Classification based on spectral library

all pixels are equally probable for your one material.

Usually, you use several endmembers (materials) to train and the unmixing decides how much of each signature is represented in each pixel.
It is also important that the signature and the rasters have the same unit. Your signature is given in radiance? It would be better to have both the signature as well as the rasters in calibrated reflectance (0-1)

Why are your bands called “B1_error”? Seems to be the result of the unmixing already.