diff --git a/src/utils/template_utils.py b/src/utils/template_utils.py
index 3355546..884e291 100644
--- a/src/utils/template_utils.py
+++ b/src/utils/template_utils.py
@@ -125,8 +125,7 @@ def log_hparams_to_all_loggers(
     )
 
     # send hparams to all loggers
-    for lg in logger:
-        lg.log_hyperparams(hparams)
+    trainer.logger.log_hyperparams(hparams)
 
 
 def finish(
diff --git a/tests/quick_tests.sh b/tests/quick_tests.sh
index c6cdab6..3c5a13a 100644
--- a/tests/quick_tests.sh
+++ b/tests/quick_tests.sh
@@ -4,32 +4,41 @@
 
 # conda activate testenv
 
+export PYTHONWARNINGS="ignore"
+
+print_test_name() {
+  termwidth="$(tput cols)"
+  padding="$(printf '%0.1s' ={1..500})"
+  printf '\e[33m%*.*s %s %*.*s\n\e[0m' 0 "$(((termwidth-2-${#1})/2))" "$padding" "$1" 0 "$(((termwidth-1-${#1})/2))" "$padding"
+}
+
+
 # Test for CPU
-echo TEST 1
-python train.py trainer.gpus=0 trainer.max_epochs=1
+print_test_name "TEST 1"
+python train.py trainer.gpus=0 trainer.max_epochs=1 print_config=false
 
 # Test for GPU
-echo TEST 2
-python train.py trainer.gpus=1 trainer.max_epochs=1
+print_test_name "TEST 2"
+python train.py trainer.gpus=1 trainer.max_epochs=1 print_config=false
 
 # Test multiple workers and cuda pinned memory
-echo TEST 3 
-python train.py trainer.gpus=1 trainer.max_epochs=2 \
+print_test_name "TEST 3"
+python train.py trainer.gpus=1 trainer.max_epochs=2 print_config=false\
 datamodule.num_workers=4 datamodule.pin_memory=True  
 
 # Test all experiment configs
-echo TEST 4
-python train.py -m '+experiment=glob(*)' trainer.gpus=1 trainer.max_epochs=3
+print_test_name "TEST 4"
+python train.py -m '+experiment=glob(*)' trainer.gpus=1 trainer.max_epochs=3 print_config=false
 
 # Test with debug trainer
-echo TEST 5
-python train.py trainer=debug_trainer
+print_test_name "TEST 5"
+python train.py trainer=debug_trainer print_config=false
 
 # Overfit to 10 bathes
-echo TEST 6
-python train.py trainer.min_epochs=20 trainer.max_epochs=20 +trainer.overfit_batches=10
+print_test_name "TEST 6"
+python train.py trainer.min_epochs=20 trainer.max_epochs=20 +trainer.overfit_batches=10 print_config=false
 
 # Test default hydra sweep over hyperparameters (runs 4 different combinations for 1 epoch)
-echo TEST 7
-python train.py -m datamodule.batch_size=32,64 model.lr=0.001,0.003 \
+print_test_name "TEST 7"
+python train.py -m datamodule.batch_size=32,64 model.lr=0.001,0.003 print_config=false \
 trainer.gpus=1 trainer.max_epochs=1