diff --git a/.gitattributes b/.gitattributes index c444e02da7cfd0d965c634fa52d0de3dda65c1ba..409a4f6e6e63520cd800545b75a96b7ec5ddb1f6 100644 --- a/.gitattributes +++ b/.gitattributes @@ -43,3 +43,13 @@ ConvNeXtBase/BINARY_ConvNeXtBase_Round2/BINARY_ConvNeXtBase_Round2.keras filter= ConvNeXtBase/BINARY_ConvNeXtBase_Round3/BINARY_ConvNeXtBase_Round3.keras filter=lfs diff=lfs merge=lfs -text ConvNeXtBase/BINARY_ConvNeXtBase_Round4/BINARY_ConvNeXtBase_Round4.keras filter=lfs diff=lfs merge=lfs -text ConvNeXtBase/BINARY_ConvNeXtBase_Round5/BINARY_ConvNeXtBase_Round5.keras filter=lfs diff=lfs merge=lfs -text +DenseNet169/BINARY_DenseNet169_Round1/BINARY_DenseNet169_Round1.keras filter=lfs diff=lfs merge=lfs -text +DenseNet169/BINARY_DenseNet169_Round2/BINARY_DenseNet169_Round2.keras filter=lfs diff=lfs merge=lfs -text +DenseNet169/BINARY_DenseNet169_Round3/BINARY_DenseNet169_Round3.keras filter=lfs diff=lfs merge=lfs -text +DenseNet169/BINARY_DenseNet169_Round4/BINARY_DenseNet169_Round4.keras filter=lfs diff=lfs merge=lfs -text +DenseNet169/BINARY_DenseNet169_Round5/BINARY_DenseNet169_Round5.keras filter=lfs diff=lfs merge=lfs -text +MobileNetV2/BINARY_MobileNetV2_Round1/BINARY_MobileNetV2_Round1.keras filter=lfs diff=lfs merge=lfs -text +MobileNetV2/BINARY_MobileNetV2_Round2/BINARY_MobileNetV2_Round2.keras filter=lfs diff=lfs merge=lfs -text +MobileNetV2/BINARY_MobileNetV2_Round3/BINARY_MobileNetV2_Round3.keras filter=lfs diff=lfs merge=lfs -text +MobileNetV2/BINARY_MobileNetV2_Round4/BINARY_MobileNetV2_Round4.keras filter=lfs diff=lfs merge=lfs -text +MobileNetV2/BINARY_MobileNetV2_Round5/BINARY_MobileNetV2_Round5.keras filter=lfs diff=lfs merge=lfs -text diff --git a/DenseNet169/BINARY_DenseNet169_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png b/DenseNet169/BINARY_DenseNet169_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round1/BINARY_DenseNet169_Round1.keras b/DenseNet169/BINARY_DenseNet169_Round1/BINARY_DenseNet169_Round1.keras new file mode 100644 index 0000000000000000000000000000000000000000..960c427a530d2a3a338c5516d8854016f9ea3dca --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round1/BINARY_DenseNet169_Round1.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8f982465e5fbe2c16be33995b753c209cbd4f0c109ec7981c51bcb9efa7c7f67 +size 57791210 diff --git a/DenseNet169/BINARY_DenseNet169_Round1/classification_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round1/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..fe40085203fc50914f80f570e2a15484579e8e46 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round1/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 1.0000 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 1.0000 +F1-Score: 1.0000 +AUC: 1.0000 +MCC: 1.0000 +Cohen's Kappa: 1.0000 +Balanced Accuracy: 1.0000 +Jaccard Index: 1.0000 +Log Loss: 0.0001 +F0.5-Score: 1.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round1/confusion_matrix.png b/DenseNet169/BINARY_DenseNet169_Round1/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round1/confusion_matrix.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round1/roc_curve.png b/DenseNet169/BINARY_DenseNet169_Round1/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..36e7da7c44fd35c6265775f18067784243763ecf Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round1/roc_curve.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round1/testing_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round1/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca3b8f50d3d99e9356d7c8a58b5fd7ab5ba04b46 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round1/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 1.0000 +auc: 1.0000 +loss: 0.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round1/training_accuracy.png b/DenseNet169/BINARY_DenseNet169_Round1/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..0b8b79abd43de7dccc4cb83e466a99bb3c26e5d5 Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round1/training_accuracy.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round1/training_loss.png b/DenseNet169/BINARY_DenseNet169_Round1/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..edbb3f0575e4f4e6c1a25327d2ca5d4dddfc19f2 Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round1/training_loss.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round1/training_validation_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round1/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..b04f8def6d130765258a3d38c967e0cff2f0c456 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round1/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9773 + Validation Accuracy: 0.9976 + Training Loss: 0.0732 + Validation Loss: 0.0096 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9982 + Validation Accuracy: 0.9994 + Training Loss: 0.0093 + Validation Loss: 0.0037 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9988 + Validation Accuracy: 0.9996 + Training Loss: 0.0047 + Validation Loss: 0.0023 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9992 + Validation Accuracy: 0.9992 + Training Loss: 0.0035 + Validation Loss: 0.0024 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9996 + Training Loss: 0.0022 + Validation Loss: 0.0016 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9992 + Training Loss: 0.0019 + Validation Loss: 0.0023 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0013 + Validation Loss: 0.0016 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0014 + Validation Loss: 0.0015 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0008 + Validation Loss: 0.0015 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0006 + Validation Loss: 0.0009 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0005 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0004 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0007 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9996 + Training Loss: 0.0006 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9992 + Training Loss: 0.0002 + Validation Loss: 0.0020 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0004 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0005 +-------------------------------------------------- diff --git a/DenseNet169/BINARY_DenseNet169_Round2/BINARY_DenseNet169_Round2.keras b/DenseNet169/BINARY_DenseNet169_Round2/BINARY_DenseNet169_Round2.keras new file mode 100644 index 0000000000000000000000000000000000000000..a8c2c58d373e3add992d20b4906165610358772d --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round2/BINARY_DenseNet169_Round2.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:08d2b67f52bc8566604ebbd731ac34c8a40c40f8252e5cd6e9f82d2997e192f5 +size 57791210 diff --git a/DenseNet169/BINARY_DenseNet169_Round2/classification_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round2/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a404a9b3b956e3b672634e8298a648d3d58e89d --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round2/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 1.0000 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 1.0000 +F1-Score: 1.0000 +AUC: 1.0000 +MCC: 1.0000 +Cohen's Kappa: 1.0000 +Balanced Accuracy: 1.0000 +Jaccard Index: 1.0000 +Log Loss: 0.0000 +F0.5-Score: 1.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round2/confusion_matrix.png b/DenseNet169/BINARY_DenseNet169_Round2/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round2/confusion_matrix.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round2/roc_curve.png b/DenseNet169/BINARY_DenseNet169_Round2/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..36e7da7c44fd35c6265775f18067784243763ecf Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round2/roc_curve.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round2/testing_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round2/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca3b8f50d3d99e9356d7c8a58b5fd7ab5ba04b46 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round2/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 1.0000 +auc: 1.0000 +loss: 0.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round2/training_accuracy.png b/DenseNet169/BINARY_DenseNet169_Round2/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..c1e4ec08d1887d665ef5c1fa585a1255c22b7774 Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round2/training_accuracy.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round2/training_loss.png b/DenseNet169/BINARY_DenseNet169_Round2/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..3ba72bd4ec9664cd6f5d57595d24ccf455fed9a8 Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round2/training_loss.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round2/training_validation_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round2/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..a8880b0f2233d6540f09ecdacc0f4d27ce161811 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round2/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9775 + Validation Accuracy: 0.9978 + Training Loss: 0.0756 + Validation Loss: 0.0087 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9983 + Validation Accuracy: 0.9992 + Training Loss: 0.0095 + Validation Loss: 0.0043 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9996 + Training Loss: 0.0051 + Validation Loss: 0.0025 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9998 + Training Loss: 0.0036 + Validation Loss: 0.0016 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9996 + Training Loss: 0.0025 + Validation Loss: 0.0017 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9998 + Training Loss: 0.0020 + Validation Loss: 0.0011 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9996 + Training Loss: 0.0013 + Validation Loss: 0.0015 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9996 + Training Loss: 0.0012 + Validation Loss: 0.0010 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0009 + Validation Loss: 0.0009 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0009 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0005 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0005 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9996 + Training Loss: 0.0007 + Validation Loss: 0.0009 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0005 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0001 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0000 + Validation Loss: 0.0001 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- diff --git a/DenseNet169/BINARY_DenseNet169_Round3/.ipynb_checkpoints/confusion_matrix-checkpoint.png b/DenseNet169/BINARY_DenseNet169_Round3/.ipynb_checkpoints/confusion_matrix-checkpoint.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round3/.ipynb_checkpoints/confusion_matrix-checkpoint.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round3/BINARY_DenseNet169_Round3.keras b/DenseNet169/BINARY_DenseNet169_Round3/BINARY_DenseNet169_Round3.keras new file mode 100644 index 0000000000000000000000000000000000000000..d3106af5f89a74e3dab598fd7f39bb3cbd750910 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round3/BINARY_DenseNet169_Round3.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3f7488a86e56380475bab670b1aeac9f505c351e317fc80af37fc4db6b14337e +size 57791210 diff --git a/DenseNet169/BINARY_DenseNet169_Round3/classification_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round3/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a404a9b3b956e3b672634e8298a648d3d58e89d --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round3/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 1.0000 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 1.0000 +F1-Score: 1.0000 +AUC: 1.0000 +MCC: 1.0000 +Cohen's Kappa: 1.0000 +Balanced Accuracy: 1.0000 +Jaccard Index: 1.0000 +Log Loss: 0.0000 +F0.5-Score: 1.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round3/confusion_matrix.png b/DenseNet169/BINARY_DenseNet169_Round3/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round3/confusion_matrix.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round3/roc_curve.png b/DenseNet169/BINARY_DenseNet169_Round3/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..36e7da7c44fd35c6265775f18067784243763ecf Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round3/roc_curve.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round3/testing_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round3/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca3b8f50d3d99e9356d7c8a58b5fd7ab5ba04b46 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round3/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 1.0000 +auc: 1.0000 +loss: 0.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round3/training_accuracy.png b/DenseNet169/BINARY_DenseNet169_Round3/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..4c0c720049a86397d57358f16df047baf9b5348e Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round3/training_accuracy.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round3/training_loss.png b/DenseNet169/BINARY_DenseNet169_Round3/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..8f3edd7527786d5bbeed4bd5da2939cead32a6ec Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round3/training_loss.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round3/training_validation_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round3/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..ccfdbcfbabbc45041be7b1f4d68b94b121e57cc0 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round3/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9708 + Validation Accuracy: 0.9970 + Training Loss: 0.0846 + Validation Loss: 0.0106 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9980 + Validation Accuracy: 0.9992 + Training Loss: 0.0103 + Validation Loss: 0.0040 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9989 + Validation Accuracy: 0.9996 + Training Loss: 0.0054 + Validation Loss: 0.0023 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9987 + Validation Accuracy: 0.9998 + Training Loss: 0.0041 + Validation Loss: 0.0016 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9998 + Training Loss: 0.0023 + Validation Loss: 0.0014 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9998 + Training Loss: 0.0023 + Validation Loss: 0.0014 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9998 + Training Loss: 0.0013 + Validation Loss: 0.0013 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0009 + Validation Loss: 0.0011 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9998 + Training Loss: 0.0013 + Validation Loss: 0.0009 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9998 + Training Loss: 0.0011 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0008 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0004 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0005 + Validation Loss: 0.0013 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0005 + Validation Loss: 0.0014 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0004 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0006 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9996 + Training Loss: 0.0001 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9996 + Training Loss: 0.0001 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0001 + Validation Loss: 0.0013 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0003 +-------------------------------------------------- diff --git a/DenseNet169/BINARY_DenseNet169_Round4/BINARY_DenseNet169_Round4.keras b/DenseNet169/BINARY_DenseNet169_Round4/BINARY_DenseNet169_Round4.keras new file mode 100644 index 0000000000000000000000000000000000000000..1848d0681b6fd73d5560f92a828380a083c21f0b --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round4/BINARY_DenseNet169_Round4.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:51431d1875636dec7b1d81f0631368b6d0350e0ebb89554c988a31f35ad3e3f0 +size 57791210 diff --git a/DenseNet169/BINARY_DenseNet169_Round4/classification_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round4/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a404a9b3b956e3b672634e8298a648d3d58e89d --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round4/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 1.0000 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 1.0000 +F1-Score: 1.0000 +AUC: 1.0000 +MCC: 1.0000 +Cohen's Kappa: 1.0000 +Balanced Accuracy: 1.0000 +Jaccard Index: 1.0000 +Log Loss: 0.0000 +F0.5-Score: 1.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round4/confusion_matrix.png b/DenseNet169/BINARY_DenseNet169_Round4/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round4/confusion_matrix.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round4/roc_curve.png b/DenseNet169/BINARY_DenseNet169_Round4/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..36e7da7c44fd35c6265775f18067784243763ecf Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round4/roc_curve.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round4/testing_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round4/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca3b8f50d3d99e9356d7c8a58b5fd7ab5ba04b46 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round4/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 1.0000 +auc: 1.0000 +loss: 0.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round4/training_accuracy.png b/DenseNet169/BINARY_DenseNet169_Round4/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..b5b23adfb3f8165ba21b87f96b51f3d49574173d Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round4/training_accuracy.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round4/training_loss.png b/DenseNet169/BINARY_DenseNet169_Round4/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..e5554131fd34b596ad8f4528a7d3cbe9ecd8041e Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round4/training_loss.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round4/training_validation_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round4/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..9f0956ba391589f2a20dba12ed22f406c492db12 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round4/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9737 + Validation Accuracy: 0.9978 + Training Loss: 0.0837 + Validation Loss: 0.0097 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9981 + Validation Accuracy: 0.9990 + Training Loss: 0.0099 + Validation Loss: 0.0041 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9990 + Training Loss: 0.0055 + Validation Loss: 0.0035 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9996 + Training Loss: 0.0037 + Validation Loss: 0.0019 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9998 + Training Loss: 0.0030 + Validation Loss: 0.0018 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9998 + Training Loss: 0.0016 + Validation Loss: 0.0014 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9996 + Validation Accuracy: 1.0000 + Training Loss: 0.0016 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9998 + Validation Accuracy: 1.0000 + Training Loss: 0.0012 + Validation Loss: 0.0010 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0008 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9998 + Training Loss: 0.0009 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9998 + Training Loss: 0.0008 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0005 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0003 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0004 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0003 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0006 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0003 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0000 + Validation Loss: 0.0004 +-------------------------------------------------- diff --git a/DenseNet169/BINARY_DenseNet169_Round5/BINARY_DenseNet169_Round5.keras b/DenseNet169/BINARY_DenseNet169_Round5/BINARY_DenseNet169_Round5.keras new file mode 100644 index 0000000000000000000000000000000000000000..6f17d81bc51397da10e17ad81463afcfd4af5ef7 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round5/BINARY_DenseNet169_Round5.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f1c1c075cbfaafe3f29655fc3566f29a653cfb4c33427fa218d77f2f14920ae7 +size 57791210 diff --git a/DenseNet169/BINARY_DenseNet169_Round5/classification_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round5/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a404a9b3b956e3b672634e8298a648d3d58e89d --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round5/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 1.0000 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 1.0000 +F1-Score: 1.0000 +AUC: 1.0000 +MCC: 1.0000 +Cohen's Kappa: 1.0000 +Balanced Accuracy: 1.0000 +Jaccard Index: 1.0000 +Log Loss: 0.0000 +F0.5-Score: 1.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round5/confusion_matrix.png b/DenseNet169/BINARY_DenseNet169_Round5/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..9f529ae204663f2d457f293cdd09ea8f9b51935c Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round5/confusion_matrix.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round5/roc_curve.png b/DenseNet169/BINARY_DenseNet169_Round5/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..36e7da7c44fd35c6265775f18067784243763ecf Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round5/roc_curve.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round5/testing_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round5/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca3b8f50d3d99e9356d7c8a58b5fd7ab5ba04b46 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round5/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 1.0000 +auc: 1.0000 +loss: 0.0000 diff --git a/DenseNet169/BINARY_DenseNet169_Round5/training_accuracy.png b/DenseNet169/BINARY_DenseNet169_Round5/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..ff4260e021cc60bc8da73f284835a503ad2675bf Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round5/training_accuracy.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round5/training_loss.png b/DenseNet169/BINARY_DenseNet169_Round5/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..2fbc7fc8a47697070a6d75871debeaa01111f9be Binary files /dev/null and b/DenseNet169/BINARY_DenseNet169_Round5/training_loss.png differ diff --git a/DenseNet169/BINARY_DenseNet169_Round5/training_validation_metrics.txt b/DenseNet169/BINARY_DenseNet169_Round5/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..a6e40a2b08ef453857e37d1b04ecbb94867ad5e2 --- /dev/null +++ b/DenseNet169/BINARY_DenseNet169_Round5/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9743 + Validation Accuracy: 0.9976 + Training Loss: 0.0800 + Validation Loss: 0.0098 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9977 + Validation Accuracy: 0.9990 + Training Loss: 0.0104 + Validation Loss: 0.0040 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9986 + Validation Accuracy: 0.9996 + Training Loss: 0.0056 + Validation Loss: 0.0025 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9992 + Training Loss: 0.0034 + Validation Loss: 0.0023 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9996 + Training Loss: 0.0027 + Validation Loss: 0.0016 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9998 + Training Loss: 0.0019 + Validation Loss: 0.0012 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0015 + Validation Loss: 0.0010 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0010 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0010 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0006 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0005 + Validation Loss: 0.0007 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0004 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0005 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0003 + Validation Loss: 0.0006 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0007 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0004 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9996 + Training Loss: 0.0005 + Validation Loss: 0.0008 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0003 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0004 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9999 + Validation Accuracy: 1.0000 + Training Loss: 0.0002 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0003 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0003 + Validation Loss: 0.0004 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 1.0000 + Validation Accuracy: 1.0000 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9998 + Training Loss: 0.0002 + Validation Loss: 0.0005 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9998 + Training Loss: 0.0001 + Validation Loss: 0.0002 +-------------------------------------------------- diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png b/MobileNetV2/BINARY_MobileNetV2_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png new file mode 100644 index 0000000000000000000000000000000000000000..4af48987a0a3003dc08c3844c0f59a8713da8140 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/BINARY_MobileNetV2_Round1.keras b/MobileNetV2/BINARY_MobileNetV2_Round1/BINARY_MobileNetV2_Round1.keras new file mode 100644 index 0000000000000000000000000000000000000000..da75793af6be81fcd3e939df99389bb4261f335a --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round1/BINARY_MobileNetV2_Round1.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:642a4512781afa153dfd492757d767122bc8e0cfd92aee8b1eda0c6dd3cee80b +size 13561499 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/classification_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round1/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..1dc70542ab7bf109549d47c60a1d01754a083aaa --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round1/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 0.9984 +Recall: 0.9992 +Sensitivity: 0.9992 +Specificity: 0.9984 +F1-Score: 0.9988 +AUC: 1.0000 +MCC: 0.9976 +Cohen's Kappa: 0.9976 +Balanced Accuracy: 0.9988 +Jaccard Index: 0.9976 +Log Loss: 0.0034 +F0.5-Score: 0.9986 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/confusion_matrix.png b/MobileNetV2/BINARY_MobileNetV2_Round1/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..4af48987a0a3003dc08c3844c0f59a8713da8140 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round1/confusion_matrix.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/roc_curve.png b/MobileNetV2/BINARY_MobileNetV2_Round1/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..b7d9b67c607ba2fa1ad15c53aaf43cf4bce0d3c7 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round1/roc_curve.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/testing_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round1/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..e2963980757ea8623070c404eafb814a7fefa68b --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round1/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 0.9988 +auc: 1.0000 +loss: 0.0034 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/training_accuracy.png b/MobileNetV2/BINARY_MobileNetV2_Round1/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..9170ac681f62f49af84477d0681291d8aa30956b Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round1/training_accuracy.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/training_loss.png b/MobileNetV2/BINARY_MobileNetV2_Round1/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..3eee05cd3df5cc1be9efddc737689bbfe6742eaf Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round1/training_loss.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round1/training_validation_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round1/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..2b8c9825b172798b535e4391b48559be24a00098 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round1/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9722 + Validation Accuracy: 0.9936 + Training Loss: 0.0798 + Validation Loss: 0.0201 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9956 + Validation Accuracy: 0.9952 + Training Loss: 0.0145 + Validation Loss: 0.0129 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9969 + Validation Accuracy: 0.9962 + Training Loss: 0.0105 + Validation Loss: 0.0098 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9979 + Validation Accuracy: 0.9976 + Training Loss: 0.0077 + Validation Loss: 0.0080 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9982 + Validation Accuracy: 0.9974 + Training Loss: 0.0063 + Validation Loss: 0.0079 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9987 + Validation Accuracy: 0.9976 + Training Loss: 0.0046 + Validation Loss: 0.0063 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9989 + Validation Accuracy: 0.9986 + Training Loss: 0.0041 + Validation Loss: 0.0055 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9991 + Validation Accuracy: 0.9970 + Training Loss: 0.0031 + Validation Loss: 0.0084 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9986 + Training Loss: 0.0031 + Validation Loss: 0.0052 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9988 + Validation Accuracy: 0.9974 + Training Loss: 0.0035 + Validation Loss: 0.0063 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9974 + Training Loss: 0.0022 + Validation Loss: 0.0060 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9982 + Training Loss: 0.0023 + Validation Loss: 0.0053 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9978 + Training Loss: 0.0017 + Validation Loss: 0.0062 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9968 + Training Loss: 0.0011 + Validation Loss: 0.0083 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9986 + Training Loss: 0.0015 + Validation Loss: 0.0050 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9968 + Training Loss: 0.0015 + Validation Loss: 0.0072 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9988 + Training Loss: 0.0013 + Validation Loss: 0.0041 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9980 + Training Loss: 0.0011 + Validation Loss: 0.0049 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9986 + Training Loss: 0.0014 + Validation Loss: 0.0040 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9962 + Training Loss: 0.0010 + Validation Loss: 0.0083 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9968 + Training Loss: 0.0015 + Validation Loss: 0.0079 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0011 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9984 + Training Loss: 0.0010 + Validation Loss: 0.0059 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0012 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9982 + Training Loss: 0.0006 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9980 + Training Loss: 0.0008 + Validation Loss: 0.0054 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0010 + Validation Loss: 0.0041 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9990 + Training Loss: 0.0007 + Validation Loss: 0.0034 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9990 + Training Loss: 0.0005 + Validation Loss: 0.0039 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9986 + Training Loss: 0.0005 + Validation Loss: 0.0052 +-------------------------------------------------- diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/BINARY_MobileNetV2_Round2.keras b/MobileNetV2/BINARY_MobileNetV2_Round2/BINARY_MobileNetV2_Round2.keras new file mode 100644 index 0000000000000000000000000000000000000000..3ddaa2eb66de022ca4d86de67a4fe40b1f9c56b8 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round2/BINARY_MobileNetV2_Round2.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c89f286c367727a7c24a3652e38811eefc6e4f9316c577b67a3134bf61396370 +size 13561499 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/classification_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round2/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..70c50df28c213915f357d0b11238174d013735c7 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round2/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 0.9984 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 0.9984 +F1-Score: 0.9992 +AUC: 1.0000 +MCC: 0.9984 +Cohen's Kappa: 0.9984 +Balanced Accuracy: 0.9992 +Jaccard Index: 0.9984 +Log Loss: 0.0020 +F0.5-Score: 0.9987 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/confusion_matrix.png b/MobileNetV2/BINARY_MobileNetV2_Round2/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..22a1837c279a4a716cf850f610e74cba45cdc12f Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round2/confusion_matrix.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/roc_curve.png b/MobileNetV2/BINARY_MobileNetV2_Round2/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..7129bd41e358587ed80d6e4a07826ee5be157126 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round2/roc_curve.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/testing_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round2/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..7ca989658bdeb6620103ae065991069bc9f45aae --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round2/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 0.9992 +auc: 1.0000 +loss: 0.0020 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/training_accuracy.png b/MobileNetV2/BINARY_MobileNetV2_Round2/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..2f774a3f53dfa71d3bf70ff0bdea7d0b023b087c Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round2/training_accuracy.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/training_loss.png b/MobileNetV2/BINARY_MobileNetV2_Round2/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..771744c615a54baf4b58f9271635f8f041a3753f Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round2/training_loss.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round2/training_validation_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round2/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..2ff71a45aa3453aa9f0f74d573f3b5a06e158c35 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round2/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9698 + Validation Accuracy: 0.9924 + Training Loss: 0.0840 + Validation Loss: 0.0220 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9957 + Validation Accuracy: 0.9946 + Training Loss: 0.0147 + Validation Loss: 0.0167 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9970 + Validation Accuracy: 0.9952 + Training Loss: 0.0102 + Validation Loss: 0.0122 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9974 + Validation Accuracy: 0.9954 + Training Loss: 0.0083 + Validation Loss: 0.0107 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9979 + Validation Accuracy: 0.9970 + Training Loss: 0.0067 + Validation Loss: 0.0083 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9968 + Training Loss: 0.0043 + Validation Loss: 0.0092 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9986 + Validation Accuracy: 0.9966 + Training Loss: 0.0041 + Validation Loss: 0.0101 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9987 + Validation Accuracy: 0.9964 + Training Loss: 0.0040 + Validation Loss: 0.0095 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9992 + Validation Accuracy: 0.9972 + Training Loss: 0.0030 + Validation Loss: 0.0070 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9992 + Validation Accuracy: 0.9980 + Training Loss: 0.0028 + Validation Loss: 0.0057 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9970 + Training Loss: 0.0029 + Validation Loss: 0.0068 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9982 + Training Loss: 0.0018 + Validation Loss: 0.0055 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9972 + Training Loss: 0.0018 + Validation Loss: 0.0067 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9984 + Training Loss: 0.0013 + Validation Loss: 0.0052 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9972 + Training Loss: 0.0017 + Validation Loss: 0.0092 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9978 + Training Loss: 0.0016 + Validation Loss: 0.0054 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9986 + Training Loss: 0.0007 + Validation Loss: 0.0049 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9982 + Training Loss: 0.0011 + Validation Loss: 0.0056 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9972 + Training Loss: 0.0019 + Validation Loss: 0.0078 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9978 + Training Loss: 0.0013 + Validation Loss: 0.0050 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9976 + Training Loss: 0.0011 + Validation Loss: 0.0071 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9974 + Training Loss: 0.0007 + Validation Loss: 0.0074 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9988 + Training Loss: 0.0008 + Validation Loss: 0.0041 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9980 + Training Loss: 0.0010 + Validation Loss: 0.0066 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9984 + Training Loss: 0.0005 + Validation Loss: 0.0051 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9980 + Training Loss: 0.0008 + Validation Loss: 0.0077 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9986 + Training Loss: 0.0007 + Validation Loss: 0.0053 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9968 + Training Loss: 0.0007 + Validation Loss: 0.0097 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9980 + Training Loss: 0.0006 + Validation Loss: 0.0059 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9984 + Training Loss: 0.0005 + Validation Loss: 0.0057 +-------------------------------------------------- diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/BINARY_MobileNetV2_Round3.keras b/MobileNetV2/BINARY_MobileNetV2_Round3/BINARY_MobileNetV2_Round3.keras new file mode 100644 index 0000000000000000000000000000000000000000..850cc2c2707d0966d90f77496ff600484bc32cb7 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round3/BINARY_MobileNetV2_Round3.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7a9c338a76afe88812d84272e7b3977fad2c9b25d354adeb0f6e61d3232f552f +size 13561499 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/classification_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round3/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..a5944ab349952974e07280e7e8744a3d6cc723af --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round3/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 0.9984 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 0.9984 +F1-Score: 0.9992 +AUC: 1.0000 +MCC: 0.9984 +Cohen's Kappa: 0.9984 +Balanced Accuracy: 0.9992 +Jaccard Index: 0.9984 +Log Loss: 0.0034 +F0.5-Score: 0.9987 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/confusion_matrix.png b/MobileNetV2/BINARY_MobileNetV2_Round3/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..22a1837c279a4a716cf850f610e74cba45cdc12f Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round3/confusion_matrix.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/roc_curve.png b/MobileNetV2/BINARY_MobileNetV2_Round3/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..9706171291149609ac05830f01eb81191dc06c11 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round3/roc_curve.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/testing_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round3/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..4b586fd450ffb4e6cec0072f35b8049fc322d6fd --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round3/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 0.9992 +auc: 1.0000 +loss: 0.0034 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/training_accuracy.png b/MobileNetV2/BINARY_MobileNetV2_Round3/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..fbe458ad9d599d6466f70c11051f2700d0015f53 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round3/training_accuracy.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/training_loss.png b/MobileNetV2/BINARY_MobileNetV2_Round3/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..c6b8df58dbdaab9fe77d6c9138c40d0e7eda5117 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round3/training_loss.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round3/training_validation_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round3/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..12eb185e9f72348b3004ca4f75452dcfa5f75bcd --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round3/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9759 + Validation Accuracy: 0.9938 + Training Loss: 0.0716 + Validation Loss: 0.0195 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9964 + Validation Accuracy: 0.9940 + Training Loss: 0.0139 + Validation Loss: 0.0160 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9969 + Validation Accuracy: 0.9962 + Training Loss: 0.0098 + Validation Loss: 0.0110 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9980 + Validation Accuracy: 0.9964 + Training Loss: 0.0076 + Validation Loss: 0.0090 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9985 + Validation Accuracy: 0.9984 + Training Loss: 0.0055 + Validation Loss: 0.0062 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9983 + Validation Accuracy: 0.9984 + Training Loss: 0.0052 + Validation Loss: 0.0056 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9989 + Validation Accuracy: 0.9984 + Training Loss: 0.0035 + Validation Loss: 0.0054 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9992 + Validation Accuracy: 0.9968 + Training Loss: 0.0037 + Validation Loss: 0.0076 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9982 + Training Loss: 0.0028 + Validation Loss: 0.0052 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9991 + Validation Accuracy: 0.9986 + Training Loss: 0.0030 + Validation Loss: 0.0042 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9992 + Validation Accuracy: 0.9978 + Training Loss: 0.0021 + Validation Loss: 0.0061 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9976 + Training Loss: 0.0025 + Validation Loss: 0.0091 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9991 + Validation Accuracy: 0.9980 + Training Loss: 0.0028 + Validation Loss: 0.0046 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9992 + Training Loss: 0.0019 + Validation Loss: 0.0037 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9984 + Training Loss: 0.0010 + Validation Loss: 0.0037 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9984 + Training Loss: 0.0012 + Validation Loss: 0.0039 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9982 + Training Loss: 0.0012 + Validation Loss: 0.0043 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9992 + Validation Accuracy: 0.9982 + Training Loss: 0.0017 + Validation Loss: 0.0055 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9978 + Training Loss: 0.0009 + Validation Loss: 0.0059 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9994 + Training Loss: 0.0011 + Validation Loss: 0.0032 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9978 + Training Loss: 0.0013 + Validation Loss: 0.0055 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0009 + Validation Loss: 0.0046 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9996 + Training Loss: 0.0010 + Validation Loss: 0.0033 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9988 + Training Loss: 0.0007 + Validation Loss: 0.0037 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9988 + Training Loss: 0.0008 + Validation Loss: 0.0046 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9988 + Training Loss: 0.0003 + Validation Loss: 0.0051 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9982 + Training Loss: 0.0011 + Validation Loss: 0.0046 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9982 + Training Loss: 0.0008 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9988 + Training Loss: 0.0007 + Validation Loss: 0.0038 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9982 + Training Loss: 0.0005 + Validation Loss: 0.0046 +-------------------------------------------------- diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/BINARY_MobileNetV2_Round4.keras b/MobileNetV2/BINARY_MobileNetV2_Round4/BINARY_MobileNetV2_Round4.keras new file mode 100644 index 0000000000000000000000000000000000000000..c7d6ac2d4c766fb4398dc1f371eca948684b3186 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round4/BINARY_MobileNetV2_Round4.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a68d793dff842e5417f71fefa9b23615fd14eac193d6cc5ceae5b3cce8479844 +size 13561499 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/classification_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round4/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..5895e0d72a40abe70aa4304379f4a251484b96a7 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round4/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 0.9984 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 0.9984 +F1-Score: 0.9992 +AUC: 1.0000 +MCC: 0.9984 +Cohen's Kappa: 0.9984 +Balanced Accuracy: 0.9992 +Jaccard Index: 0.9984 +Log Loss: 0.0028 +F0.5-Score: 0.9987 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/confusion_matrix.png b/MobileNetV2/BINARY_MobileNetV2_Round4/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..22a1837c279a4a716cf850f610e74cba45cdc12f Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round4/confusion_matrix.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/roc_curve.png b/MobileNetV2/BINARY_MobileNetV2_Round4/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..6fb146d2ba943745ae4abec618c9d0b12a942571 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round4/roc_curve.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/testing_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round4/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..9c724f734df7c734f69a71d11bd8fd512e200ecf --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round4/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 0.9992 +auc: 1.0000 +loss: 0.0028 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/training_accuracy.png b/MobileNetV2/BINARY_MobileNetV2_Round4/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..44a3db0a11fcebcc6f7ba1b9670200f9e7ec3d97 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round4/training_accuracy.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/training_loss.png b/MobileNetV2/BINARY_MobileNetV2_Round4/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..6978dbf2d18f9079bbb4f45af7a5ec71b5b86635 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round4/training_loss.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round4/training_validation_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round4/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..bda1e6bd7c3c1cbf68965f120e48d4e6b967b8b5 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round4/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9688 + Validation Accuracy: 0.9924 + Training Loss: 0.0875 + Validation Loss: 0.0239 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9959 + Validation Accuracy: 0.9938 + Training Loss: 0.0169 + Validation Loss: 0.0170 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9975 + Validation Accuracy: 0.9954 + Training Loss: 0.0100 + Validation Loss: 0.0117 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9974 + Validation Accuracy: 0.9954 + Training Loss: 0.0076 + Validation Loss: 0.0110 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9980 + Validation Accuracy: 0.9968 + Training Loss: 0.0068 + Validation Loss: 0.0084 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9985 + Validation Accuracy: 0.9954 + Training Loss: 0.0049 + Validation Loss: 0.0116 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9989 + Validation Accuracy: 0.9956 + Training Loss: 0.0046 + Validation Loss: 0.0103 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9964 + Training Loss: 0.0036 + Validation Loss: 0.0097 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9984 + Training Loss: 0.0033 + Validation Loss: 0.0059 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9982 + Training Loss: 0.0025 + Validation Loss: 0.0061 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9968 + Training Loss: 0.0022 + Validation Loss: 0.0091 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9972 + Training Loss: 0.0022 + Validation Loss: 0.0100 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9970 + Training Loss: 0.0021 + Validation Loss: 0.0084 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9991 + Validation Accuracy: 0.9976 + Training Loss: 0.0025 + Validation Loss: 0.0076 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9976 + Training Loss: 0.0018 + Validation Loss: 0.0066 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9978 + Training Loss: 0.0010 + Validation Loss: 0.0076 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9988 + Training Loss: 0.0012 + Validation Loss: 0.0057 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9964 + Training Loss: 0.0012 + Validation Loss: 0.0088 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9974 + Training Loss: 0.0013 + Validation Loss: 0.0086 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9964 + Training Loss: 0.0009 + Validation Loss: 0.0101 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9984 + Training Loss: 0.0012 + Validation Loss: 0.0050 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9976 + Training Loss: 0.0012 + Validation Loss: 0.0069 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9972 + Training Loss: 0.0010 + Validation Loss: 0.0078 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9972 + Training Loss: 0.0006 + Validation Loss: 0.0086 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0010 + Validation Loss: 0.0050 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9988 + Training Loss: 0.0009 + Validation Loss: 0.0045 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9978 + Training Loss: 0.0004 + Validation Loss: 0.0070 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9998 + Validation Accuracy: 0.9986 + Training Loss: 0.0007 + Validation Loss: 0.0053 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9976 + Training Loss: 0.0006 + Validation Loss: 0.0078 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9982 + Training Loss: 0.0003 + Validation Loss: 0.0057 +-------------------------------------------------- diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/BINARY_MobileNetV2_Round5.keras b/MobileNetV2/BINARY_MobileNetV2_Round5/BINARY_MobileNetV2_Round5.keras new file mode 100644 index 0000000000000000000000000000000000000000..12378d34a176ba0ee3ee821d775cc2ed6df21802 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round5/BINARY_MobileNetV2_Round5.keras @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:21884bbf211cb7805cfdd6b8ac562e7149a60bb2a7e9ae4594cdb7bb90201603 +size 13561499 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/classification_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round5/classification_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..d39108d14f88482f186b912aeefca533f3e2b7d9 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round5/classification_metrics.txt @@ -0,0 +1,12 @@ +Precision: 0.9968 +Recall: 1.0000 +Sensitivity: 1.0000 +Specificity: 0.9967 +F1-Score: 0.9984 +AUC: 1.0000 +MCC: 0.9968 +Cohen's Kappa: 0.9968 +Balanced Accuracy: 0.9984 +Jaccard Index: 0.9968 +Log Loss: 0.0056 +F0.5-Score: 0.9975 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/confusion_matrix.png b/MobileNetV2/BINARY_MobileNetV2_Round5/confusion_matrix.png new file mode 100644 index 0000000000000000000000000000000000000000..951ede7cb8b6732bf9efebf20d5484f2d70fb91b Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round5/confusion_matrix.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/roc_curve.png b/MobileNetV2/BINARY_MobileNetV2_Round5/roc_curve.png new file mode 100644 index 0000000000000000000000000000000000000000..e01a7853a404e2da0dba31d7988984a9de18be16 Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round5/roc_curve.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/testing_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round5/testing_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..73dc48f3ceb68cdc4eb181ca93e6a8164118fe34 --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round5/testing_metrics.txt @@ -0,0 +1,3 @@ +accuracy: 0.9984 +auc: 0.9996 +loss: 0.0056 diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/training_accuracy.png b/MobileNetV2/BINARY_MobileNetV2_Round5/training_accuracy.png new file mode 100644 index 0000000000000000000000000000000000000000..d4924cf449221ecd24d544e9892ef20c2a97087c Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round5/training_accuracy.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/training_loss.png b/MobileNetV2/BINARY_MobileNetV2_Round5/training_loss.png new file mode 100644 index 0000000000000000000000000000000000000000..d0f5bec3e18071add337303f05aa0ccc91537a4f Binary files /dev/null and b/MobileNetV2/BINARY_MobileNetV2_Round5/training_loss.png differ diff --git a/MobileNetV2/BINARY_MobileNetV2_Round5/training_validation_metrics.txt b/MobileNetV2/BINARY_MobileNetV2_Round5/training_validation_metrics.txt new file mode 100644 index 0000000000000000000000000000000000000000..bd9a573e258e966e8ad9f9ff1ffcd632ca3042cd --- /dev/null +++ b/MobileNetV2/BINARY_MobileNetV2_Round5/training_validation_metrics.txt @@ -0,0 +1,182 @@ +Training and Validation Metrics Per Epoch +================================================== +Epoch 1 + Training Accuracy: 0.9694 + Validation Accuracy: 0.9930 + Training Loss: 0.0831 + Validation Loss: 0.0221 +-------------------------------------------------- +Epoch 2 + Training Accuracy: 0.9957 + Validation Accuracy: 0.9942 + Training Loss: 0.0162 + Validation Loss: 0.0155 +-------------------------------------------------- +Epoch 3 + Training Accuracy: 0.9970 + Validation Accuracy: 0.9958 + Training Loss: 0.0101 + Validation Loss: 0.0117 +-------------------------------------------------- +Epoch 4 + Training Accuracy: 0.9982 + Validation Accuracy: 0.9964 + Training Loss: 0.0075 + Validation Loss: 0.0120 +-------------------------------------------------- +Epoch 5 + Training Accuracy: 0.9981 + Validation Accuracy: 0.9966 + Training Loss: 0.0058 + Validation Loss: 0.0110 +-------------------------------------------------- +Epoch 6 + Training Accuracy: 0.9983 + Validation Accuracy: 0.9982 + Training Loss: 0.0051 + Validation Loss: 0.0062 +-------------------------------------------------- +Epoch 7 + Training Accuracy: 0.9988 + Validation Accuracy: 0.9968 + Training Loss: 0.0038 + Validation Loss: 0.0082 +-------------------------------------------------- +Epoch 8 + Training Accuracy: 0.9987 + Validation Accuracy: 0.9974 + Training Loss: 0.0041 + Validation Loss: 0.0074 +-------------------------------------------------- +Epoch 9 + Training Accuracy: 0.9991 + Validation Accuracy: 0.9980 + Training Loss: 0.0032 + Validation Loss: 0.0050 +-------------------------------------------------- +Epoch 10 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9974 + Training Loss: 0.0029 + Validation Loss: 0.0069 +-------------------------------------------------- +Epoch 11 + Training Accuracy: 0.9990 + Validation Accuracy: 0.9972 + Training Loss: 0.0025 + Validation Loss: 0.0073 +-------------------------------------------------- +Epoch 12 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9976 + Training Loss: 0.0021 + Validation Loss: 0.0066 +-------------------------------------------------- +Epoch 13 + Training Accuracy: 0.9991 + Validation Accuracy: 0.9980 + Training Loss: 0.0027 + Validation Loss: 0.0052 +-------------------------------------------------- +Epoch 14 + Training Accuracy: 0.9995 + Validation Accuracy: 0.9980 + Training Loss: 0.0015 + Validation Loss: 0.0053 +-------------------------------------------------- +Epoch 15 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9982 + Training Loss: 0.0014 + Validation Loss: 0.0055 +-------------------------------------------------- +Epoch 16 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9974 + Training Loss: 0.0010 + Validation Loss: 0.0063 +-------------------------------------------------- +Epoch 17 + Training Accuracy: 0.9993 + Validation Accuracy: 0.9974 + Training Loss: 0.0020 + Validation Loss: 0.0065 +-------------------------------------------------- +Epoch 18 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9980 + Training Loss: 0.0014 + Validation Loss: 0.0054 +-------------------------------------------------- +Epoch 19 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9980 + Training Loss: 0.0008 + Validation Loss: 0.0068 +-------------------------------------------------- +Epoch 20 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9982 + Training Loss: 0.0012 + Validation Loss: 0.0055 +-------------------------------------------------- +Epoch 21 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0011 + Validation Loss: 0.0049 +-------------------------------------------------- +Epoch 22 + Training Accuracy: 0.9996 + Validation Accuracy: 0.9986 + Training Loss: 0.0009 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 23 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9980 + Training Loss: 0.0007 + Validation Loss: 0.0067 +-------------------------------------------------- +Epoch 24 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9980 + Training Loss: 0.0011 + Validation Loss: 0.0066 +-------------------------------------------------- +Epoch 25 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9978 + Training Loss: 0.0006 + Validation Loss: 0.0071 +-------------------------------------------------- +Epoch 26 + Training Accuracy: 0.9997 + Validation Accuracy: 0.9986 + Training Loss: 0.0008 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 27 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9982 + Training Loss: 0.0006 + Validation Loss: 0.0064 +-------------------------------------------------- +Epoch 28 + Training Accuracy: 0.9994 + Validation Accuracy: 0.9984 + Training Loss: 0.0013 + Validation Loss: 0.0050 +-------------------------------------------------- +Epoch 29 + Training Accuracy: 1.0000 + Validation Accuracy: 0.9986 + Training Loss: 0.0004 + Validation Loss: 0.0048 +-------------------------------------------------- +Epoch 30 + Training Accuracy: 0.9999 + Validation Accuracy: 0.9976 + Training Loss: 0.0005 + Validation Loss: 0.0086 +--------------------------------------------------