lgb.get.eval.result(
  booster,
  data_name,
  eval_name,
  iters = NULL,
  is_err = FALSE
)

# train a regression model
data(agaricus.train, package = "lightgbm")
train <- agaricus.train
dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm")
test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2")
valids <- list(test = dtest)
model <- lgb.train(
  params = params
  , data = dtrain
  , nrounds = 5L
  , valids = valids
  , min_data = 1L
  , learning_rate = 1.0
)

# Examine valid data_name values
print(setdiff(names(model$record_evals), "start_iter"))

# Examine valid eval_name values for dataset "test"
print(names(model$record_evals[["test"]]))

# Get L2 values for "test" dataset
lgb.get.eval.result(model, "test", "l2")