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@@ -36,17 +36,19 @@ It achieves the following results on the evaluation set:
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  ## Model description
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- More information needed
 
 
 
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- ## Intended uses & limitations
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- More information needed
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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  ### Training hyperparameters
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  ## Model description
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+ This model was created by importing the dataset of the photos of flowers into
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+ Google Colab from kaggle here: https://www.kaggle.com/datasets/l3llff/flowers.
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+ I then used the image classification tutorial here:
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+ https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb
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+ obtaining the following notebook:
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+ https://colab.research.google.com/drive/1bapCEz4vkDd16Ax9jb5oHGa85PeuyZVW?usp=sharing
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+ The possible classified flowers are:
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+ 'common_daisy', 'rose', 'california_poppy', 'iris', 'astilbe', 'carnation',
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+ 'tulip', 'sunflower', 'coreopsis', 'magnolia', 'water_lily', 'bellflower',
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+ 'daffodil', 'calendula', 'dandelion', 'black_eyed_susan'
 
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  ### Training hyperparameters
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