diff --git a/main.py b/main.py
index ef7676823df473b16c5fbf04096e342e81672349..0cfe2257511501c5a5f007a09e72dbef2a11e871 100644
--- a/main.py
+++ b/main.py
@@ -136,6 +136,7 @@ def trainRNNAE(model, nClasses, data, f_data, s_data, y_val, loss_huber, optimiz
 	#th = 40
 	n_epochs_warmUp = 40
 	centers = None
+	print("PRETRAINING STAGE : AE + CONTRASTIVE LOSS")
 	for e in range(n_epochs_warmUp):
 		f_data, s_data, y_val, = shuffle(f_data, s_data, y_val)
 		data = shuffle(data)
@@ -143,6 +144,8 @@ def trainRNNAE(model, nClasses, data, f_data, s_data, y_val, loss_huber, optimiz
 		trainLoss += trainStepL(model, f_data, s_data, y_val, loss_huber, optimizer2, BATCH_SIZE, e)
 		print("epoch %d with loss %f" % (e, trainLoss))
 
+
+	print("COMPUTE INTERMEDIATE CLUSTERING ASSIGNMENT")
 	emb, _, _, _ = model(data)
 	km = KMeans(n_clusters=nClasses)
 	km.fit(emb)
@@ -151,6 +154,8 @@ def trainRNNAE(model, nClasses, data, f_data, s_data, y_val, loss_huber, optimiz
 		centers.append( km.cluster_centers_[val])
 	centers = np.array(centers)
 
+
+	print("REFINEMENT STEP alternating AE + MANIFOLD STRETCH TOWARDS CENTROIDS and AE + CONTRASTIVE LOSS")
 	for e in range(n_epochs - n_epochs_warmUp):
 		#labelledData, labelsSmall = shuffle(labelledData, labelsSmall)
 		data, centers = shuffle(data, centers)