I am trying fitting several mixed linear models.

 summary(model3 <- lme4::lmer(LPP2POz ~ COND + (COND|ID), data = dataLPP2POz))

whose output is

Error: number of observations (=75) <= number of random effects (=75) for term (COND | ID); the random-effects parameters and the residual variance (or scale parameter) are probably unidentifiable

Can anyone can figure out why this model turns back this error?

Here's the dataset:

> dput(head(dataLPP2POz))
structure(list(ID = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("01", 
"04", "06", "07", "08", "09", "10", "11", "12", "13", "15", "16", 
"17", "18", "19", "21", "22", "23", "25", "27", "28", "30", "44", 
"46", "49"), class = "factor"), GR = c("RP", "RP", "RP", "RP", 
"RP", "RP"), SES = c("V", "V", "V", "V", "V", "V"), COND = structure(c(1L, 
2L, 3L, 1L, 2L, 3L), .Label = c("NEG-CTR", "NEG-NOC", "NEU-NOC"
), class = "factor"), LPP2POz = c(7.91468942320841, 9.94838815736199, 
10.2186482048953, 1.07455889922813, 1.65917850515029, 3.22422743232682
)), row.names = c(NA, 6L), class = "data.frame")