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{
"architecture": {
"base_model": "MobileNetV2",
"input_shape": [
224,
224,
3
]
},
"custom_layers": [
{
"type": "GlobalAveragePooling2D"
},
{
"type": "Dense",
"units": 128,
"activation": "relu"
},
{
"type": "Dropout",
"rate": 0.5
},
{
"type": "Dense",
"units": 1,
"activation": "sigmoid"
}
],
"training": {
"optimizer": "Adam",
"learning_rate": 0.001,
"loss": "binary_crossentropy",
"metrics": [
"accuracy"
]
},
"fine_tuning": {
"unfreeze_from_layer": 100,
"fine_tune_learning_rate": 0.0001
}
} |