The code for fitting the model is as follows:
# Fit model
model_one <- model %>% fit(train_x, train_y,
epochs = 10,
batch_size = 128,
validation_split = 0.2)
For fitting the model, we will make use of a 20% validation split, which uses 20,000 movie review data from training data for building the model. The remaining 5,000 movie review training data is used for assessing validation in the form of loss and accuracy. We run 10 epochs with a batch size of 128.
When using a validation split, it is important to note that, with 20%, it uses the first 80% of the training data for training and the last 20% of the training data for validation. Thus, if the first 50% of the review data was negative and the last 50% was positive, the 20% validation split will cause model validation to be based only on positive reviews. Therefore, before using a validation split, we must verify that this is not the case; otherwise, it will introduce significant bias.