Train 1-dimensional Convolution Network with Glove Embeddings

Train 1-dimensional Convolution Network using keras on the given dataset using Glove Embeddings available here - (https://nlp.stanford.edu/projects/glove/)

Arguments

data	the sentiment140 train dataset with text for text of the tweet and polarity for polarity.
max_words	Maximum number of words to consider using word frequency measure.
maxlen	Maximum length of a sequence.
embedding_dim	Output dimension of the embedding layer.
epochs	Number of epochs to run the training for.
batch_size	Batch Size for model fitting.
validation_split	Split ratio for validation
conv1d_filters	Number of filters i.e. output dimension for convolution layers.
conv1d_kernel_size	Window size for convolution layers.
conv1d_pool_size	Pool size for max pooling.
seed	Seed for shuffling training data.
glove_file_path	File path location for glove embeddings.
model_save_path	File path location for saving model.

Value

plot of the training operation showing train vs validation loss and accuracy.

Examples

# NOT RUN {
  data(sentiment140_train)
  train_conv1d_with_glove(glove_file_path = "./glove.6B.100d.txt",
                          model_save_path = "./train_glove_conv_1d.h5")
# }