We examine the capacity of beamforming over a Multi-Input/Single-Output block Rayleigh fading channel with finite training for channel estimation and limited feedback. A fixed-length packet is assumed, which is spanned by T training symbols, B feedback bits, and the data symbols. The training symbols are used to obtain a Minimum Mean Squared Error (MMSE) estimate of the channel vector. Given this estimate, the receiver selects a transmit beamforming vector from a codebook containing 2B i.i.d. random vectors, and relays the corresponding B bits back to the transmitter. We derive bounds on the capacity and show that for a large number of transmit antennas Nt, the optimal T and B, which maximize the bounds, are approximately equal and both increase as Nt/log Nt. We conclude that with limited training and feedback, the optimal number of antennas to activate also increases as N t/log Nt.