This is a bit pedantic, but FID score wouldn't really be a viable metric for best of n selection since it's a metric that's only computable for distributions of samples. FID score is also pretty high variance for small sample sizes, so you need a lot of samples to compute a meaningful FID score.
Better metrics (assuming goal is text->image) would be some sort of inception score or CLIP-based text matching score. These metrics are computable on single samples.
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This is a bit pedantic, but FID score wouldn't really be a viable metric for best of n selection since it's a metric that's only computable for distributions of samples. FID score is also pretty high variance for small sample sizes, so you need a lot of samples to compute a meaningful FID score.
Better metrics (assuming goal is text->image) would be some sort of inception score or CLIP-based text matching score. These metrics are computable on single samples.