Pneumonia Detection with an accuracy of 91%

Model Architecture:
- model = Sequential()
- model.add(base_model)
- model.add(AveragePooling2D(pool_size=(2, 2), strides=2))
- model.add(Flatten())
- model.add(Dense(256, activation="relu"))
- model.add(Dense(128, activation="relu"))
- model.add(Dense(2, activation="softmax"))
- model.compile(
loss="sparse_categorical_crossentropy",
optimizer=Adam(learning_rate=0.000035),
metrics=["sparse_categorical_accuracy"],
)

Confusion Matrix for the model


model evaluation result:


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