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[CIKM'22 Workshop(EvalRS)] Item-based Variational Auto-encoder for Fair Music Recommendation

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EvalRS-CIKM-2022

This is a repository of team ML for the EvalRS Data Challenge. We will update the readme and instructions as soon as possible.

Getting Started

  • Environment: AWS Deep Learning AMI GPU PyTorch 1.12.1 (Amazon Linux 2) with p3.2xlarge instance.
  • upload upload.env
  1. Activate pre-built pytorch environment

    source activate pytorch
    
  2. Install all dependencies.

    pip install -r requirements.txt
    
  3. Run the following command to run our submission

    python submission.py --gpu 0 --model_type VAE --lr 1e-3 --epoch 10 --beta 0.0001 --use_group --use_ensemble --gamma 0.003
    
  4. If you want to see best accuracy model reported on paper run

    python submission.py --gpu 0 model_type VAE --lr 1e-3 --epoch 5 --dim 500
    

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[CIKM'22 Workshop(EvalRS)] Item-based Variational Auto-encoder for Fair Music Recommendation

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