i wanted to learn more about exposure bias mitigation in language models and came across ReMask. it's a neat idea, and i wanted to give it a go.
- during training, the model processes input sequences twice - once with the full sequence & once with masked sequence.
- computes model outputs for both.
- divergence loss is computed as the average of forward and backward KL divergences.
- final loss is a weighted sum of the cross entropy losses and the divergence loss.
impl on github
<|user|>
Could Moulin Rouge have been hypothetically used as Spain's Spanish American War triage center?
<|logic|>
The Moulin Rouge cabaret in France had a capacity of 850 people. Spain had 700-800 injured during Spanish American War.
<|answer|>
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