kuenm_feval and summary not running/running slowly

[leibar4]

Can anyone see anything wrong with my script? kuenm_feval is stuck on 6% for hours, I'm not sure if it's stuck or just running slowly. Either way it's a bit frustrating and I can't afford to spend too long waiting it out. 17 Final models were produced. Additionally, the summary of results also does not work.
nayaur_occ_kuenm.csv
nayaur_ind.csv
nayaur_train.csv
nayaur_test.csv
nayaur_joint.csv

##. Set the working directory --------------------------------------------

wd <- "/Users/apple/Downloads/kuenm/nayaur"
setwd(wd)
get(wd)

#1. Packages & libraries -------------------------------------------------

packages <- c("devtools", "kuenm", "NCmisc")

installed_packages <- packages %in% rownames(installed.packages())
if (any(installed_packages == FALSE)) {install.packages(packages[!installed_packages])}
sapply(packages, require, character.only = TRUE)

If error with installing and loading kuenm:

if(!require(kuenm)){devtools::install_github("marlonecobos/kuenm")}
library(kuenm)

#2. Import data --------------------------------------------

nayaur_occurrence <- read.csv(file = "nayaur_occ_kuenm.csv")

#3. Run maxent via kuenm --------------------------------------------

#subset occ data

kuenm_occsplit(nayaur_occurrence, train.proportion = 0.75, method = "random",
save = TRUE, name = "nayaur")

#Workflow Recording
{

Preparing variables to be used in arguments

file_name <- "nayaur_enm_process"
kuenm_start(file.name = file_name)
}
#Calibration of models
{
#Creation of candidate models
{

# Variables with information to be used as arguments.

occ_joint <- "nayaur_joint.csv"
occ_tra <- "nayaur_train.csv"
M_var_dir <- "M_variables"
batch_cal <- "Candidate_Models"
out_dir <- "Candidate_models"
reg_mult <- c(seq(0.1, 1, 0.1), seq(2, 15, 1))
f_clas <- "all"
args <- "togglelayertype=t" # e.g., "maximumbackground=20000" for increasing the number of pixels in the background or
# note that some arguments are fixed in the function and should not be changed
maxent_path <- wd
wait <- TRUE
run <- TRUE

#Model creation
kuenm_cal(occ.joint = occ_joint, occ.tra = occ_tra, M.var.dir = M_var_dir, batch = batch_cal,
          out.dir = out_dir, reg.mult = reg_mult, f.clas = f_clas, args = args,
          maxent.path = maxent_path, wait = wait, run = run)

}
#Evaluation and selection of best models
{

occ_test <- "nayaur_test.csv"
out_eval <- "Calibration_results"
threshold <- 5
rand_percent <- 50
iterations <- 500
kept <- TRUE
selection <- "OR_AICc"
paral_proc <- TRUE # make this true to perform pROC calculations in parallel, recommended
# only if a powerful computer is used (see function's help)
# Note, some of the variables used here as arguments were already created for previous function

cal_eval <- kuenm_ceval(path = out_dir, occ.joint = occ_joint, occ.tra = occ_tra, occ.test = occ_test, 
                        batch = batch_cal, out.eval = out_eval, threshold = threshold, 
                        rand.percent = rand_percent, iterations = iterations, kept = kept, 
                        selection = selection, parallel.proc = paral_proc)

}
}
#Final model creation
{

batch_fin <- "Final_Models"
mod_dir <- "Final_models"
rep_n <- 10
rep_type <- "Bootstrap"
jackknife <- TRUE
G_var_dir <- "G_variables"
out_format <- "logistic"
project <- FALSE
ext_type <- "ext"
write_mess <- FALSE
write_clamp <- FALSE
wait1 <- TRUE
run1 <- TRUE
args <- "togglelayertype=t" # e.g., "maximumbackground=20000" for increasing the number of pixels in the background or

"outputgrids=false" which avoids writing grids of replicated models and only writes the

summary of them (e.g., average, median, etc.) when rep.n > 1

note that some arguments are fixed in the function and should not be changed

Again, some of the variables used here as arguments were already created for previous functions

kuenm_mod(occ.joint = occ_joint, M.var.dir = M_var_dir, out.eval = out_eval, batch = batch_fin,
rep.n = rep_n, rep.type = rep_type, jackknife = jackknife, out.dir = mod_dir,
out.format = out_format, project = project, G.var.dir = G_var_dir, ext.type = ext_type,
write.mess = write_mess, write.clamp = write_clamp, maxent.path = maxent_path, args = args,
wait = wait1, run = run1)
}
#Final model evaluation
{help(kuenm_feval)

occ_ind <- "nayaur_ind.csv"
replicates <- TRUE
out_feval <- "Final_models_evaluation"

Most of the variables used here as arguments were already created for previous functions

fin_eval <- kuenm_feval(path = mod_dir, occ.joint = occ_joint, occ.ind = occ_ind, replicates = replicates,
out.eval = out_feval, threshold = threshold, rand.percent = rand_percent,
iterations = iterations, parallel.proc = paral_proc)
}
#Summary of results ***NOT WORKING
{
spname <- "nayaur"
modstats <- "Final_model_stats"
moddir <- "Final_models"

help("kuenm_modstats")

kuenm_modstats(sp.name = spname, fmod.dir = moddir, format = "asc", project = FALSE,
statistics = c("med", "min", "max", "range"), replicated = TRUE,
out.dir = modstats)
}

[marlonecobos]

It looks to me that your coordinates are in a projected coordinate system. To my knowledge Maxent needs coordinates to be in WGS84 (non-projected) format.