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+# Repository Contents
+
+constants.py: File containing all the tuneable parameters and the current values to try
+
+paths.py: File containing all the paths to the data files on the remote server
+
+tuningfunctions.py: File containing functions used in example.ipynb
+
+models.py: File containing the model class definitions to be tuned, tuneable parameters should be placed in constants.py and called when using trial.suggest
+
+example.ipynb: Jupyter Notebook detailing the necessary steps to optimize hyperparameters in Ignite+Optuna, including loading data, defining the objective, running trials, and viewing the Tensorboard logs.
+
+# Accessing Tensorboard Logs
+-Ensure you have tensorboard installed (presuming you use Conda environments run the following)<br>
+```
+conda install -c conda-forge tensorboard
+```
+-after successful install enter below...<br>
+```
+tensorboard --logdir <LOCATION OF TENSORBOARD DIRECTORY>
+```
+-you should see ```TensorBoard 1.15.0 at http://youraddress:6006/ (Press CTRL+C to quit)``` (NOTE that 6006 may be in use by other users)<br>
+-open a new terminal window and enter <br>
+```
+  ssh youruserID@youraddress -- -NfL 6006:localhost:6006
+```
+-open your local browser and type in ```localhost:6006```<br>
+  
+# Example Tensorboard Log Output
+The tensorboard will log all experiments and allow you to review the train and validation stages across them.
+<img src="./Tensorboard_Log_Example.png" width="1000"/>