Inconsistent Training Results in Document AI Splitter

[tootsieroll]

Hi Google Support,

I've been training a model in Document AI Splitter, but I'm noticing inconsistent results even when using the same training data. Specifically, when I train a model for the first time, I get good results with a high confidence threshold. However, when I retrain a new model with the exact same data (without making any updates to the model or dataset), the results vary significantly, sometimes with lower confidence scores.

I expected that retraining with the same data would yield similar or identical results, but that doesn’t seem to be the case. Could you provide insights into why this is happening? Are there factors influencing variability in model training that I should be aware of?

Any guidance on ensuring more consistent results would be greatly appreciated.

Thanks.