dt %>%
  arrange(label) %>%
  group_by(label) %>%
  mutate(total = n(),
         percent = sum(match == 1) /total)

# A tibble: 10 x 6
# Groups:   label [6]
      id label predicted match total percent
   <dbl> <dbl>     <dbl> <dbl> <int>   <dbl>
 1     3     1         1     1     3   0.667
 2     8     1         1     1     3   0.667
 3    10     1         4     0     3   0.667
 4     6     2         2     1     1   1
 5     7     3         3     1     1   1
 6     5     4         2     0     1   0
 7     2     5         5     1     2   0.5
 8     4     5         3     0     2   0.5
 9     1     6         6     1     2   0.5
10     9     6         4     0     2   0.5