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            ## Model description
         
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            ## Intended uses & limitations
         
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            ## Training and evaluation data
         
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            ## Training procedure
         
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            ### Training hyperparameters
         
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            The following hyperparameters were used during training:
         
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            - training_precision: float32
         
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             ## Training Metrics
         
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            ## Model description
         
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            This repo contains the model which showcases the learning capabilities of LSTM using a simple example. A single-layer LSTM is made to learn to add two numbers, provided as strings. The model has been trained for adding two numbers where each number can have maximum of 5 digits.   
         
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            *Example:*
         
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            Input: "535+61"
         
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            Output: "596"
         
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            Full credits to [Smerity](https://twitter.com/Smerity) and others for this work.
         
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            ## Intended uses & limitations
         
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            ## Training and evaluation data
         
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            The data consists of generation of two random 5 digit numbers as input and their sum as output. These numbers (_and their sum)_ are encoded and fed as input to LSTM. The full data creation code is available within the [example](https://keras.io/examples/nlp/addition_rnn/).
         
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            ## Training procedure
         
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            ### Training hyperparameters
         
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            The following hyperparameters were used during training:
         
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            - learning_rate: 0.001
         
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            - train_batch_size: 32
         
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            - optimizer: {'name': 'Adam', 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
         
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            - training_precision: float32
         
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            - num_epochs: 30
         
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             ## Training Metrics
         
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