diff --git a/projects/calgary_campinas/README.md b/projects/calgary_campinas/README.md
index eec86c5e..5c7317df 100644
--- a/projects/calgary_campinas/README.md
+++ b/projects/calgary_campinas/README.md
@@ -3,23 +3,23 @@ This folder contains the training code specific for the [Calgary Campinas challe
 As of writing (25 Oct 2020) this is the top result in both Track 1 and Track 2.
 
 ## Training
-The standard training script `train_rim.py` in [tools/](tools) can be used. If you want, the validation volumes can be computed using `predict_val.py`.
+The standard training script `train_model.py` in [tools/](tools) can be used. If you want, the validation volumes can be computed using `predict_val.py`.
 During training, validation metrics will be logged, these match the challenge metrics.
 For our submission we used [base.yaml](configs/base.yaml) as model configuration.
 
-After downloading the data to `<data_root>` a command such as the one below was used (running in the docker container, which maps the code to `direct`):
+After downloading the data to `<data_root>` a command such as the one below was used to train a RIM (running in the docker container, which maps the code to `direct`):
 ```
 cd /direct/tools
-python train_rim.py <data_root>/Train/ \
+python train_model.py <data_root>/Train/ \
                     <data_root>/Val/ \
                     <output_folder> \
                     --name base \
-                    --cfg /direct/projects/calgary_campinas/configs/base.yaml \
+                    --cfg /direct/projects/calgary_campinas/configs/base_rim.yaml \
                     --num-gpus 4 \
                     --num-workers 8 \
                     --resume
 ```
-Additional options can be found using `python train_rim.py --help`.
+Additional options can be found using `python train_model.py --help`.
 
 
 ## Prediction