Hi, I've been trying for a while to use incremental training, but I'm running into quite a few issues. The updates seem to be working fine, as evident from updates containing OOVs, but the performance when using the dynamic suffix array is much inferior (several BLEU points) in comparison to using the regular Moses server on the same dataset and with the same model. In both cases I used a model trained with incremental GIZA, so this seems like an effect of the suffix array rather than a different alignment model. I was not making any updates to the server in these experiments. Could this be a result of a limit on the memory that is used when the suffix array is loaded (my corpus contains 1M sentence pairs)? Any other ideas for the cause of the decrease in performance?
Concerning updates, is there a way to change the incremental GIZA parameters, such as the interpolation parameter gamma? Lastly, when my ini file for loading the server in the suffix array mode contains the complete reordering table of the trained model (rather than the filtered one for the test test), it takes forever to load. Any suggestions? Thanks a lot, Shachar
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