Analyzing IMDB Data in Keras - Solution

4. Building the model architecture

Build a model here using sequential. Feel free to experiment with different layers and sizes! Also, experiment adding dropout to reduce overfitting.



In [ ]:

    
# Building the model architecture with one layer of length 100
model = Sequential()
model.add(Dense(512, activation='relu', input_dim=1000))
model.add(Dropout(0.5))
model.add(Dense(num_classes, activation='softmax'))
model.summary()

# Compiling the model using categorical_crossentropy loss, and rmsprop optimizer.
model.compile(loss='categorical_crossentropy',
              optimizer='rmsprop',
              metrics=['accuracy'])

5. Training the model

Run the model here. Experiment with different batch_size, and number of epochs!



In [ ]:

    
# Running and evaluating the model
hist = model.fit(x_train, y_train,
          batch_size=32,
          epochs=10,
          validation_data=(x_test, y_test), 
          verbose=2)