I’ve been experimenting with OpenNMT-tf with my own data, which are a series of numbers as source data and word sentences as the target. The corpus is about 20,000 lines long each, of generally uneven length.
When I run
onmt-main infer --config config/opennmt-defaults.yml config/data/toy-ende.yml --features_file data/toy-ende/src-test.txt, using a src-test file of new inputs, it repeats the same output over and over as the results, which is a seemingly random sentence (one that is present in the target training data). What I was hoping for from the inference process was to generate predictions that were different from the training data, a mishmash of new sentences (of likely varying levels of sense).
I’m running the NMTBig model, with 200000 steps. The beam is 12, learning 1.0, decay rate 0.7, batch size 64, infer batch size 30.
Am I doing something wrong here which is resulting in these repeated results? And can anyone suggest what I can do to get my desired results?