Hello! I am trying to train a model to recognize plural and singular nouns; input is a noun and output is either 1 or 2, 1 for singular and 2 for plural. Truth be told, I am not sure entirely how to tackle this… I saw a few tutorials about TF NN and image processing, but I don’t know how does that relate. Every time I try to run model.fit(nouns, labels, epoc=N) it either doesn’t do anything or it fails due to bad input.
The challenges I am facing are as follows: * Can I have a variable sized input? * How can I get the text, stored in a CSV, to a form that can be input into the NN model?
The code I have so far is something like this: “`python model = keras.models.Sequential() model.add(keras.layers.Input(INPUT_LENGTH,)) ## I am padding the string to have this length model.add(keras.layers.Dense(10, activation=’relu’, name=”First_Layer”)) model.add(keras.layers.Dense(2, activation=’relu’, name=”Output_Layer”))
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy') # model.summary() model.fit(nouns_array, labels_array, epochs=10)
I couldn’t find any tutorials or documentation, that I can clearly understand, talking about inputting string to a NN. Any advice or links would be appreciated.
I followed the linked YouTube tutorial to turn the text into tokens and it worked great. I didn’t use the suggested embedded layer and just stuck with the ordinary input dense dense model. Thanks everyone!