Error: $ operator is invalid for atomic vectors using ggploot2

I was wondering if someone can help me. I am running a linear mixed model analyses using the nlme package. The model runs fine but I cant plot the regression lines from the model using ggplot2. I get the error
Error: $ operator is invalid for atomic vectors
my code is as follows
m1<-lme(vis_hits~Group*session+nbacklevel, random=~session|subjno,
data = sampledata,method="ML",na.action=na.omit)

vi■■■■sdata<-sampledata[-which(is.na(sampledata$vis_hits)),]
vis_hits_plot<-ggplot(vi■■■■sdata,aes(session,vis_hits,colour=Group))+
stat_summary(fun.data=mean_se,geom="pointrange")+
stat_summary(aes(y=fitted(m1),linetype=Group),fun=mean,geom="line")

A sample of my data is below

subjno+A1:E303 Group session nbacklevel vis_hits
1 1 1 1 0.83
1 1 1 2 0.5
1 1 1 3 0.33
1 1 1 3
1 1 2 1 0.67
1 1 2 2 0.5
1 1 2 3 0.17
1 1 2 2 0.17
1 1 2 2 0.5
1 1 2 2 0.33
1 1 2 2 0.33
1 1 2 2 0.5
1 1 2 2 0.33
1 1 2 2
1 1 2 1 0.67
1 1 2 2 0.67
1 1 2 3 0.33
1 1 2 3 0.33
1 1 2 3 0.17
1 1 3 1 0.67
1 1 3 2 0.5
1 1 3 2 0.5
1 1 3 2 0.33
1 1 3 2 0.33
1 1 3 2 0.5
1 1 3 2 0.33
1 1 3 2 0.33
1 1 3 2 0.17
1 1 3 2 0.33
1 1 3 2 0.33
1 1 3 2 0.67
1 1 3 3 0.17
1 1 3 3 0.17
1 1 3 3 0.17
1 1 3 3 0.17
1 1 4 1 1
1 1 4 2 1
1 1 4 3 0.5
1 1 4 2 1
1 1 4 3 0.67
1 1 4 3 0.5
1 1 4 2 1
1 1 4 3 0.67
1 1 4 4 0.67
1 1 4 3 0.67
1 1 4 2 0.83
1 1 4 3 1
1 1 4 4 0.67
1 1 5 2 0.83
1 1 5 3 0.33
1 1 5 3 0.33
1 1 6 2 0.83
1 1 6 3 0.5
1 1 6 3 0.67
1 1 6 3 0.17
2 0 1 1 1
2 0 1 2 1
2 0 1 2 1
2 0 2 1 1
2 0 2 2 1
2 0 2 3 0.83
2 0 2 2 1
2 0 2 3 0.83
2 0 2 2 1
2 0 2 2 0.83
2 0 2 2 1
2 0 2 2 1
2 0 2 3 0.83
2 0 2 2 1
2 0 2 3 0.5
2 0 2 2 1
2 0 3 1 1
2 0 3 2 1
2 0 3 3 0.83
2 0 3 2 1
2 0 3 2 1
2 0 3 2 1
2 0 3 2 1
2 0 3 3 0.33
2 0 3 2 0.67
2 0 3 2 1
2 0 3 2 0.83
2 0 3 2 1
2 0 3 3 0.83
2 0 3 2 1
2 0 4 1 1
2 0 4 2 1
2 0 4 3 0.33
2 0 4 2 1
2 0 4 3 0.67
2 0 4 2 1
2 0 4 3 0.67
2 0 4 2 0.5
2 0 4 1 0.83
2 0 4 1 0.83
2 0 4 1 0.83
2 0 4 2 1
2 0 4 3 0.33
2 0 4 2 0.83
2 0 5 2 0.5
2 0 5 1 1
2 0 5 2 0.83
2 0 5 2 0.83
2 0 6 2 1
2 0 6 3 0.67
2 0 6 2 1
2 0 6 3 0.83
2 0 6 3 0.83
3 1 1 1 0.67
3 1 1 2 0.67
3 1 1 3 0.33
3 1 1 3 0.33
3 1 2 1 0.67
3 1 2 2 0.33
3 1 2 1 0.83
3 1 2 2 1
3 1 2 3 0.33
3 1 2 2 0.67
3 1 2 2 0.67
3 1 2 3
3 1 2 2 0.5
3 1 2 2 0.5
3 1 2 2 0.67
3 1 2 2 0.67
3 1 2 2 1
3 1 2 3 0.5
3 1 2 2 0.83
3 1 3 1 0.83
3 1 3 2 0.67
3 1 3 2 0.67
3 1 3 3 0.17
3 1 3 2 1
3 1 3 3 0.5
3 1 3 3 0.67
3 1 3 3 0.5
3 1 3 2 0.83
3 1 3 3 0.33
3 1 3 2 1
3 1 3 3 0.67
3 1 3 3 0.67
3 1 3 3 0.5
3 1 3 3 0.33
3 1 4 1 0.83
3 1 4 2 0.67
3 1 4 3 0.5
3 1 4 2 1
3 1 4 3 0.33
3 1 4 3 0.67
3 1 4 3 0.83
3 1 4 4 0.33
3 1 4 3 0.33
3 1 4 2 0.5
3 1 4 2 1
3 1 4 3 0.33
3 1 4 3 0.17
3 1 4 2 1
3 1 4 3 0.33
3 1 5 2 1
3 1 5 3 0.67
3 1 5 3 0.33
3 1 6 2 0.17
3 1 6 1 1
3 1 6 2 0.83
3 1 6 3 0.83
3 1 6 4 0.17
3 1 6 4 0.5
4 0 1 1 1
4 0 1 2 0.5
4 0 1 2 0.5
4 0 2 1 1
4 0 2 2 0.5
4 0 2 2 0.5
4 0 2 2 1
4 0 2 3 0.5
4 0 2 3 0.67
4 0 2 3 0.33
4 0 2 3 0.33
4 0 2 3 0.5
4 0 2 3 0.17
4 0 2 3 0.67
4 0 2 3 0.33
4 0 2 3 0.67
4 0 3 1 1
4 0 3 2 1
4 0 3 3 0.5
4 0 3 3 0.5
4 0 3 2 0.67
4 0 3 2 0.67
4 0 3 2 0.67
4 0 3 2 0.67
4 0 3 2 0.67
4 0 3 2 0.33
4 0 3 2 0.5
4 0 3 2 0.17
4 0 3 3 0.33
4 0 4 1 1
4 0 4 2 0.67
4 0 4 2 0.67
4 0 4 3 0.33
4 0 4 3 0.5
4 0 4 2 0.5
4 0 4 2 0.5
4 0 4 2 0.83
4 0 4 3 0.17
4 0 4 2 0.5
4 0 4 2 0.33
4 0 4 1 1
4 0 4 2 0.5
4 0 4 2 1
4 0 5 1 1
4 0 5 2 1
4 0 5 3 0.33
4 0 5 2 0.5
4 0 6 2 0.5
4 0 6 2 0.5
4 0 6 2 0.5
4 0 6 3
6 0 1 1 1
6 0 1 2 1
6 0 1 3 0.67
6 0 1 2 0.83
6 0 2 1 1
6 0 2 2 1
6 0 2 3 0.17
6 0 2 2 1
6 0 2 3 0.67
6 0 2 3 0.83
6 0 2 3 0.67
6 0 2 2 1
6 0 2 3 1
6 0 2 4 0.5
6 0 3 1 1
6 0 3 2 1
6 0 3 3 0.5
6 0 3 2 1
6 0 3 3 0.67
6 0 3 3 0.5
6 0 3 2 1
6 0 3 3 0.67
6 0 3 4 0.67
6 0 3 3 0.67
6 0 3 2 0.83
6 0 3 3 1
6 0 3 4 0.67
6 0 4 2 1
6 0 4 3 0.67
6 0 4 3 0.67
6 0 4 3 1
6 0 4 4 0.33
6 0 4 3 0.67
6 0 4 3 0.83
6 0 4 2 1
6 0 4 3 1
6 0 4 4 0.67
6 0 4 3 1
6 0 4 4 0.5
6 0 4 3 0.67
6 0 5 2 1
6 0 5 3 1
6 0 5 4 0.5
6 0 6 2 0.83
6 0 6 3 1
6 0 6 4 0.83
6 0 6 4 0.83
7 0 1 1 0.67
7 0 1 1 0.83
7 0 1 2 0.33
7 0 2 1 0.67
7 0 2 1 1
7 0 2 2 0.33
7 0 2 1 0.83
7 0 2 2 0.33
7 0 2 2 0.5
7 0 2 1 0.83
7 0 2 1 1
7 0 2 2 0.67
7 0 3 1 1
7 0 3 2 0.33
7 0 3 2 0.5
7 0 3 2 0.67
7 0 3 2 0.83
7 0 3 1 0.83
7 0 3 2 0.67
7 0 3 1 0.83
7 0 3 2 0.67
7 0 4 2 0.67
7 0 4 1 0.83
7 0 4 2 0.67
7 0 4 2 0.17
7 0 4 1 0.83
7 0 4 2 0.17
7 0 4 1 0.83
7 0 4 2 0.5
7 0 4 2 0.5
7 0 4 1 0.67
7 0 5 2 1
7 0 5 3 0.33
7 0 5 2 0.83
7 0 6 2 0.5
7 0 6 2 0.67
7 0 6 3 0.17
7 0 6 2 0.33