Update README.md

README.md

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 # Introduction
-Hello and welcome to the Estonian Bird Classifier model page! This model was created by Karl-Erik Kanal as a part of his Bachelor's thesis and can recognise 50 common Estonian bird species. 
+Hello, and welcome to the Estonian Bird Classifier model page! This model was 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 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 complete 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. 
+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.
+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.