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I trained a rank 40 model on the movielens data, but cannot retrieve the weights from the trained model with gd_mf_weights. I'm following the syntax from the matrix factorization example but it is giving me errors. Any advice?
WARNING: model file has set of {-q, --cubic, --interactions} settings stored, but they'll be OVERRIDEN by set of {-q, --cubic, --interactions} settings from command line.
creating quadratic features for pairs: ui
finished run
number of examples = 0
weighted example sum = 0
weighted label sum = 0
average loss = -nan
total feature number = 0
terminate called after throwing an instance of 'boost::exception_detail::clone_impl<boost::exception_detail::error_info_injectorboost::program_options::multiple_occurrences >'
what(): option '--rank' cannot be specified more than once
Aborted (core dumped)
If I just run it without specifying rank and interaction variables, it doesn't return the same trained model, since the parameters displayed are different from before.
library/gd_mf_weights -I train.vw -O '/data/home/mlteam/notebooks/Recommenders-master/notebooks/Outputs/movielens' --vwparams '-i movielens.reg'
creating quadratic features for pairs: ui
Num weight bits = 18
learning rate = 10
initial_t = 1
power_t = 0.5
using no cache
Reading datafile =
num sources = 0
Segmentation fault (core dumped)
If I run weights generation with the entire set of model training parameters, it just ignores my extra parameters (and finishes much faster than 50 passes would take) and returns same weights from a randomly initiated rank 40 model. library/gd_mf_weights -I train.vw -0 '/data/home/mlteam/notebooks/Recommenders-master/notebooks/Outputs/movielens' --vwparams '--rank 40 -q ui --l2 0.1 --learning_rate 0.015 --decay_learning_rate 0.97 --power_t 0 --passes 50 --cache_file movielens.cache -f movielens.reg -d train.vw'
The text was updated successfully, but these errors were encountered:
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I trained a rank 40 model on the movielens data, but cannot retrieve the weights from the trained model with gd_mf_weights. I'm following the syntax from the matrix factorization example but it is giving me errors. Any advice?
Model training call:
vw --rank 40 -q ui --l2 0.1 --learning_rate 0.015 --decay_learning_rate 0.97 --power_t 0 --passes 50 --cache_file movielens.cache -f movielens.reg -d train.vw
Weights generating call:
library/gd_mf_weights -I train.vw -O '/data/home/mlteam/notebooks/Recommenders-master/notebooks/Outputs/movielens' --vwparams '-q ui --rank 40 -i movielens.reg'
Error:
If I just run it without specifying rank and interaction variables, it doesn't return the same trained model, since the parameters displayed are different from before.
If I run weights generation with the entire set of model training parameters, it just ignores my extra parameters (and finishes much faster than 50 passes would take) and returns same weights from a randomly initiated rank 40 model.
library/gd_mf_weights -I train.vw -0 '/data/home/mlteam/notebooks/Recommenders-master/notebooks/Outputs/movielens' --vwparams '--rank 40 -q ui --l2 0.1 --learning_rate 0.015 --decay_learning_rate 0.97 --power_t 0 --passes 50 --cache_file movielens.cache -f movielens.reg -d train.vw'
The text was updated successfully, but these errors were encountered: