jrpespinas / pytorch-autoencoder

Develop an autoencoder using PyTorch

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Autoencoder

Overview

This repository is based from this Medium article. The main focus is to implement a convolutional autoencoder in PyTorch with CIFAR-10 dataset.

Results

epoch [1/10], loss:0.3079
epoch [2/10], loss:0.3022
epoch [3/10], loss:0.2992
epoch [4/10], loss:0.2974
epoch [5/10], loss:0.2963
epoch [6/10], loss:0.2952
epoch [7/10], loss:0.2937
epoch [8/10], loss:0.2930
epoch [9/10], loss:0.2914
epoch [10/10], loss:0.2903

LICENSE

MIT License

Copyright (c) 2020 Bogs Espinas

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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Develop an autoencoder using PyTorch

License:MIT License


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