The acceptance rate is higher than expected. During tuning, the sampler tries to select sampling parameters that will achieve certain performance (e.g., proportion of proposals accepted). The lower-than-expected acceptance rate suggests that the sampling was not as efficient as it could have been (which is consistent with the lower-than-expected number of effective samples), but this is probably fine. If you were run this “for real” (e.g., in production, need to make this inference many times, etc.), you might want to improve the efficiency.