TitleStylist_Zh

The following Repo is Hard fork of TitleStylist

The code uses the Chinese generation model ProphetNet-Dialog-Zh for initializing the base encoder-decoder architecture.

Model uses ideas from TitleStylist (Style Layer Normalization and Style-Guided Encoder Attention) with base pretrained model as ProphetNet-Dialog-Zh with Masked Sequence to Sequence Pretraining inspire from MASS

• Pretrained ProphetNet-Dialog-Zh

Requirements

Python packages

• Pytorch
• fairseq
• blingfire

In order to install them, you can run this command:

pip install -r requirements.txt

Bash commands

In order to evaluate the generated headlines by ROUGE scores, you need to install the "files2rouge" package. To do so, run the following commands (provided by this repository):

pip install -U git+https://github.com/pltrdy/pyrouge
git clone https://github.com/pltrdy/files2rouge.git     
cd files2rouge
python setup_rouge.py
python setup.py install

Usage

1. All data including the combination of CNN and NYT article and headline pairs, and the three style-specific corpora (humor, romance, and clickbait) mentioned in the paper have been placed in the folder "data".

2. Please download the pretrained model parameters of ProphetNet-Dialog-Zh from this link, unzip it, and put the unzipped files into the folder "pretrained_model/prophet_zh/".

cd pretrained_model
mkdir prophet_zh
wget https://msraprophetnet.blob.core.windows.net/prophetnet/release_checkpoints/prophetnet_dialog_zh.pt
tar -xvzf prophetnet_dialog_zh.pt
cd ..

3. To train a headline generation model that can simultaneously generated a facutal and a stylistic headline, you can run the following command:

./train_mix_Zh_News_X.sh --style ZH_poem

Here the arugment YOUR_TARGET_STYLE specifies any style you would like to have, in this paper, we provide three options: humor, romance, clickbait.

After running this command, the trained model parameters will be saved into the folder "tmp/exp".

4. If you want to evaluate the trained model and generate headlines (both factual and stylistic) using this model, please run the following command:

./evaluate_mix_Zh_News_X.sh --style style ZH_poem --model_dir MODEL_STORED_DIRCTORY

In this command, the argument MODEL_STORED_DIRCTORY specifies the directory which stores the trained model.