If you view your output as global_bias + phase_adjustment(t) + timeseries_specific_adjustment(t,x), conclusion would be that the last component was not learned. If you start your rnn with zero context, this can mean that your timeseries have no distinguishing features when fed step-by-step, to have non-zero timeseries specific bias (encoded in hidden state). In other cases such features may be missed (try GRU and slower training).