Quantify the effectiveness of baseline correction in Raman spectra
Could you also mention the correction method? Your auto-fluorescence background is really huge and your signal to noise ratio is low. One of the most cited methods in automated background correction is indeed based on polynomial fitting, albeit little but more sophisticated than just least square fitting. This article is worth reading.

Automated Method for Subtraction of Fluorescence from Biological Raman Spectra
https://journals.sagepub.com/doi/abs/10.1366/000370203322554518



Another simple option is that you can choose a spectral range where to apply a polynomial baseline. Say from 0 to 1200 you apply a polynomial of degree 5, but 1200 onward you choose polynomial of degree 6. However, you have thousands of spectra and it is not clear whether your background shape is similar in each case or not.

Addendum:  I am afraid there is no solid way to compare the baseline correction approaches. The reason is that you do not know the "true" model of the autofluorescence. This is also stated by Ed in comments. He is a leading spectroscopist. In such cases, you should simulate a baseline like these authors and do a comparison. Make a synthetic baseline by polynomials with say n=5, make it more complicated by mixing certain regions with polynomial  n=6, 3, 2, and then try your approaches. Don't add any peaks to the baseline, and just check which technique is showing least residuals. Is there a trend in the residuals? The trend is also important. The residuals should be scattered. What technique did you use in your case?

Alternatively, you can try a known fluorescent compound, Rhodamine G, and collect a fluorescence spectrum. In this case you will know the true shape of the spectrum. Use that as a true model and try your baseline corrections.

One general advice given to us by a professor, who was an author of Raman spectroscopy monograph, was that a better and better fit does not indicate reality. The model may be completely wrong but may have a correlation coefficient close to unity. Thus fitting a polynomial or any experimental baseline correction is just a utilitarian approach, which is changing the aesthetics and cosmetic appearance of a Raman spectrum. There is nothing fundamental going on.