swabhs/open-sesame

Dimensionality Mismatch While Trying to Run Prediction

savan77 opened this issue · 7 comments

Hi,

Thanks for this work. I was trying to test on unannoatated data using the predict model. But, when I try to run the targetid, it throws following error. I think this has been reported before but not sure how to solve this. Also, I just downloaded the code and model so they are up to date.
Dimensions of lookup parameter /_0 lookup up from file ({100,400574}) do not match parameters to be populated ({100,400001})
Thanks

similar problem. I ran python -m sesame.targetid --mode predict --model_name fn1.7-pretrained-targetid --raw_input sentences.txt and get RuntimeError: Dimensions of lookup parameter /_0 lookup up from file ({100,400574}) do not match parameters to be populated ({100,400000})

heeh commented

Same error here. Did anyone resolve this issue?
RuntimeError: Dimensions of lookup parameter /_0 lookup up from file ({100,400574}) do not match parameters to be populated ({100,410050})

Same error here. Did anyone resolve this issue?
RuntimeError: Dimensions of lookup parameter /_0 lookup up from file ({100,400574}) do not match parameters to be populated ({100,410050})

I've also met this problem, and it seems that the glove embeddings we use are not same as their pretrained model. Retrain this model on framenet data can solve this problem, but i got 'nan gradient' during train stage. Now i decided to ask them for their version of GloVe embeddings.

heeh commented

@Zce1112zslx Thank you for figuring this out. I finally understand what's going on here.

Facing the same issue. @heeh @Zce1112zslx, Can you please drop a note when it works for you?

@swabhs @sammthomson Would really appreciate your help!

Same error here. Did anyone resolve this issue?
RuntimeError: Dimensions of lookup parameter /_0 lookup up from file ({100,400574}) do not match parameters to be populated ({100,410050})

I've also met this problem, and it seems that the glove embeddings we use are not same as their pretrained model. Retrain this model on framenet data can solve this problem, but i got 'nan gradient' during train stage. Now i decided to ask them for their version of GloVe embeddings.

Hi, same issue!
Have you obtained the GloVe embeddings?