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README.md
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## Introduction
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This model is defined as proposed in the book "mastering pytorch".
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It is based on CNN-encoder and a LSTM-decoder.
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## Introduction
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This model is defined as proposed in the book "mastering pytorch".
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It is based on CNN-encoder and a LSTM-decoder.
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The CNN-encoder is based on a pretrained RESNET-152. The last layer of the resnet is replaced by a vector embedding layer of 256 elements.
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The LSTM-decoder use an input of 256, a hidden layer of 512, and uses the vocabulary size.
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The model has been trained as a pure learning exercise, and so the model performances remain relatively mean.
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## Training procedure
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For the sake of the exercise, the model has been trained for only 5 epochs.
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It has been trained on the COCO dataset.
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