Make summary output of lmer model use the actual names for the factor levels

Question

Output of summary() changes the names of my factor levels so that I have no idea which effect corresponds to which level in my data. For example, it will change levels of the factor "hemisphere" from (lh, rh) to (hemi1, hemi2). This becomes a problem for factors with 10+ levels.

Here is a reproducible example:

library(lmerTest)

# Set the seed for reproducibility
set.seed(42)

# Define the levels for each column
subjects <- 1:5
hemispheres <- c("lh", "rh")
groups <- c("Control", "Treatment")
labels <- paste0("label", 1:3)

# Create an empty dataframe with the specified columns
df <- data.frame(subject = integer(),
                 hemisphere = character(),
                 label = character(),
                 y = double(),
                 group = character(),
                 stringsAsFactors = FALSE)

# Populate the dataframe with random values
for (sub in subjects) {
  grp <- sample(groups, 1)  # Assign each subject to one group randomly
  for (hemi in hemispheres) {
    for (lbl in labels) {
      y <- rnorm(n = 1, mean = 0, sd = 0.2)
      row <- data.frame(subject = sub,
                        hemisphere = hemi,
                        label = lbl,
                        group = grp,
                        y = y)
      df <- rbind(df, row)
    }
  }
}

# Print the first 5 rows of the dataframe
head(df)

# Run mixed effects model
mod_lme <- lmerTest::lmer(y ~ group*hemisphere*label + (1|subject/hemisphere), data = df)
summary(mod_lme)

And got this as part of the output:

I expected the leftmost column to use the names of factor levels from my actual data: e.g. "Treatment" instead of "group1", etc.

How can I make the summary() function use the actual names from the data?

Edit: Tried update.packages() to see if it was an outdated package issue, but that didn't work. Also my R version is 4.2.3 and it's aarch64-apple-darwin20.