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"Unsupervised Paraphrase Generation using Pre-trained Language Model."

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Unsupervised Paraphrase Generation

Unsupervised Paraphrase Generation using Pre-trained Language Model (paper)

We use Huggingface transformers 3.0.2, pytorch 1.6.0, and python 3.8 and only support GPU version Please check environment.yml for detail.

How to run

  1. Environment setup

    conda env create -f environment.yml
    conda activate huggingface
    
  2. Download dataset

    Please check the data/README.md for how to download and preprocess dataset

  3. Training (Finetune GPT-2)

    bash run_train.sh {GPU_ID} {TAG}
    

    For example,

    bash run_train.sh "0,1,2,3" "training_with_4_GPUs" 
    
  4. Evaluation

    bash run_eval.sh {GPU_ID} {TAG} {CHECKPOINT_DIR}
    

    For example,

    bash run_eval.sh 0 "training_with_4_GPUs" "checkpoints/gpt2-medium_training_with_4_GPUs_2020-08-28_12:34:56/checkpoint-3000/"
    

Notice

  • I don't reproduce the results yet. Please feel free to comment for reproduction by creating an issue or a pull request.
  • The experiment on QQP dataset is implemented now. Experiments on SST-2 will be added later.

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