Update README.md

README.md

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 ---
 license: apache-2.0
----
+language:
+- et
+- en
+tags:
+- image classifier
+metrics:
+- accuracy
+---
+# Introduction
+Hello and welcome to the Estonian Bird Classifier model page! This model is created by Karl-Erik Kanal as a part of his Bachelor's thesis and can recognise 50 common Estonian bird species. 
+
+# About the model
+The model estonian_birds_classifier is a pretrained InceptionV3 model on imagenet weights that has been trained using transfer learning to recognise 50 bird species that can be found in estonia.
+The full list of birds that it can classify can be found in the label map provided with the model.
+The model was trained and tested using a custom made dataset for this model, with 5926 images in the training set and 1064 images in the test set. 
+On the test set, the model achieved 74% accuracy, 89% Top-3 accuracy and 91% Top-5 accuracy with a loss of 1.119.
+In comparison, the [Google AIY bird classifier](https://tfhub.dev/google/aiy/vision/classifier/birds_V1/1) that can recognise 45 species of the 50, achieved 71% accuracy on the test set with the 5 species taken out while this model achieved 75% accuracy with the same 45 species.
+
+# How to use
+**The model requires the images to be resized to 150 x 150 and normalized before predicting.** You can use the ImageDataGenerator class from keras.preprocessing.image to achieve this.
+The images should be well-cropped to achieve the best results.
+You can load in the model like you would load in other Keras type models by simply using the load_model function.
+You can load the labels into a dataframe using pandas read_csv. The labels of the birds are provided both in Estonian and in Latin.
+
+    model = keras.models.load_model('estonian_birds_classifier.h5')
+    labels = pd.read_csv('ebc_labelmap.csv', sep=";")