How to get the most out of Titan Optimise

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Garbage in, garbage out. Quality in, quality out.

The Titan-compressed models are produced from the models which you feed in from the command line. The better the model you put in the system, the better the model you will get out. For a lot of cases, an ELECTRA Large model will be the best choice.

If you put an already very small model into TitanML to be compressed even further, results will not be nearly as good as if you started with a large, high-accuracy model.

Whilst you might see a drop-off in performance relative to your input model, the output model will substantially outperform a directly-finetuned model of a similar size. Rather than comparing the accuracy of the smaller model with the bigger input model, compare the accuracy of the smaller model with a model of a similar resource profile. TitanML models typically perform much better!

The same applies to datasets: the higher the quality and size of your input dataset, the better the TitanML models will be.