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meta-learning experiments
I believe there is a bug at "eval2.py" file. RMSprop run (lines 50-60) is done updating the embedding weights after one iteration, and the converged results is just +- the learning rate. I believe it happens due to the embedding weights initialization to zero (lines 20-21). Comment these lines out gives much better loss.