Question: Transformer for time series

[jannik-scheider]

Hi,
My problem: I want to determine a value for time t based on variables at time t and their associated time series, i.e. values at time t-1, t-2, and so on.
So for example: I have a dataset with 4 columns which store values for certain sensors (e.g. A,B,C,D). Additionally I have a datetime column. I want that my model predicts the value for sensor A at time t by only looking at Sensor B, C, D time series, so time t, t-1, t-2, t-3 ... . In general when I test my Model I have an input of size [sequence length, variables (without target)] and my output is my target variable, so one value.

I want to implement the whole thing with a transformer. However, when configuring your framework, I specify my Target column and in the relevant columns I also specify my Target column again. If I understand it correctly, the model learns additionally about the history of the target column. However, I do not want this in my example. ( For training I have the information of the target variable of course, but I don't want this information to influence the weights of the model, but only based on the other relevant columns).
Is there a solution to adapt the configuration for a SimpleTransformer, Informer or Crossformer to my mentioned problem?