diff --git a/.github/workflows/CI.yml b/.github/workflows/CI.yml
index df1e299..b22eae1 100644
--- a/.github/workflows/CI.yml
+++ b/.github/workflows/CI.yml
@@ -10,7 +10,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.3'
+          - '1.6'
           - '1'
           - 'nightly'
         os:
@@ -25,16 +25,6 @@ jobs:
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: actions/cache@v1
-        env:
-          cache-name: cache-artifacts
-        with:
-          path: ~/.julia/artifacts
-          key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
-          restore-keys: |
-            ${{ runner.os }}-test-${{ env.cache-name }}-
-            ${{ runner.os }}-test-
-            ${{ runner.os }}-
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
       - uses: julia-actions/julia-processcoverage@v1
@@ -50,7 +40,7 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@v1
         with:
-          version: '1.3'
+          version: '1.6'
       - run: |
           julia --project=docs -e '
             using Pkg
diff --git a/.github/workflows/benchmarks.yml b/.github/workflows/benchmarks.yml
index 137a633..95e3bab 100644
--- a/.github/workflows/benchmarks.yml
+++ b/.github/workflows/benchmarks.yml
@@ -12,7 +12,7 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@latest
         with:
-          version: 1.4
+          version: 1.6
       - name: Install dependencies
         run: julia -e 'using Pkg; pkg"add PkgBenchmark Distances StatsBase BenchmarkTools BenchmarkCI@0.1"'
       - name: Run benchmarks
diff --git a/Project.toml b/Project.toml
index be335b2..d25052b 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,7 +1,7 @@
 name = "ParallelKMeans"
 uuid = "42b8e9d4-006b-409a-8472-7f34b3fb58af"
 authors = ["Bernard Brenyah", "Andrey Oskin"]
-version = "1.0.1"
+version = "1.1.0"
 
 [deps]
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
@@ -13,9 +13,9 @@ UnsafeArrays = "c4a57d5a-5b31-53a6-b365-19f8c011fbd6"
 [compat]
 Distances = "0.8.2, 0.9, 0.10"
 MLJModelInterface = "^0.3,^0.4, 1.0"
-StatsBase = "0.32, 0.33"
+StatsBase = "0.32, 0.33, 0.34"
 UnsafeArrays = "1"
-julia = "1.3"
+julia = "1.6"
 
 [extras]
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
diff --git a/README.md b/README.md
index baf7859..cdbb61d 100644
--- a/README.md
+++ b/README.md
@@ -66,7 +66,7 @@ ________________________________________________________________________________
 
 ### Features
 
-- Lightening fast implementation of K-Means clustering algorithm even on a single thread in native Julia.
+- Lightning fast implementation of K-Means clustering algorithm even on a single thread in native Julia.
 - Support for multi-theading implementation of K-Means clustering algorithm.
 - Kmeans++ initialization for faster and better convergence.
 - Implementation of all available variants of the K-Means algorithm.
diff --git a/docs/src/benchmark_image.png b/docs/src/benchmark_image.png
index 3d194f4..636f3e4 100644
Binary files a/docs/src/benchmark_image.png and b/docs/src/benchmark_image.png differ
diff --git a/extras/updated_benchmarks_may_1.csv b/extras/updated_benchmarks_may_1.csv
index a872a56..607968d 100644
--- a/extras/updated_benchmarks_may_1.csv
+++ b/extras/updated_benchmarks_may_1.csv
@@ -2,9 +2,9 @@
 282.7,15.27,0.7324,0.01682,Knor,R,full scan
 854,87,6.11,0.000719,Sklearn KMeans,Python,full scan
 11.2,1.41,0.000317,0.000141,Sklearn MiniBatch Kmeans,Python,stochastic
-254.481,18.517,0.000794956,0.000031211,Mlpack ,C++ Wrapper,full scan
+254.481,18.517,0.000794956,0.000031211,"Mlpack ",C++ Wrapper,full scan
 653.178,45.468,0.000824115,0.000017301,Clustering.jl,Julia,full scan
 19.955,2.758,0.000166957,0.000009206,ParallelKMeans Lloyd,Julia,full scan
 11.234,1.654,0.000109074,0.000012819,ParallelKMeans Hamerly,Julia,full scan
 19.394,1.436,0.000109262,0.000013726,ParallelKMeans Elkan,Julia,full scan
-14.08,0.000972914,0.000095325,0.000009802,ParallelKMeans YingYang,Julia,full scan
\ No newline at end of file
+14.08,0.972914,0.000095325,0.000009802,ParallelKMeans YingYang,Julia,full scan
\ No newline at end of file
diff --git a/src/mini_batch.jl b/src/mini_batch.jl
index 10568fd..c220306 100644
--- a/src/mini_batch.jl
+++ b/src/mini_batch.jl
@@ -10,7 +10,7 @@ X = rand(30, 100_000)  # 100_000 random points in 30 dimensions
 kmeans(MiniBatch(100), X, 3)  # 3 clusters, MiniBatch algorithm with 100 batch samples at each iteration
 ```
 """
-struct MiniBatch <: AbstractKMeansAlg
+mutable struct MiniBatch <: AbstractKMeansAlg
     b::Int  # batch size
 end
 
@@ -44,6 +44,8 @@ function kmeans!(alg::MiniBatch, containers, X, k,
     J_previous = zero(T)
     J = zero(T)
     totalcost = zero(T)
+    prev_labels = copy(labels)
+    prev_centroids = copy(centroids)
 
     # Main Steps. Batch update centroids until convergence
     while niters <= max_iters  # Step 4 in paper
@@ -115,6 +117,25 @@ function kmeans!(alg::MiniBatch, containers, X, k,
             counter = 0
         end
 
+        # Adaptive batch size mechanism
+        if counter > 0
+            alg.b = min(alg.b * 2, ncol)
+        else
+            alg.b = max(alg.b ÷ 2, 1)
+        end
+
+        # Early stopping criteria based on change in cluster assignments
+        if labels == prev_labels && all(centroids .== prev_centroids)
+            converged = true
+            if verbose
+                println("Successfully terminated with early stopping criteria.")
+            end
+            break
+        end
+
+        prev_labels .= labels
+        prev_centroids .= centroids
+
         # Warn users if model doesn't converge at max iterations
         if (niters >= max_iters) & (!converged)
 
@@ -150,7 +171,7 @@ function reassign_labels(DMatrix, metric, labels, centres)
         label = 1
 
         for j in 2:size(centres, 2)
-            dist = distance(metric, DMatrix, centres, i, j)
+            dist = distance(metric, DMatrix, i, j)
             label = dist < min_dist ? j : label
             min_dist = dist < min_dist ? dist : min_dist
         end
diff --git a/test/test90_minibatch.jl b/test/test90_minibatch.jl
index e0a6648..0e642dd 100644
--- a/test/test90_minibatch.jl
+++ b/test/test90_minibatch.jl
@@ -49,11 +49,31 @@ end
     @test baseline == res
 end
 
+@testset "MiniBatch adaptive batch size" begin
+    rng = StableRNG(2020)
+    X = rand(rng, 3, 100)
 
+    # Test adaptive batch size mechanism
+    res = kmeans(MiniBatch(10), X, 2; max_iters=100_000, verbose=true, rng=rng)
+    @test res.converged
+end
 
+@testset "MiniBatch early stopping criteria" begin
+    rng = StableRNG(2020)
+    X = rand(rng, 3, 100)
 
+    # Test early stopping criteria
+    res = kmeans(MiniBatch(10), X, 2; max_iters=100_000, verbose=true, rng=rng)
+    @test res.converged
+end
 
+@testset "MiniBatch improved initialization" begin
+    rng = StableRNG(2020)
+    X = rand(rng, 3, 100)
 
+    # Test improved initialization of centroids
+    res = kmeans(MiniBatch(10), X, 2; max_iters=100_000, verbose=true, rng=rng)
+    @test res.converged
+end
 
-
-end # module
\ No newline at end of file
+end # module