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README.md

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-license: cc-by-4.0
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+license: cc-by-4.0
+metrics:
+- accuracy
+---
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+# Image Scenery Classification
+This model is built on the efficientnet_b2 architecture.
+The model uses pretrained weights of the model found in the torchvision.models library.
+The classification head was changed, to be a dropout layer, followed by a linear layer with 6 target classes.  
+Using transfer learning, the model was then trained on the [intel image dataset.](https://www.kaggle.com/datasets/puneet6060/intel-image-classification)
+
+#### Performance
+The model achieved a test accuracy of 89,67%.  
+Misclassified images are often times ambiguous, such as a snowy mountain, being classified as 'glacier'.
+The model architecture is quite simple, when compared to SOTA architectures and produces fast predictions.
+A prediction on the hugging face space, hosted on the free cpu, takes about 0.2 seconds.
+
+The code is original and written by me.