Pytorch-BPR

Note that I use the two sub datasets provided by Xiangnan's repo. Another pytorch NCF implementaion can be found at this repo.

I utilized a factor number 32, and posted the results in the NCF paper and this implementation here. Since there is no specific numbers in their paper, I found this implementation achieved a better performance than the original curve. Moreover, the batch_size is not very sensitive with the final model performance.

Models	MovieLens HR@10	MovieLens NDCG@10	Pinterest HR@10	Pinterest NDCG@10
pytorch-BPR	0.700	0.418	0.877	0.551

The requirements are as follows:

* python==3.6
* pandas==0.24.2
* numpy==1.16.2
* pytorch==1.0.1
* tensorboardX==1.6 (mainly useful when you want to visulize the loss, see https://github.com/lanpa/tensorboard-pytorch)

Example to run:

python main.py --factor_num=16 --lamda=0.001