss: 0.0463
|
| 7 |
+
Validation Loss: 0.0059
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9987
|
| 11 |
+
Validation Accuracy: 0.9997
|
| 12 |
+
Training Loss: 0.0062
|
| 13 |
+
Validation Loss: 0.0026
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9992
|
| 17 |
+
Validation Accuracy: 0.9996
|
| 18 |
+
Training Loss: 0.0032
|
| 19 |
+
Validation Loss: 0.0020
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9997
|
| 23 |
+
Validation Accuracy: 0.9996
|
| 24 |
+
Training Loss: 0.0020
|
| 25 |
+
Validation Loss: 0.0015
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9997
|
| 29 |
+
Validation Accuracy: 0.9996
|
| 30 |
+
Training Loss: 0.0014
|
| 31 |
+
Validation Loss: 0.0012
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9998
|
| 35 |
+
Validation Accuracy: 0.9996
|
| 36 |
+
Training Loss: 0.0010
|
| 37 |
+
Validation Loss: 0.0011
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9997
|
| 41 |
+
Validation Accuracy: 0.9996
|
| 42 |
+
Training Loss: 0.0010
|
| 43 |
+
Validation Loss: 0.0015
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9999
|
| 47 |
+
Validation Accuracy: 1.0000
|
| 48 |
+
Training Loss: 0.0006
|
| 49 |
+
Validation Loss: 0.0005
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9999
|
| 53 |
+
Validation Accuracy: 0.9999
|
| 54 |
+
Training Loss: 0.0005
|
| 55 |
+
Validation Loss: 0.0005
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9999
|
| 59 |
+
Validation Accuracy: 0.9996
|
| 60 |
+
Training Loss: 0.0005
|
| 61 |
+
Validation Loss: 0.0010
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 0.9990
|
| 66 |
+
Training Loss: 0.0005
|
| 67 |
+
Validation Loss: 0.0037
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9999
|
| 71 |
+
Validation Accuracy: 0.9999
|
| 72 |
+
Training Loss: 0.0005
|
| 73 |
+
Validation Loss: 0.0004
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9997
|
| 78 |
+
Training Loss: 0.0005
|
| 79 |
+
Validation Loss: 0.0007
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9999
|
| 83 |
+
Validation Accuracy: 0.9999
|
| 84 |
+
Training Loss: 0.0004
|
| 85 |
+
Validation Loss: 0.0007
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9999
|
| 89 |
+
Validation Accuracy: 1.0000
|
| 90 |
+
Training Loss: 0.0004
|
| 91 |
+
Validation Loss: 0.0002
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 0.9999
|
| 96 |
+
Training Loss: 0.0003
|
| 97 |
+
Validation Loss: 0.0004
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 1.0000
|
| 101 |
+
Validation Accuracy: 0.9997
|
| 102 |
+
Training Loss: 0.0002
|
| 103 |
+
Validation Loss: 0.0007
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 1.0000
|
| 107 |
+
Validation Accuracy: 0.9995
|
| 108 |
+
Training Loss: 0.0002
|
| 109 |
+
Validation Loss: 0.0011
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 1.0000
|
| 113 |
+
Validation Accuracy: 0.9997
|
| 114 |
+
Training Loss: 0.0002
|
| 115 |
+
Validation Loss: 0.0004
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9998
|
| 119 |
+
Validation Accuracy: 0.9997
|
| 120 |
+
Training Loss: 0.0006
|
| 121 |
+
Validation Loss: 0.0004
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 1.0000
|
| 125 |
+
Validation Accuracy: 0.9999
|
| 126 |
+
Training Loss: 0.0001
|
| 127 |
+
Validation Loss: 0.0003
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9999
|
| 131 |
+
Validation Accuracy: 0.9997
|
| 132 |
+
Training Loss: 0.0003
|
| 133 |
+
Validation Loss: 0.0010
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 0.9996
|
| 138 |
+
Training Loss: 0.0002
|
| 139 |
+
Validation Loss: 0.0010
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 0.9996
|
| 144 |
+
Training Loss: 0.0001
|
| 145 |
+
Validation Loss: 0.0013
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 0.9999
|
| 149 |
+
Validation Accuracy: 1.0000
|
| 150 |
+
Training Loss: 0.0003
|
| 151 |
+
Validation Loss: 0.0002
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
+
Validation Accuracy: 0.9996
|
| 156 |
+
Training Loss: 0.0000
|
| 157 |
+
Validation Loss: 0.0013
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 0.9999
|
| 161 |
+
Validation Accuracy: 0.9999
|
| 162 |
+
Training Loss: 0.0004
|
| 163 |
+
Validation Loss: 0.0004
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 0.9999
|
| 167 |
+
Validation Accuracy: 0.9997
|
| 168 |
+
Training Loss: 0.0003
|
| 169 |
+
Validation Loss: 0.0004
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 0.9999
|
| 174 |
+
Training Loss: 0.0000
|
| 175 |
+
Validation Loss: 0.0003
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 0.9999
|
| 179 |
+
Validation Accuracy: 0.9997
|
| 180 |
+
Training Loss: 0.0002
|
| 181 |
+
Validation Loss: 0.0004
|
| 182 |
+
--------------------------------------------------
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/HELMINTHS_BINARY_EfficientNetB0_Round4.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7817f69dbaa59095afcbbddea98415a28a2f8fc653809bc5a0e7819f55e8973d
|
| 3 |
+
size 20986130
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/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: 0.0000
|
| 12 |
+
F0.5-Score: 1.0000
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/confusion_matrix.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/roc_curve.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0000
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/training_accuracy.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/training_loss.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round4/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9855
|
| 5 |
+
Validation Accuracy: 0.9991
|
| 6 |
+
Training Loss: 0.0454
|
| 7 |
+
Validation Loss: 0.0058
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9991
|
| 11 |
+
Validation Accuracy: 0.9995
|
| 12 |
+
Training Loss: 0.0053
|
| 13 |
+
Validation Loss: 0.0032
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9994
|
| 17 |
+
Validation Accuracy: 0.9996
|
| 18 |
+
Training Loss: 0.0033
|
| 19 |
+
Validation Loss: 0.0020
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9998
|
| 23 |
+
Validation Accuracy: 0.9991
|
| 24 |
+
Training Loss: 0.0016
|
| 25 |
+
Validation Loss: 0.0028
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9998
|
| 29 |
+
Validation Accuracy: 0.9996
|
| 30 |
+
Training Loss: 0.0015
|
| 31 |
+
Validation Loss: 0.0012
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9997
|
| 35 |
+
Validation Accuracy: 0.9996
|
| 36 |
+
Training Loss: 0.0013
|
| 37 |
+
Validation Loss: 0.0015
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9999
|
| 41 |
+
Validation Accuracy: 0.9996
|
| 42 |
+
Training Loss: 0.0009
|
| 43 |
+
Validation Loss: 0.0011
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9998
|
| 47 |
+
Validation Accuracy: 0.9999
|
| 48 |
+
Training Loss: 0.0009
|
| 49 |
+
Validation Loss: 0.0004
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9999
|
| 53 |
+
Validation Accuracy: 0.9996
|
| 54 |
+
Training Loss: 0.0005
|
| 55 |
+
Validation Loss: 0.0010
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9998
|
| 59 |
+
Validation Accuracy: 0.9996
|
| 60 |
+
Training Loss: 0.0007
|
| 61 |
+
Validation Loss: 0.0012
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 0.9996
|
| 66 |
+
Training Loss: 0.0004
|
| 67 |
+
Validation Loss: 0.0013
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 1.0000
|
| 71 |
+
Validation Accuracy: 0.9996
|
| 72 |
+
Training Loss: 0.0004
|
| 73 |
+
Validation Loss: 0.0006
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9996
|
| 78 |
+
Training Loss: 0.0006
|
| 79 |
+
Validation Loss: 0.0014
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9998
|
| 83 |
+
Validation Accuracy: 0.9995
|
| 84 |
+
Training Loss: 0.0006
|
| 85 |
+
Validation Loss: 0.0019
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 0.9999
|
| 89 |
+
Validation Accuracy: 0.9986
|
| 90 |
+
Training Loss: 0.0002
|
| 91 |
+
Validation Loss: 0.0044
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 0.9997
|
| 96 |
+
Training Loss: 0.0002
|
| 97 |
+
Validation Loss: 0.0005
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9998
|
| 101 |
+
Validation Accuracy: 0.9996
|
| 102 |
+
Training Loss: 0.0004
|
| 103 |
+
Validation Loss: 0.0010
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 1.0000
|
| 107 |
+
Validation Accuracy: 0.9990
|
| 108 |
+
Training Loss: 0.0003
|
| 109 |
+
Validation Loss: 0.0026
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9999
|
| 113 |
+
Validation Accuracy: 0.9995
|
| 114 |
+
Training Loss: 0.0002
|
| 115 |
+
Validation Loss: 0.0015
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9999
|
| 119 |
+
Validation Accuracy: 0.9997
|
| 120 |
+
Training Loss: 0.0003
|
| 121 |
+
Validation Loss: 0.0008
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 0.9999
|
| 125 |
+
Validation Accuracy: 0.9997
|
| 126 |
+
Training Loss: 0.0004
|
| 127 |
+
Validation Loss: 0.0010
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 0.9999
|
| 131 |
+
Validation Accuracy: 0.9997
|
| 132 |
+
Training Loss: 0.0002
|
| 133 |
+
Validation Loss: 0.0008
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 0.9997
|
| 138 |
+
Training Loss: 0.0002
|
| 139 |
+
Validation Loss: 0.0010
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 1.0000
|
| 143 |
+
Validation Accuracy: 0.9997
|
| 144 |
+
Training Loss: 0.0002
|
| 145 |
+
Validation Loss: 0.0010
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 1.0000
|
| 149 |
+
Validation Accuracy: 0.9997
|
| 150 |
+
Training Loss: 0.0001
|
| 151 |
+
Validation Loss: 0.0007
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 0.9998
|
| 155 |
+
Validation Accuracy: 0.9997
|
| 156 |
+
Training Loss: 0.0006
|
| 157 |
+
Validation Loss: 0.0004
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 0.9999
|
| 161 |
+
Validation Accuracy: 1.0000
|
| 162 |
+
Training Loss: 0.0002
|
| 163 |
+
Validation Loss: 0.0001
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 1.0000
|
| 167 |
+
Validation Accuracy: 0.9997
|
| 168 |
+
Training Loss: 0.0002
|
| 169 |
+
Validation Loss: 0.0007
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 0.9999
|
| 173 |
+
Validation Accuracy: 1.0000
|
| 174 |
+
Training Loss: 0.0004
|
| 175 |
+
Validation Loss: 0.0001
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 1.0000
|
| 179 |
+
Validation Accuracy: 0.9997
|
| 180 |
+
Training Loss: 0.0002
|
| 181 |
+
Validation Loss: 0.0003
|
| 182 |
+
--------------------------------------------------
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/HELMINTHS_BINARY_EfficientNetB0_Round5.keras
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ab15d89bee2b2d65eee0cf4d4e7702ee41d37b1fa019084aee14ad9e1fd53b2d
|
| 3 |
+
size 20986130
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/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
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/confusion_matrix.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/roc_curve.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/testing_metrics.txt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
+
auc: 1.0000
|
| 3 |
+
loss: 0.0001
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/training_accuracy.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/training_loss.png
ADDED
|
EfficientNetB0/HELMINTHS_BINARY_EfficientNetB0_Round5/training_validation_metrics.txt
ADDED
|
@@ -0,0 +1,182 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Training and Validation Metrics Per Epoch
|
| 2 |
+
==================================================
|
| 3 |
+
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9857
|
| 5 |
+
Validation Accuracy: 0.9992
|
| 6 |
+
Training Loss: 0.0458
|
| 7 |
+
Validation Loss: 0.0051
|
| 8 |
+
--------------------------------------------------
|
| 9 |
+
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9990
|
| 11 |
+
Validation Accuracy: 0.9997
|
| 12 |
+
Training Loss: 0.0058
|
| 13 |
+
Validation Loss: 0.0018
|
| 14 |
+
--------------------------------------------------
|
| 15 |
+
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9994
|
| 17 |
+
Validation Accuracy: 0.9996
|
| 18 |
+
Training Loss: 0.0031
|
| 19 |
+
Validation Loss: 0.0016
|
| 20 |
+
--------------------------------------------------
|
| 21 |
+
Epoch 4
|
| 22 |
+
Training Accuracy: 0.9996
|
| 23 |
+
Validation Accuracy: 0.9996
|
| 24 |
+
Training Loss: 0.0021
|
| 25 |
+
Validation Loss: 0.0014
|
| 26 |
+
--------------------------------------------------
|
| 27 |
+
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9999
|
| 29 |
+
Validation Accuracy: 0.9995
|
| 30 |
+
Training Loss: 0.0011
|
| 31 |
+
Validation Loss: 0.0021
|
| 32 |
+
--------------------------------------------------
|
| 33 |
+
Epoch 6
|
| 34 |
+
Training Accuracy: 0.9997
|
| 35 |
+
Validation Accuracy: 0.9996
|
| 36 |
+
Training Loss: 0.0013
|
| 37 |
+
Validation Loss: 0.0010
|
| 38 |
+
--------------------------------------------------
|
| 39 |
+
Epoch 7
|
| 40 |
+
Training Accuracy: 0.9999
|
| 41 |
+
Validation Accuracy: 0.9997
|
| 42 |
+
Training Loss: 0.0009
|
| 43 |
+
Validation Loss: 0.0006
|
| 44 |
+
--------------------------------------------------
|
| 45 |
+
Epoch 8
|
| 46 |
+
Training Accuracy: 0.9999
|
| 47 |
+
Validation Accuracy: 0.9996
|
| 48 |
+
Training Loss: 0.0007
|
| 49 |
+
Validation Loss: 0.0008
|
| 50 |
+
--------------------------------------------------
|
| 51 |
+
Epoch 9
|
| 52 |
+
Training Accuracy: 0.9999
|
| 53 |
+
Validation Accuracy: 0.9995
|
| 54 |
+
Training Loss: 0.0005
|
| 55 |
+
Validation Loss: 0.0014
|
| 56 |
+
--------------------------------------------------
|
| 57 |
+
Epoch 10
|
| 58 |
+
Training Accuracy: 0.9999
|
| 59 |
+
Validation Accuracy: 0.9999
|
| 60 |
+
Training Loss: 0.0008
|
| 61 |
+
Validation Loss: 0.0004
|
| 62 |
+
--------------------------------------------------
|
| 63 |
+
Epoch 11
|
| 64 |
+
Training Accuracy: 0.9999
|
| 65 |
+
Validation Accuracy: 0.9994
|
| 66 |
+
Training Loss: 0.0005
|
| 67 |
+
Validation Loss: 0.0022
|
| 68 |
+
--------------------------------------------------
|
| 69 |
+
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9997
|
| 71 |
+
Validation Accuracy: 0.9997
|
| 72 |
+
Training Loss: 0.0008
|
| 73 |
+
Validation Loss: 0.0005
|
| 74 |
+
--------------------------------------------------
|
| 75 |
+
Epoch 13
|
| 76 |
+
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9999
|
| 78 |
+
Training Loss: 0.0005
|
| 79 |
+
Validation Loss: 0.0004
|
| 80 |
+
--------------------------------------------------
|
| 81 |
+
Epoch 14
|
| 82 |
+
Training Accuracy: 0.9999
|
| 83 |
+
Validation Accuracy: 0.9999
|
| 84 |
+
Training Loss: 0.0005
|
| 85 |
+
Validation Loss: 0.0003
|
| 86 |
+
--------------------------------------------------
|
| 87 |
+
Epoch 15
|
| 88 |
+
Training Accuracy: 1.0000
|
| 89 |
+
Validation Accuracy: 0.9996
|
| 90 |
+
Training Loss: 0.0003
|
| 91 |
+
Validation Loss: 0.0008
|
| 92 |
+
--------------------------------------------------
|
| 93 |
+
Epoch 16
|
| 94 |
+
Training Accuracy: 0.9999
|
| 95 |
+
Validation Accuracy: 1.0000
|
| 96 |
+
Training Loss: 0.0003
|
| 97 |
+
Validation Loss: 0.0001
|
| 98 |
+
--------------------------------------------------
|
| 99 |
+
Epoch 17
|
| 100 |
+
Training Accuracy: 0.9999
|
| 101 |
+
Validation Accuracy: 0.9997
|
| 102 |
+
Training Loss: 0.0004
|
| 103 |
+
Validation Loss: 0.0005
|
| 104 |
+
--------------------------------------------------
|
| 105 |
+
Epoch 18
|
| 106 |
+
Training Accuracy: 1.0000
|
| 107 |
+
Validation Accuracy: 0.9996
|
| 108 |
+
Training Loss: 0.0001
|
| 109 |
+
Validation Loss: 0.0009
|
| 110 |
+
--------------------------------------------------
|
| 111 |
+
Epoch 19
|
| 112 |
+
Training Accuracy: 0.9999
|
| 113 |
+
Validation Accuracy: 0.9999
|
| 114 |
+
Training Loss: 0.0002
|
| 115 |
+
Validation Loss: 0.0003
|
| 116 |
+
--------------------------------------------------
|
| 117 |
+
Epoch 20
|
| 118 |
+
Training Accuracy: 0.9999
|
| 119 |
+
Validation Accuracy: 1.0000
|
| 120 |
+
Training Loss: 0.0004
|
| 121 |
+
Validation Loss: 0.0002
|
| 122 |
+
--------------------------------------------------
|
| 123 |
+
Epoch 21
|
| 124 |
+
Training Accuracy: 0.9999
|
| 125 |
+
Validation Accuracy: 0.9999
|
| 126 |
+
Training Loss: 0.0003
|
| 127 |
+
Validation Loss: 0.0004
|
| 128 |
+
--------------------------------------------------
|
| 129 |
+
Epoch 22
|
| 130 |
+
Training Accuracy: 1.0000
|
| 131 |
+
Validation Accuracy: 0.9997
|
| 132 |
+
Training Loss: 0.0002
|
| 133 |
+
Validation Loss: 0.0007
|
| 134 |
+
--------------------------------------------------
|
| 135 |
+
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 0.9997
|
| 138 |
+
Training Loss: 0.0001
|
| 139 |
+
Validation Loss: 0.0007
|
| 140 |
+
--------------------------------------------------
|
| 141 |
+
Epoch 24
|
| 142 |
+
Training Accuracy: 0.9999
|
| 143 |
+
Validation Accuracy: 0.9995
|
| 144 |
+
Training Loss: 0.0002
|
| 145 |
+
Validation Loss: 0.0013
|
| 146 |
+
--------------------------------------------------
|
| 147 |
+
Epoch 25
|
| 148 |
+
Training Accuracy: 1.0000
|
| 149 |
+
Validation Accuracy: 0.9996
|
| 150 |
+
Training Loss: 0.0002
|
| 151 |
+
Validation Loss: 0.0013
|
| 152 |
+
--------------------------------------------------
|
| 153 |
+
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
+
Validation Accuracy: 0.9999
|
| 156 |
+
Training Loss: 0.0002
|
| 157 |
+
Validation Loss: 0.0002
|
| 158 |
+
--------------------------------------------------
|
| 159 |
+
Epoch 27
|
| 160 |
+
Training Accuracy: 0.9999
|
| 161 |
+
Validation Accuracy: 0.9994
|
| 162 |
+
Training Loss: 0.0003
|
| 163 |
+
Validation Loss: 0.0015
|
| 164 |
+
--------------------------------------------------
|
| 165 |
+
Epoch 28
|
| 166 |
+
Training Accuracy: 1.0000
|
| 167 |
+
Validation Accuracy: 0.9997
|
| 168 |
+
Training Loss: 0.0002
|
| 169 |
+
Validation Loss: 0.0006
|
| 170 |
+
--------------------------------------------------
|
| 171 |
+
Epoch 29
|
| 172 |
+
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 0.9999
|
| 174 |
+
Training Loss: 0.0001
|
| 175 |
+
Validation Loss: 0.0003
|
| 176 |
+
--------------------------------------------------
|
| 177 |
+
Epoch 30
|
| 178 |
+
Training Accuracy: 1.0000
|
| 179 |
+
Validation Accuracy: 0.9997
|
| 180 |
+
Training Loss: 0.0001
|
| 181 |
+
Validation Loss: 0.0006
|
| 182 |
+
--------------------------------------------------
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/HELMINTHS_BINARY_ResNet50_Round1.keras
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 101310022
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:331a49db79a347707caa58542450d51aaa33b803976e42bfef17a3db6dce1b64
|
| 3 |
size 101310022
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/classification_metrics.txt
CHANGED
|
@@ -1,12 +1,12 @@
|
|
| 1 |
Precision: 1.0000
|
| 2 |
-
Recall:
|
| 3 |
-
Sensitivity:
|
| 4 |
Specificity: 1.0000
|
| 5 |
-
F1-Score:
|
| 6 |
AUC: 1.0000
|
| 7 |
-
MCC:
|
| 8 |
-
Cohen's Kappa:
|
| 9 |
-
Balanced Accuracy:
|
| 10 |
-
Jaccard Index:
|
| 11 |
-
Log Loss: 0.
|
| 12 |
-
F0.5-Score:
|
|
|
|
| 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: 0.0000
|
| 12 |
+
F0.5-Score: 1.0000
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/confusion_matrix.png
CHANGED
|
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/testing_metrics.txt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
-
accuracy:
|
| 2 |
auc: 1.0000
|
| 3 |
-
loss: 0.
|
|
|
|
| 1 |
+
accuracy: 1.0000
|
| 2 |
auc: 1.0000
|
| 3 |
+
loss: 0.0000
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/training_accuracy.png
CHANGED
|
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/training_loss.png
CHANGED
|
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round1/training_validation_metrics.txt
CHANGED
|
@@ -1,182 +1,182 @@
|
|
| 1 |
Training and Validation Metrics Per Epoch
|
| 2 |
==================================================
|
| 3 |
Epoch 1
|
| 4 |
-
Training Accuracy: 0.
|
| 5 |
-
Validation Accuracy: 0.
|
| 6 |
-
Training Loss: 0.
|
| 7 |
-
Validation Loss: 0.
|
| 8 |
--------------------------------------------------
|
| 9 |
Epoch 2
|
| 10 |
-
Training Accuracy: 0.
|
| 11 |
-
Validation Accuracy:
|
| 12 |
-
Training Loss: 0.
|
| 13 |
-
Validation Loss: 0.
|
| 14 |
--------------------------------------------------
|
| 15 |
Epoch 3
|
| 16 |
-
Training Accuracy: 0.
|
| 17 |
-
Validation Accuracy: 0.
|
| 18 |
-
Training Loss: 0.
|
| 19 |
-
Validation Loss: 0.
|
| 20 |
--------------------------------------------------
|
| 21 |
Epoch 4
|
| 22 |
-
Training Accuracy:
|
| 23 |
-
Validation Accuracy: 0.
|
| 24 |
-
Training Loss: 0.
|
| 25 |
-
Validation Loss: 0.
|
| 26 |
--------------------------------------------------
|
| 27 |
Epoch 5
|
| 28 |
-
Training Accuracy: 0.
|
| 29 |
-
Validation Accuracy: 0.
|
| 30 |
-
Training Loss: 0.
|
| 31 |
-
Validation Loss: 0.
|
| 32 |
--------------------------------------------------
|
| 33 |
Epoch 6
|
| 34 |
-
Training Accuracy:
|
| 35 |
-
Validation Accuracy:
|
| 36 |
-
Training Loss: 0.
|
| 37 |
-
Validation Loss: 0.
|
| 38 |
--------------------------------------------------
|
| 39 |
Epoch 7
|
| 40 |
-
Training Accuracy:
|
| 41 |
-
Validation Accuracy: 0.
|
| 42 |
-
Training Loss: 0.
|
| 43 |
-
Validation Loss: 0.
|
| 44 |
--------------------------------------------------
|
| 45 |
Epoch 8
|
| 46 |
-
Training Accuracy:
|
| 47 |
-
Validation Accuracy:
|
| 48 |
-
Training Loss: 0.
|
| 49 |
-
Validation Loss: 0.
|
| 50 |
--------------------------------------------------
|
| 51 |
Epoch 9
|
| 52 |
-
Training Accuracy:
|
| 53 |
-
Validation Accuracy:
|
| 54 |
-
Training Loss: 0.
|
| 55 |
-
Validation Loss: 0.
|
| 56 |
--------------------------------------------------
|
| 57 |
Epoch 10
|
| 58 |
-
Training Accuracy:
|
| 59 |
-
Validation Accuracy:
|
| 60 |
-
Training Loss: 0.
|
| 61 |
-
Validation Loss: 0.
|
| 62 |
--------------------------------------------------
|
| 63 |
Epoch 11
|
| 64 |
-
Training Accuracy:
|
| 65 |
-
Validation Accuracy:
|
| 66 |
-
Training Loss: 0.
|
| 67 |
-
Validation Loss: 0.
|
| 68 |
--------------------------------------------------
|
| 69 |
Epoch 12
|
| 70 |
-
Training Accuracy: 0.
|
| 71 |
-
Validation Accuracy:
|
| 72 |
-
Training Loss: 0.
|
| 73 |
-
Validation Loss: 0.
|
| 74 |
--------------------------------------------------
|
| 75 |
Epoch 13
|
| 76 |
Training Accuracy: 0.9999
|
| 77 |
-
Validation Accuracy: 0.
|
| 78 |
-
Training Loss: 0.
|
| 79 |
-
Validation Loss: 0.
|
| 80 |
--------------------------------------------------
|
| 81 |
Epoch 14
|
| 82 |
Training Accuracy: 1.0000
|
| 83 |
Validation Accuracy: 1.0000
|
| 84 |
-
Training Loss: 0.
|
| 85 |
-
Validation Loss: 0.
|
| 86 |
--------------------------------------------------
|
| 87 |
Epoch 15
|
| 88 |
Training Accuracy: 1.0000
|
| 89 |
-
Validation Accuracy:
|
| 90 |
-
Training Loss: 0.
|
| 91 |
-
Validation Loss: 0.
|
| 92 |
--------------------------------------------------
|
| 93 |
Epoch 16
|
| 94 |
-
Training Accuracy:
|
| 95 |
-
Validation Accuracy:
|
| 96 |
-
Training Loss: 0.
|
| 97 |
-
Validation Loss: 0.
|
| 98 |
--------------------------------------------------
|
| 99 |
Epoch 17
|
| 100 |
Training Accuracy: 1.0000
|
| 101 |
Validation Accuracy: 1.0000
|
| 102 |
-
Training Loss: 0.
|
| 103 |
-
Validation Loss: 0.
|
| 104 |
--------------------------------------------------
|
| 105 |
Epoch 18
|
| 106 |
Training Accuracy: 1.0000
|
| 107 |
-
Validation Accuracy:
|
| 108 |
-
Training Loss: 0.
|
| 109 |
-
Validation Loss: 0.
|
| 110 |
--------------------------------------------------
|
| 111 |
Epoch 19
|
| 112 |
-
Training Accuracy:
|
| 113 |
-
Validation Accuracy:
|
| 114 |
-
Training Loss: 0.
|
| 115 |
-
Validation Loss: 0.
|
| 116 |
--------------------------------------------------
|
| 117 |
Epoch 20
|
| 118 |
-
Training Accuracy:
|
| 119 |
Validation Accuracy: 1.0000
|
| 120 |
-
Training Loss: 0.
|
| 121 |
-
Validation Loss: 0.
|
| 122 |
--------------------------------------------------
|
| 123 |
Epoch 21
|
| 124 |
Training Accuracy: 1.0000
|
| 125 |
Validation Accuracy: 1.0000
|
| 126 |
-
Training Loss: 0.
|
| 127 |
-
Validation Loss: 0.
|
| 128 |
--------------------------------------------------
|
| 129 |
Epoch 22
|
| 130 |
Training Accuracy: 1.0000
|
| 131 |
Validation Accuracy: 1.0000
|
| 132 |
-
Training Loss: 0.
|
| 133 |
-
Validation Loss: 0.
|
| 134 |
--------------------------------------------------
|
| 135 |
Epoch 23
|
| 136 |
-
Training Accuracy:
|
| 137 |
-
Validation Accuracy:
|
| 138 |
-
Training Loss: 0.
|
| 139 |
-
Validation Loss: 0.
|
| 140 |
--------------------------------------------------
|
| 141 |
Epoch 24
|
| 142 |
Training Accuracy: 1.0000
|
| 143 |
Validation Accuracy: 1.0000
|
| 144 |
-
Training Loss: 0.
|
| 145 |
-
Validation Loss: 0.
|
| 146 |
--------------------------------------------------
|
| 147 |
Epoch 25
|
| 148 |
Training Accuracy: 1.0000
|
| 149 |
Validation Accuracy: 1.0000
|
| 150 |
Training Loss: 0.0001
|
| 151 |
-
Validation Loss: 0.
|
| 152 |
--------------------------------------------------
|
| 153 |
Epoch 26
|
| 154 |
-
Training Accuracy:
|
| 155 |
Validation Accuracy: 1.0000
|
| 156 |
-
Training Loss: 0.
|
| 157 |
-
Validation Loss: 0.
|
| 158 |
--------------------------------------------------
|
| 159 |
Epoch 27
|
| 160 |
Training Accuracy: 1.0000
|
| 161 |
Validation Accuracy: 1.0000
|
| 162 |
Training Loss: 0.0000
|
| 163 |
-
Validation Loss: 0.
|
| 164 |
--------------------------------------------------
|
| 165 |
Epoch 28
|
| 166 |
Training Accuracy: 1.0000
|
| 167 |
Validation Accuracy: 1.0000
|
| 168 |
-
Training Loss: 0.
|
| 169 |
-
Validation Loss: 0.
|
| 170 |
--------------------------------------------------
|
| 171 |
Epoch 29
|
| 172 |
Training Accuracy: 1.0000
|
| 173 |
-
Validation Accuracy: 0.
|
| 174 |
-
Training Loss: 0.
|
| 175 |
-
Validation Loss: 0.
|
| 176 |
--------------------------------------------------
|
| 177 |
Epoch 30
|
| 178 |
Training Accuracy: 1.0000
|
| 179 |
-
Validation Accuracy:
|
| 180 |
Training Loss: 0.0000
|
| 181 |
-
Validation Loss: 0.
|
| 182 |
--------------------------------------------------
|
|
|
|
| 1 |
Training and Validation Metrics Per Epoch
|
| 2 |
==================================================
|
| 3 |
Epoch 1
|
| 4 |
+
Training Accuracy: 0.9953
|
| 5 |
+
Validation Accuracy: 0.9997
|
| 6 |
+
Training Loss: 0.0160
|
| 7 |
+
Validation Loss: 0.0012
|
| 8 |
--------------------------------------------------
|
| 9 |
Epoch 2
|
| 10 |
+
Training Accuracy: 0.9997
|
| 11 |
+
Validation Accuracy: 1.0000
|
| 12 |
+
Training Loss: 0.0017
|
| 13 |
+
Validation Loss: 0.0003
|
| 14 |
--------------------------------------------------
|
| 15 |
Epoch 3
|
| 16 |
+
Training Accuracy: 0.9997
|
| 17 |
+
Validation Accuracy: 0.9999
|
| 18 |
+
Training Loss: 0.0009
|
| 19 |
+
Validation Loss: 0.0006
|
| 20 |
--------------------------------------------------
|
| 21 |
Epoch 4
|
| 22 |
+
Training Accuracy: 1.0000
|
| 23 |
+
Validation Accuracy: 0.9999
|
| 24 |
+
Training Loss: 0.0003
|
| 25 |
+
Validation Loss: 0.0003
|
| 26 |
--------------------------------------------------
|
| 27 |
Epoch 5
|
| 28 |
+
Training Accuracy: 0.9999
|
| 29 |
+
Validation Accuracy: 0.9999
|
| 30 |
+
Training Loss: 0.0003
|
| 31 |
+
Validation Loss: 0.0003
|
| 32 |
--------------------------------------------------
|
| 33 |
Epoch 6
|
| 34 |
+
Training Accuracy: 1.0000
|
| 35 |
+
Validation Accuracy: 1.0000
|
| 36 |
+
Training Loss: 0.0002
|
| 37 |
+
Validation Loss: 0.0001
|
| 38 |
--------------------------------------------------
|
| 39 |
Epoch 7
|
| 40 |
+
Training Accuracy: 1.0000
|
| 41 |
+
Validation Accuracy: 0.9999
|
| 42 |
+
Training Loss: 0.0002
|
| 43 |
+
Validation Loss: 0.0002
|
| 44 |
--------------------------------------------------
|
| 45 |
Epoch 8
|
| 46 |
+
Training Accuracy: 1.0000
|
| 47 |
+
Validation Accuracy: 1.0000
|
| 48 |
+
Training Loss: 0.0001
|
| 49 |
+
Validation Loss: 0.0001
|
| 50 |
--------------------------------------------------
|
| 51 |
Epoch 9
|
| 52 |
+
Training Accuracy: 1.0000
|
| 53 |
+
Validation Accuracy: 1.0000
|
| 54 |
+
Training Loss: 0.0001
|
| 55 |
+
Validation Loss: 0.0000
|
| 56 |
--------------------------------------------------
|
| 57 |
Epoch 10
|
| 58 |
+
Training Accuracy: 1.0000
|
| 59 |
+
Validation Accuracy: 1.0000
|
| 60 |
+
Training Loss: 0.0001
|
| 61 |
+
Validation Loss: 0.0000
|
| 62 |
--------------------------------------------------
|
| 63 |
Epoch 11
|
| 64 |
+
Training Accuracy: 1.0000
|
| 65 |
+
Validation Accuracy: 1.0000
|
| 66 |
+
Training Loss: 0.0000
|
| 67 |
+
Validation Loss: 0.0000
|
| 68 |
--------------------------------------------------
|
| 69 |
Epoch 12
|
| 70 |
+
Training Accuracy: 0.9999
|
| 71 |
+
Validation Accuracy: 0.9996
|
| 72 |
+
Training Loss: 0.0002
|
| 73 |
+
Validation Loss: 0.0010
|
| 74 |
--------------------------------------------------
|
| 75 |
Epoch 13
|
| 76 |
Training Accuracy: 0.9999
|
| 77 |
+
Validation Accuracy: 0.9999
|
| 78 |
+
Training Loss: 0.0002
|
| 79 |
+
Validation Loss: 0.0002
|
| 80 |
--------------------------------------------------
|
| 81 |
Epoch 14
|
| 82 |
Training Accuracy: 1.0000
|
| 83 |
Validation Accuracy: 1.0000
|
| 84 |
+
Training Loss: 0.0001
|
| 85 |
+
Validation Loss: 0.0000
|
| 86 |
--------------------------------------------------
|
| 87 |
Epoch 15
|
| 88 |
Training Accuracy: 1.0000
|
| 89 |
+
Validation Accuracy: 0.9999
|
| 90 |
+
Training Loss: 0.0001
|
| 91 |
+
Validation Loss: 0.0002
|
| 92 |
--------------------------------------------------
|
| 93 |
Epoch 16
|
| 94 |
+
Training Accuracy: 1.0000
|
| 95 |
+
Validation Accuracy: 1.0000
|
| 96 |
+
Training Loss: 0.0000
|
| 97 |
+
Validation Loss: 0.0000
|
| 98 |
--------------------------------------------------
|
| 99 |
Epoch 17
|
| 100 |
Training Accuracy: 1.0000
|
| 101 |
Validation Accuracy: 1.0000
|
| 102 |
+
Training Loss: 0.0000
|
| 103 |
+
Validation Loss: 0.0001
|
| 104 |
--------------------------------------------------
|
| 105 |
Epoch 18
|
| 106 |
Training Accuracy: 1.0000
|
| 107 |
+
Validation Accuracy: 1.0000
|
| 108 |
+
Training Loss: 0.0000
|
| 109 |
+
Validation Loss: 0.0000
|
| 110 |
--------------------------------------------------
|
| 111 |
Epoch 19
|
| 112 |
+
Training Accuracy: 1.0000
|
| 113 |
+
Validation Accuracy: 0.9999
|
| 114 |
+
Training Loss: 0.0000
|
| 115 |
+
Validation Loss: 0.0002
|
| 116 |
--------------------------------------------------
|
| 117 |
Epoch 20
|
| 118 |
+
Training Accuracy: 1.0000
|
| 119 |
Validation Accuracy: 1.0000
|
| 120 |
+
Training Loss: 0.0002
|
| 121 |
+
Validation Loss: 0.0000
|
| 122 |
--------------------------------------------------
|
| 123 |
Epoch 21
|
| 124 |
Training Accuracy: 1.0000
|
| 125 |
Validation Accuracy: 1.0000
|
| 126 |
+
Training Loss: 0.0000
|
| 127 |
+
Validation Loss: 0.0000
|
| 128 |
--------------------------------------------------
|
| 129 |
Epoch 22
|
| 130 |
Training Accuracy: 1.0000
|
| 131 |
Validation Accuracy: 1.0000
|
| 132 |
+
Training Loss: 0.0002
|
| 133 |
+
Validation Loss: 0.0000
|
| 134 |
--------------------------------------------------
|
| 135 |
Epoch 23
|
| 136 |
+
Training Accuracy: 1.0000
|
| 137 |
+
Validation Accuracy: 1.0000
|
| 138 |
+
Training Loss: 0.0000
|
| 139 |
+
Validation Loss: 0.0000
|
| 140 |
--------------------------------------------------
|
| 141 |
Epoch 24
|
| 142 |
Training Accuracy: 1.0000
|
| 143 |
Validation Accuracy: 1.0000
|
| 144 |
+
Training Loss: 0.0000
|
| 145 |
+
Validation Loss: 0.0000
|
| 146 |
--------------------------------------------------
|
| 147 |
Epoch 25
|
| 148 |
Training Accuracy: 1.0000
|
| 149 |
Validation Accuracy: 1.0000
|
| 150 |
Training Loss: 0.0001
|
| 151 |
+
Validation Loss: 0.0000
|
| 152 |
--------------------------------------------------
|
| 153 |
Epoch 26
|
| 154 |
+
Training Accuracy: 1.0000
|
| 155 |
Validation Accuracy: 1.0000
|
| 156 |
+
Training Loss: 0.0001
|
| 157 |
+
Validation Loss: 0.0000
|
| 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: 0.0001
|
| 169 |
+
Validation Loss: 0.0000
|
| 170 |
--------------------------------------------------
|
| 171 |
Epoch 29
|
| 172 |
Training Accuracy: 1.0000
|
| 173 |
+
Validation Accuracy: 0.9999
|
| 174 |
+
Training Loss: 0.0000
|
| 175 |
+
Validation Loss: 0.0001
|
| 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 |
--------------------------------------------------
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round2/HELMINTHS_BINARY_ResNet50_Round2.keras
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 101310022
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:06a71d9bb5e215bb633a242d26d66b221239f18bb81fe029f8dc0278ea11ed5b
|
| 3 |
size 101310022
|
ResNet50/HELMINTHS_BINARY_ResNet50_Round2/classification_metrics.txt
CHANGED
|
@@ -1,12 +1,12 @@
|
|
| 1 |
Precision: 1.0000
|
| 2 |
-
Recall:
|
| 3 |
-
Sensitivity:
|
| 4 |
Specificity: 1.0000
|
| 5 |
-
F1-Score:
|
| 6 |
AUC: 1.0000
|
| 7 |
-
MCC:
|
| 8 |
-
Cohen's Kappa:
|
| 9 |
-
Balanced Accuracy:
|
| 10 |
-
Jaccard Index:
|
| 11 |
-
Log Loss: 0.
|
| 12 |
-
F0.5-Score:
|
|
|
|
| 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
|