Finding covariance in a lmer mixed effects model

I am having difficulty finding the covariance for the random effects
in a mixed effects model. I fit this model: fm1 <-  lmer(fpg ~ 1 +
time + (1|ID) + (0+time|ID),fpg_lme)

and want to find the covariance between the time and intercept random
effects.

I tried using VarCorr (see below) but it does not give the covariance
or correlation between the random effects. Am I doing something
wrong?

Thanks,
Kurt

summary(fm1)

Linear mixed model fit by REML
Formula: fpg ~ 1 + time + (1 | ID) + (0 + time | ID)
   Data: fpg_lme
     AIC     BIC  logLik deviance REMLdev
 1499289 1499339 -749639  1499259 1499279
Random effects:
 Groups   Name        Variance   Std.Dev.
 ID       (Intercept) 1.0396e+03 32.2435465
 ID       time        1.2199e-05  0.0034926
 Residual             1.1241e+02 10.6025764
Number of obs: 174042, groups: ID, 55526

Fixed effects:
             Estimate Std. Error t value
(Intercept) 1.108e+02  1.421e-01   779.9
time        2.106e-03  6.678e-05    31.5

Correlation of Fixed Effects:
     (Intr)
time -0.163

VarCorr(fm1)

$ID
            (Intercept)
(Intercept)    1039.646
attr(,"stddev")
(Intercept)
   32.24355
attr(,"correlation")
            (Intercept)
(Intercept)           1

$ID
             time
time 1.219857e-05
attr(,"stddev")
       time
0.003492645
attr(,"correlation")
     time
time    1

attr(,"sc")
sigmaREML
 10.60258