Update README.md

Author: jaime-cespedes-sisniega

README.md

@@ -39,7 +39,9 @@ python ml/training.py -d CIFAR10
 
 For each dataset, this will create a `cnn.pt` (inference model), `detector.pkl` (covariate drift detector), `encoder.pt` (dimensionality reduction model) and `transformer.pt` (preprocessing object) files in the `ml/objects` directory.
 
-In addition, `cnn.pt` and `transformer.pt` are stored in the `model_inference_api/app/objects` directory. `encoder.pt` and `transformer.pt` are stored in the `dimensionality_reduction_api/app/objects` directory. `detector.pkl` is stored in the `detector_api/app/objects` directory.
+In addition, `cnn.pt` and `transformer.pt` are also stored in the `model_inference_api/app/objects` directory. `encoder.pt` and `transformer.pt` are stored in the `dimensionality_reduction_api/app/objects` directory. `detector.pkl` is stored in the `detector_api/app/objects` directory.
+
+The training script will also generate two plots for each dataset with the losses (train and validation) for the autoencoder and the model.
 
 ## Testing
 
@@ -103,6 +105,13 @@ make build-dimensionality-reduction
 make build-covariate-drift-detector
 ```
 
+## Plots
+
+The transformations plots in the paper can be generated by running the following command:
+
+```bash
+python ml/plot.py
+```
 
 ## Citation