This repository contains PyTorch evaluation code, training code and pretrained models for Collaborative Filtering with Contrastive Learning.
For details see Collaborative Filtering with Contrastive Learning by Hawon Jeong, Saemee Choi, Sohyun Jeong.
To run the code, you probably need to add datasets in data/dataset/ and run following ipynb.
notebooks/store_features_task1.ipynb
notebooks/store_features_task2.ipynb
python train.py --gpu_ids 1 --dataset task1
python train.py --gpu_ids 1 --dataset task2
BatchSize | Epochs | Task | |
---|---|---|---|
WCL | 256 | 20 | task1 |
WCL | 256 | 20 | task2 |
notebooks/DM_visualize_representation_sample_label.ipynb
notebooks/DM_visualize_representation_without_label.ipynb
/baselines/task1_vanilla_cf.ipynb
/baselines/task2_vanilla_cf.ipynb
If you want to test the pretained model, please download the weights from the link above, and move it to the checkpoints folder (create one if you don't have .checkpoints/ directory).