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qubvel · Feb 28, 2020 · 6ceca71 · 6ceca71
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diff --git a/README.md b/README.md
@@ -51,7 +51,7 @@ EfficientNets achieve state-of-the-art accuracy on ImageNet with an order of mag
 # efficientnet.keras / efficientnet.tfkeras
 import efficientnet.keras as efn 
 
-model = efn.EfficientNetB0(weights='imagenet')
+model = efn.EfficientNetB0(weights='imagenet')  # or weights='noisy-student'
 
 ```
 
@@ -73,16 +73,16 @@ See the complete example of loading the model and making an inference in the Jup
 
 The performance of each model variant using the pre-trained weights converted from checkpoints provided by the authors is as follows:
 
-| Architecture   | @top1* |
-| -------------- | :----: |
-| EfficientNetB0 | 0.772  |
-| EfficientNetB1 | 0.791  |
-| EfficientNetB2 | 0.802  |
-| EfficientNetB3 | 0.816  |
-| EfficientNetB4 | 0.830  |
-| EfficientNetB5 | 0.837  |
-| EfficientNetB6 | 0.841  |
-| EfficientNetB7 | 0.844  |
+| Architecture   | @top1* Imagenet| @top1* Noisy-Student| 
+| -------------- | :----: |:---:|
+| EfficientNetB0 | 0.772  |0.788|
+| EfficientNetB1 | 0.791  |0.815|
+| EfficientNetB2 | 0.802  |0.824|
+| EfficientNetB3 | 0.816  |0.841|
+| EfficientNetB4 | 0.830  |0.853|
+| EfficientNetB5 | 0.837  |0.861|
+| EfficientNetB6 | 0.841  |0.864|
+| EfficientNetB7 | 0.844  |0.869|
 
 **\*** - topK accuracy score for converted models (imagenet `val` set)
 

diff --git a/efficientnet/__version__.py b/efficientnet/__version__.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-VERSION = (1, 0, 0)
+VERSION = (1, 1, 0)
 
 __version__ = ".".join(map(str, VERSION))