How to solve a problem with null values in SVM and GA

Question

Unfortunately, I have a problem with my code in R. I am trying to use GA to tune up hyperparameters, but I received null values, so it is impossible to train svm. Do you have any idea how to solve the problem?

library(caret)
library(GA)
library(e1071)

Iris <- iris

fit_fun <- function(params){
  model <- train(Species ~ ., data = iris, method = "svmRadial", 
                 trControl = trainControl(method = "cv", number = 5),
                 tuneGrid = data.frame(C = params[1], sigma = params[2]))
  return(model$results[which.min(model$results[,"Accuracy"]),"Accuracy"])
}


param_grid <- expand.grid(C = c(0.1, 1, 10), sigma = c(0.1, 1, 10))


set.seed(123)
best_params <- ga(type = "real-valued", fitness = fit_fun, lower = as.numeric(param_grid[1,]),
                  upper = as.numeric(param_grid[nrow(param_grid),]), maxiter = 20, popSize = 50)


best_cost <- attributes(best_params)$parameters[1]
best_sigma <- attributes(best_params)$parameters[2]


model <- svm(Species ~ ., data = iris, cost = best_cost, 
             sigma = best_sigma, type = "C-classification")

**Error in svm.default(x, y, scale = scale, ..., na.action = na.action) : 
  ‘cost’ must not be NULL!**

Thank You in advance.