Udacity_DeepLearning_CharacterLevelRNNExercise

This is my implementation of the Character-based RNN Udacity exercise. The model generates sentences character by character, using its previous picks as inputs for the next.

Dataset

The model was trained using the english version of the book Anna Karenina, stored at the path ./data/anna.txt

Architecture

The model has the following architecture:

• An LSTM with 2 hidden layers of 256 nodes
• A Batch Normalization layer to avoid overfitting
• A Fully Connected layer for the output

Training

The model was trained for 10 epochs using a 0.5 dropout probability for the LSTM nodes. The final loss was 1.2885.

Try it yourself

You can try the model yourself by cloning this repo and running the Character_Level_RNN_Exercise.ipynb notebook. To make it work make sure you have the following packages:

• Numpy
• Torch