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A Large Short-video Recommendation Dataset with Raw Text/Audio/Image/Videos (Talk Invited by DeepMind).

Python 96.16% Jupyter Notebook 2.90% Shell 0.02% Makefile 0.03% Batchfile 0.04% JavaScript 0.60% CSS 0.25%
audio-recommendation foundation-models image-recommendation large large-language-models short-video video video-recommendation text-recommendation video-generation

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microlens's Issues

Crush

cant download, it crush.

[Issue] Problems Encountered Running `run_video.py`

Description

I have successfully downloaded the MicroLens dataset and am currently running the code provided by the authors. However, I've encountered several issues during the execution.

Issues

  1. Clarification Needed on Dataset Selection
    In the file MicroLens/Code/VideoRec/SASRec/run_video.py, there is a line:

    max_video_no = 91717 # 34321 for 10wu, 91717 for 100wu

    I am unsure what "10wu" and "100wu" refer to. Which setting should I use for the MicroLens-100k dataset?

  2. Error Using x3d-s Video Model
    When running the code with the x3d-s video model, strictly following the parameters specified in the paper, the following traceback error occurs:

RuntimeError: input image (T: 5 H: 7 W: 7) smaller than kernel size (kT: 13 kH: 5 kW: 5)

The error points to an issue with the pooling operation in the video model. It seems the input image dimensions are too small for the kernel size. How should I adjust the kernel size or the input dimensions?

  1. Instability in Metrics When Using video-mae-base Model

Using the video-mae-base as the video model, I observed that the learning metrics Hit10 and nDCG10 fluctuate significantly during training, with a trend of occasionally approaching zero. What might be causing this instability, and how can it be resolved?

Request for Assistance

I would appreciate any insights or recommendations on addressing these issues, especially with the right dataset settings for MicroLens-100k, the handling of input dimensions for the x3d-s model, and strategies for stabilizing training metrics with the video-mae-base model.

Thank you very much!

preprocessing

Hi,Thanks to your excellent work!I would like to know how you processed the raw image and text modes to get the.npy file. Can you share the code for the process?

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