embedding = {'type': args.embedding_type, 'path': args.embedding_path}
if args.model == 'sentence_pair':
reader = ReadData(path_file=args.dataset,
embedding_config=embedding,
data_shape=inputs,
train_val_split=args.train_val_split,
sentence_pair=True)
else:
reader = ReadData(path_file=args.dataset,
embedding_config=embedding,
data_shape=inputs,
train_val_split=args.train_val_split,
sentence_pair=False)
print('Reading Validation Data ..')
val_x, val_y = reader.read_val()
train_generator = reader.generator()
log_dir = args.model
logging = TrainValTensorBoard(log_dir=log_dir)
checkpoint = ModelCheckpoint(os.path.join(
log_dir, 'ep{epoch:03d}-val_loss{val_loss:.3f}-val_acc{val_acc:.3f}.h5'),
monitor='val_loss',
save_weights_only=True,
save_best_only=True,
period=1)
reduce_lr = ReduceLROnPlateau(monitor='val_loss',
