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README.md
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## Training Procedure
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As the purpose of this model was to act just as a proof of concept for quick prototyping of RecycleTree, I opted to use the fast.ai library and a simple model architecture of ResNet34.
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The training procedure is following the recommendations from [fast.ai](https://docs.fast.ai/)
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## Training Procedure
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As the purpose of this model was to act just as a proof of concept for quick prototyping of RecycleTree, I opted to use the fast.ai library and a simple model architecture of ResNet34.
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The training procedure is following the recommendations from [fast.ai](https://docs.fast.ai/)
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## Other Models
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There are also other models in the RecycleTree model series:
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* [Materials Classification Model](https://huggingface.co/pyesonekyaw/recycletree_materials) - Classification of images of trash into different materials
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* [Paper Classification Model](https://huggingface.co/pyesonekyaw/recycletree_paper) - Classification of images of paper trash into different classes
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* [Metal Classification Model](https://huggingface.co/pyesonekyaw/recycletree_metal) - Classification of images of metal trash into different classes
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* [Glass Classification Model](https://huggingface.co/pyesonekyaw/recycletree_glass) - Classification of images of glass trash into different classes
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* [Others Classification Model](https://huggingface.co/pyesonekyaw/recycletree_others) - Classification of images of other (not paper, metal, glass, or plastic) trash into different classes
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