diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 8ec6a0d..043b9c0 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -39,12 +39,10 @@ jobs:
 
     runs-on: ubuntu-latest
     strategy:
+      max-parallel: 1
       matrix:
         python-version: [3.6, 3.7, 3.8]
-        tensorflow-version: [2.1.0, 2.2.0, 2.3.0, 2.4.0, 2.5.0]
-        exclude:
-          - tensorflow-version: 2.1.0
-            python-version: 3.8
+        tensorflow-version: [2.3.0, 2.4.0, 2.5.0]
 
     steps:
       - uses: actions/checkout@v2
@@ -69,11 +67,17 @@ jobs:
 
     runs-on: ubuntu-latest
     strategy:
+      max-parallel: 1
       matrix:
-        python-version: [3.6, 3.7, 3.8]
-        tensorflow-version: [2.6.0]
-        keras-version: [2.6.0]
-
+        python-version: [3.7, 3.8]
+        tensorflow-version: [2.6.0, 2.7.0, 2.8.0]
+        include:
+          - tensorflow-version: 2.6.0
+            keras-version: 2.6.0
+          - tensorflow-version: 2.7.0
+            keras-version: 2.7.0
+          - tensorflow-version: 2.8.0
+            keras-version: 2.8.0
     steps:
       - uses: actions/checkout@v2
       - name: Set up Python ${{ matrix.python-version }}
diff --git a/tests/integration/conftest.py b/tests/integration/conftest.py
index 340d40a..0dfafaf 100644
--- a/tests/integration/conftest.py
+++ b/tests/integration/conftest.py
@@ -23,10 +23,10 @@ def mnist_dataset(num_classes):
     test_labels = tf.keras.utils.to_categorical(test_labels, num_classes=num_classes)
 
     return (
-        train_images[0:500],
-        train_labels[0:500],
-        test_images[0:300],
-        test_labels[0:300],
+        train_images[0:100],
+        train_labels[0:100],
+        test_images[0:50],
+        test_labels[0:50],
     )
 
 
diff --git a/tests/integration/test_keras_api.py b/tests/integration/test_keras_api.py
index 71114cd..d637ef0 100644
--- a/tests/integration/test_keras_api.py
+++ b/tests/integration/test_keras_api.py
@@ -173,4 +173,4 @@ def test_all_keras_api(
     ]
 
     # Start training
-    model.fit(train_images, train_labels, epochs=3, callbacks=callbacks)
+    model.fit(train_images, train_labels, epochs=2, callbacks=callbacks)