How do you validate a large video dataset before training?

I am comparing approaches for validating a large video dataset before training a video or vision-language model. The checks I am considering include: Metadata completeness Duplicate and near-duplicate detection Caption and transcript alignment Creator or channel-level train/test splits Language balance Temporal distribution Source provenance For teams using PyTorch Datasets or DataLoaders, which checks have provided the most practical value before the first training run? I am especially int...