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CMU-MOSEI Dataset

This code along with our trained weights reproduces our results on CMU-MOSEI dataset in Table 2 of our paper.

Setup

Install dependencies for CMU-MultimodalSDK

pip install h5py validators tqdm numpy argparse requests colorama

Install library for pretrained BERT model

pip install pytorch_pretrained_bert

Our dependencies

pip install sklearn

Download and preprocess the dataset with the following

python dataset_prep.py --datadir <path/to/CMU_MOSEI>

Generated folder structure (do not modify file names)

CMU_MOSEI/  # based on --datadir argument
    csd/  # can delete this folder to save space
        .csd files
    train/
        .npy files
    val/
        .npy files
    test/
        .npy files

Evaluate

python main_msaf.py --datadir <path/to/CMU_MOSEI> \
--checkpoint checkpoints/msaf_mosei_epoch6.pth

Train

Basic training command

python main_msaf.py --datadir <path/to/CMU_MOSEI> --train

All parameters

usage: main_msaf.py [-h] [--datadir DATADIR] [--lr LR]
                    [--batch_size BATCH_SIZE] [--num_workers NUM_WORKERS]
                    [--epochs EPOCHS] [--checkpoint CHECKPOINT]
                    [--checkpointdir CHECKPOINTDIR] [--no_verbose]
                    [--log_interval LOG_INTERVAL] [--no_save] [--train]