Chinese News Summarization

This project aims to generate titles for Chinese news using mT5-small model.

Prerequisites

• Python 3.9

Repository Structure

• requirements.txt: List of Python packages required for this project.
• download.sh: Script download training data and a pre-trained model.
• download.py: Script called by download.sh to handle the downloading process.
• run.sh: Bash script to run the inference code.
• inference.py: Python script that performs inference using the pre-trained model.
• train_src: Folder containing additional resources for training models on your own.
• report.pdf: Explanations of the hyperparameter sweep and generation strategies.

Setup

Step 1: Clone the Repository

git clone https://github.com/Hannibal0420/Chinese-News-Summarization.git
cd Chinese-News-Summarization

Step 2: Install Dependencies

Install the required Python packages and inference model using the following command:

pip install -r requirements.txt
bash ./download.sh

Run Inference

To run the inference code, execute the run.sh script with the following arguments:

• ${1}: Path to input.jsonl
• ${2}: Path to output.jsonl

bash ./run.sh /path/to/input.jsonl /path/to/output.jsonl

Note: Make sure to replace /path/to/input.jsonl and /path/to/output.jsonl with the actual paths to your files. To use the example code in this repo, you can run as below.

./run.sh ./data/public.jsonl ./output.jsonl

Train Your Own Model

In the train_src folder, you can fine-tune existing models or train from scratch and track the process with Weights & Biases toolkits. These codes are modified from this source:

• Summarization: Transformers model on a extractive and abstractive summarization dataset, like CNN/DailyMail

License

This project is licensed under the MIT License - see the LICENSE.md file for details.