MMSRec

Due to a lack of GPU machines, this work has been delayed for several months. As a result, only a limited number of ablation experiments are included in the paper. We plan to supplement with more experiments when resources become available in the future.

Environment

Create virtual environment from configuration file

conda env create --file configs/mmsrec.yml

Activate virtual environment

conda activate mmsrec

Install and download CLIP (used as feature extractor)

sh weights/clip/download.sh

Download Datasets

Pretraining Datasets

1.Webvid

Go to /dataset/webvid/preprocess/ directory

Install git-lfs

sudo apt-get install git-lfs

Download dataset

git lfs clone https://huggingface.co/datasets/iejMac/CLIP-WebVid.git

Extract dataset

sh download.sh

Generate training files

python process_item.py
python process_seq.py

2.MSR-VTT

Go to dataset/msrvtt/preprocess directory

Download dataset

sh download.sh

Generate training files

python process_item.py
python process_seq.py

Recommendation Datasets

1.Amazon

Go to dataset/amazon/preprocess directory

Download dataset (This will download Beauty, Sports, Clothing, and Home datasets. You can modify and adjust according to your needs)

sh download.sh

Scrape image links from the dataset and generate training files

python process_item.py

Feature extraction

python extract_features.py

2.Movielens-1M

Go to dataset/movielens-1m/preprocess directory

Download dataset

sh download.sh

Scrape video data

python download_videos.py

Generate training files

python process_item.py

Feature extraction

python extract_features.py

Quick Start

1.Pretraining

Execute the following command to start pretraining

sh pretrain_webvid.sh

Note: The script assumes each node has 8 GPUs by default. You can modify the following parameter for custom configuration

--nproc_per_node=8 \

The configuration file for pretraining is configs/pretraining/pretrain_webvid.yaml

2.Finetune on Amazon

Finetune the pre-trained model on Amazon

sh finetune_amazon.sh

The configuration file is configs/pretraining/finetune_amazon.yaml

3.Finetune on Movielens-1M

Finetune the pre-trained model on Movielens-1M

sh finetune_movielens.sh

The configuration file is configs/pretraining/finetune_movielens.yaml