Weights not changing

Hello,

I am new to machine learning and am currently trying out different models.

I have noticed the following:

when i train a model such as linear regression, i get the weights (coeff. and intercept) at the end of the training.

Now if i repeat the training and do not change the training data, not even the order, then i get exactly the same weights. I don’t understand why.

Shouldn’t the result be at least slightly different, since the initial weights and the optimization of the weights are not exactly the same?

The same thing happens with other models like boosted trees etc.

Also what i dont understand is the learner not only outputs the weights but also a R^2, how? what data does it use to calculate that? the only input to the learner is training data