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This is what the repo says:

>Results >Ariane RISC-V CPU >View the full details of the Ariane experiment on our details page. With this code we are able to get comparable or better results training from scratch as fine-tuning a pre-trained model.

The paper includes a graph showing that it takes longer for Ariane to train without pre-training however the results in the end are the same.

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See their ISPD 2022 paper, which goes into more detail about the value of pre-training (e.g. Figure 7): https://dl.acm.org/doi/pdf/10.1145/3505170.3511478

Sometimes training from scratch is able to match the results of pre-training, given ~5X more time to converge. Other times, though, it never does as well as a pre-trained model, converging to a worse final result.

This isn't too surprising -- the whole point of the method is to be able to learn from experience.

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