diff --git a/docker/run.sh b/docker/run.sh
index 8210625..64735fa 100755
--- a/docker/run.sh
+++ b/docker/run.sh
@@ -21,7 +21,7 @@ fi
 
 
 python3.10 convert.py -s $1-data/ --camera SIMPLE_RADIAL --no_gpu #GPU produces worse results (?)
-python3.10 train.py -s $1-data/ -r 1 --model_path=$1-data/output/ --position_lr_init 0.000016 --position_lr_final 0.000001 --scaling_lr 0.001 --iterations 100000 #Test more training budget
+python3.10 train.py -s $1-data/ -r 1 --model_path=$1-data/output/ --position_lr_init 0.000016 --scaling_lr 0.001 --iterations 35000 #Test more training budget
 
 python3.10 3dgsconverter/3dgsconverter.py -i $1-data/output/point_cloud/iteration_30000/point_cloud.ply -o $1-data/output/point_cloud/iteration_30000/output_cc.ply -f cc --rgb --density_filter --remove_flyers
 python3.10 3dgsconverter/3dgsconverter.py -i $1-data/output/output/point_cloud/iteration_30000/output_cc.ply  -o $1-data/output/output/point_cloud/iteration_30000/point_cloud_clean.ply -f 3dgs
diff --git a/train.py b/train.py
index 5d819b3..c0f8b22 100644
--- a/train.py
+++ b/train.py
@@ -29,6 +29,9 @@ except ImportError:
     TENSORBOARD_FOUND = False
 
 def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoint_iterations, checkpoint, debug_from):
+    bestLossEncountered     = 1000000
+    pickBetweenFinalNLosses = 10 
+
     first_iter = 0
     tb_writer = prepare_output_and_logger(dataset)
     gaussians = GaussianModel(dataset.sh_degree)
@@ -103,6 +106,10 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
             if iteration == opt.iterations:
                 progress_bar.close()
 
+            if  (bestLossEncountered>ema_loss_for_log) and (pickBetweenFinalNLosses+iteration > opt.iterations):
+                     print("\n[ITER {}] Also remembering this iteration..".format(iteration))
+                     saving_iterations.append(iteration)
+
             # Log and save
             training_report(tb_writer, iteration, Ll1, loss, l1_loss, iter_start.elapsed_time(iter_end), testing_iterations, scene, render, (pipe, background))
             if (iteration in saving_iterations):