TF IDF will give you the degree of measure of how relevant a document is to your query. owever, to evaluate your IR system you need to use metrics such as - Precision, Recall and F score.
Precision: Out of all the documents that your system retrieves, which ones are relevant? This measures how much noise there is in the output of your IR system.
Recall: Out of all the documents that are relevant, which ones did your system retrieve? This measures how much coverage does your IR system have?
It is possible to get 100% recall all the time by basically retrieving ALL documents from a collection for any query. However, the precision in this case will be very low.
It is possible to get a very high precision by hand modeling an IR system ti produce very accurate results. However, it would produce a very bad recall as there will not be coverage over all the documents.
So we need to measure F score- which is the harmonic mean between Precision and Recall
Check out Chapter 8 of the Stanford IR book.
If you are looking for datasets only here are a few that are relevant: