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+
+# The Physionet 2017 Challenge 
+
+Before following this guide first follow the setup instructions in the top-level
+[README](../../README.md).
+
+These instructions go through the training and evaluation of a model on the
+[Physionet 2017 challenge](https://www.physionet.org/challenge/2017/) dataset.
+
+## Data
+
+To download and build the datasets run:
+
+```
+./setup.sh
+```
+
+## Training
+
+Change directory to the repo root directory (`ecg`) and run
+
+```
+python ecg/train.py examples/cinc17/config.json -e cinc17
+```
+
+## Evaluation
+
+The test dataset for the Physionet 2017 challenge is hidden and maintained by
+the challenge organizers. To evaluate on this dataset requires packaging and
+submitting the code, dependencies and model to a test server. In general you
+will need to be familiar with the instructions on the challenge
+[website](https://www.physionet.org/challenge/2017/), but we have included some
+scripts to make this as simple as possible.
+
+First change the file in `entry/AUTHORS.txt` to be your name and institution.
+
+Next, from the `entry` directory, run
+
+```
+./prepare-entry.sh <path_to_model>
+```
+
+The model path should be in
+`<path_to_repo>/ecg/saved/cinc17/<timestamp>/<best_model>.hdf5`. The dev set
+loss is the first number in the model file name, so the best model (as
+evaluated by dev set loss) is the model with the smallest first number in its
+name.
+
+Note that this script is quite slow since every time the model is run on a
+record it has to be reloaded. Once complete, a zip file should be created in
+`entry/entry/entry.zip`. This is the submission.