diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
index 75c2aeb14678..1a39e15606d4 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
@@ -2145,10 +2145,11 @@ class LogisticRegressionSuite extends MLTest with DefaultReadWriteTest {
   test("multinomial logistic regression with intercept with elasticnet regularization") {
     val trainer1 = (new LogisticRegression).setFitIntercept(true).setWeightCol("weight")
       .setElasticNetParam(0.5).setRegParam(0.1).setStandardization(true)
-      .setMaxIter(300).setTol(1e-10)
+      .setMaxIter(220).setTol(1e-10)
+
     val trainer2 = (new LogisticRegression).setFitIntercept(true).setWeightCol("weight")
       .setElasticNetParam(0.5).setRegParam(0.1).setStandardization(false)
-      .setMaxIter(300).setTol(1e-10)
+      .setMaxIter(90).setTol(1e-10)
 
     val model1 = trainer1.fit(multinomialDataset)
     val model2 = trainer2.fit(multinomialDataset)
@@ -2234,8 +2235,8 @@ class LogisticRegressionSuite extends MLTest with DefaultReadWriteTest {
       0.0, 0.0, 0.0, 0.0), isTransposed = true)
     val interceptsR = Vectors.dense(-0.38857157, 0.62492165, -0.2363501)
 
-    assert(model1.coefficientMatrix ~== coefficientsRStd absTol 0.01)
-    assert(model1.interceptVector ~== interceptsRStd absTol 0.01)
+    assert(model1.coefficientMatrix ~== coefficientsRStd absTol 0.05)
+    assert(model1.interceptVector ~== interceptsRStd absTol 0.1)
     assert(model1.interceptVector.toArray.sum ~== 0.0 absTol eps)
     assert(model2.coefficientMatrix ~== coefficientsR absTol 0.01)
     assert(model2.interceptVector ~== interceptsR absTol 0.01)