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Update README.md

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  1. README.md +16 -2
README.md CHANGED
@@ -10,15 +10,24 @@ tags:
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  - ML
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  - Ai
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  ---
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- Model Card: Facial Recognition Model
 
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  Model Information
 
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  Name: Facial Means
 
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  Type: Convolutional Neural Network (CNN)
 
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  Framework: TensorFlow
 
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  Dataset: Celebrity Faces Dataset
 
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  Dataset Path: /content/drive/MyDrive/beard_dataset/celb_dataset/
 
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  Model Save Path: /content/drive/MyDrive/beard_dataset/celebrity_model.h5
 
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  Image Dimensions: 224 x 224 pixels
 
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  Batch Size: 32
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  Data Augmentation
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  Rescale: 1./255
@@ -27,7 +36,8 @@ Zoom Range: 0.2
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  Horizontal Flip: True
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  Validation Split: 20%
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  Model Architecture
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- Layer (type) Output Shape Param #
 
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  ===============================================================
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  conv2d (Conv2D) (None, 222, 222, 32) 896
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  max_pooling2d (MaxPooling2D) (None, 111, 111, 32) 0
@@ -39,6 +49,7 @@ flatten (Flatten) (None, 86528) 0
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  dense (Dense) (None, 128) 11075712
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  dense_1 (Dense) (None, 6) 774
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  ===============================================================
 
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  Total params: 11,170,734
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  Trainable params: 11,170,734
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  Non-trainable params: 0
@@ -46,8 +57,11 @@ Model Compilation
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  Optimizer: Adam
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  Loss Function: Categorical Crossentropy
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  Metrics: Accuracy
 
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  Training
 
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  Epochs: 10
 
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  Steps per Epoch: Calculated based on the training dataset size and batch size.
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  Validation Steps: Calculated based on the validation dataset size and batch size.
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  Model Save
 
10
  - ML
11
  - Ai
12
  ---
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+ Facial Recognition Model
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+
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  Model Information
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+
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  Name: Facial Means
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+
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  Type: Convolutional Neural Network (CNN)
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+
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  Framework: TensorFlow
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+
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  Dataset: Celebrity Faces Dataset
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+
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  Dataset Path: /content/drive/MyDrive/beard_dataset/celb_dataset/
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+
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  Model Save Path: /content/drive/MyDrive/beard_dataset/celebrity_model.h5
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+
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  Image Dimensions: 224 x 224 pixels
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+
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  Batch Size: 32
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  Data Augmentation
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  Rescale: 1./255
 
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  Horizontal Flip: True
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  Validation Split: 20%
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  Model Architecture
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+ Layer (type)
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+ Output Shape Param #
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  ===============================================================
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  conv2d (Conv2D) (None, 222, 222, 32) 896
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  max_pooling2d (MaxPooling2D) (None, 111, 111, 32) 0
 
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  dense (Dense) (None, 128) 11075712
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  dense_1 (Dense) (None, 6) 774
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  ===============================================================
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+
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  Total params: 11,170,734
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  Trainable params: 11,170,734
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  Non-trainable params: 0
 
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  Optimizer: Adam
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  Loss Function: Categorical Crossentropy
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  Metrics: Accuracy
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+
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  Training
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+
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  Epochs: 10
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+
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  Steps per Epoch: Calculated based on the training dataset size and batch size.
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  Validation Steps: Calculated based on the validation dataset size and batch size.
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  Model Save