diff --git a/tests/test_finetune.py b/tests/test_finetune.py
index fad2def8..d0977de5 100644
--- a/tests/test_finetune.py
+++ b/tests/test_finetune.py
@@ -6,61 +6,43 @@
 import timm
 import torch
 
-import terratorch
 from terratorch.cli_tools import build_lightning_cli
 
 
 @pytest.mark.parametrize("model_name", ["prithvi_swin_B", "prithvi_swin_L", "prithvi_vit_100", "prithvi_vit_300"])
-def test_finetune_multiple_backbones(model_name, tmp_path):
-
+def test_finetune_multiple_backbones(model_name, tmpdir):
     model_instance = timm.create_model(model_name)
-    pretrained_bands = [0, 1, 2, 3, 4, 5]
-    model_bands = [0, 1, 2, 3, 4, 5]
 
     state_dict = model_instance.state_dict()
 
-    torch.save(state_dict, os.path.join(tmp_path, model_name + ".pt"))
+    torch.save(state_dict, os.path.join(tmpdir, model_name + ".pt"))
 
     # Running the terratorch CLI
     command_list = ["fit", "-c", f"tests/manufactured-finetune_{model_name}.yaml"]
     _ = build_lightning_cli(command_list)
 
-@pytest.mark.parametrize("model_name", ["prithvi_swin_B"])
-def test_finetune_bands_intervals(model_name, tmp_path):
 
+@pytest.mark.parametrize("model_name", ["prithvi_swin_B"])
+def test_finetune_bands_intervals(model_name, tmpdir):
     model_instance = timm.create_model(model_name)
 
     state_dict = model_instance.state_dict()
 
-    torch.save(state_dict, os.path.join(tmp_path, model_name + ".pt"))
+    torch.save(state_dict, os.path.join(tmpdir, model_name + ".pt"))
 
     # Running the terratorch CLI
     command_list = ["fit", "-c", f"tests/manufactured-finetune_{model_name}_band_interval.yaml"]
     _ = build_lightning_cli(command_list)
 
-@pytest.mark.parametrize("model_name", ["prithvi_swin_B"])
-def test_finetune_bands_str(model_name, tmp_path):
-
-    model_instance = timm.create_model(model_name)
-
-    state_dict = model_instance.state_dict()
 
-    torch.save(state_dict, os.path.join(tmp_path, model_name + ".pt"))
-
-    # Running the terratorch CLI
-    command_list = ["fit", "-c", f"tests/manufactured-finetune_{model_name}_string.yaml"]
-    _ = build_lightning_cli(command_list)
-    
 @pytest.mark.parametrize("model_name", ["prithvi_swin_B"])
-def test_finetune_bands_str(model_name, tmp_path):
-
+def test_finetune_bands_str(model_name, tmpdir):
     model_instance = timm.create_model(model_name)
 
     state_dict = model_instance.state_dict()
 
-    torch.save(state_dict, os.path.join(tmp_path, model_name + ".pt"))
+    torch.save(state_dict, os.path.join(tmpdir, model_name + ".pt"))
 
     # Running the terratorch CLI
-    command_list = ["fit", "-c", f"tests/manufactured-finetune_{model_name}_metrics_from_file.yaml"]
+    command_list = ["fit", "-c", f"tests/manufactured-finetune_{model_name}_string.yaml"]
     _ = build_lightning_cli(command_list)
-