diff --git a/config/config_sci-colorado.json b/configs/config_sci-colorado.json
similarity index 100%
rename from config/config_sci-colorado.json
rename to configs/config_sci-colorado.json
diff --git a/configs/config_sci_full-vol_bs=8_bnf=8_no-bin_lr_augs.json b/configs/config_sci_full-vol_bs=8_bnf=8_no-bin_lr_augs.json
new file mode 100644
index 00000000..6f205292
--- /dev/null
+++ b/configs/config_sci_full-vol_bs=8_bnf=8_no-bin_lr_augs.json
@@ -0,0 +1,117 @@
+{
+    "command": "train",
+    "gpu_ids": [2],
+    "path_output": "/home/GRAMES.POLYMTL.CA/u114716/sci-zurich_project/configs_all_subs/outputs/sciLesions_crpd_exp3_bs_no-bin_seed123",
+    "model_name": "Unet3d_singleContrast",
+    "debugging": true,
+    "object_detection_params": {
+        "object_detection_path": null,
+        "safety_factor": [1.0, 1.0, 1.0]
+    },
+    "wandb": {
+         "wandb_api_key": "bf043c64b6c6b4abcc1ee7d8501c300b19945028",
+         "project_name": "sci-zurich",
+         "group_name": "ivadomed_models",
+         "run_name": "sc=sag_ep=300_bs=8",
+         "log_grads_every": 1000
+     },
+     "loader_parameters": {
+        "path_data": ["/home/GRAMES.POLYMTL.CA/u114716/duke/temp/muena/sci-zurich_preprocessed"],
+        "target_suffix": ["_lesion-manual"],
+        "extensions": [".nii.gz"],
+        "roi_params": {
+            "suffix": null,
+            "slice_filter_roi": null
+        },
+        "contrast_params": {
+            "training_validation": ["T2w"],
+            "testing": ["T2w"],
+            "balance": {}
+        },
+        "slice_filter_params": {
+            "filter_empty_mask": false,
+            "filter_empty_input": false
+        },
+        "slice_axis": "sagittal",
+        "multichannel": false,
+        "soft_gt": true
+    },
+    "split_dataset": {
+        "fname_split": null,
+        "random_seed": 123,
+        "split_method" : "participant_id",
+        "data_testing": {"data_type": null, "data_value":[]},
+        "balance": null,
+        "train_fraction": 0.75,
+        "test_fraction": 0.2
+    },
+    "training_parameters": {
+        "batch_size": 2,
+        "loss": {
+            "name": "DiceLoss"
+        },
+        "training_time": {
+            "num_epochs": 500,
+            "early_stopping_patience": 200,
+            "early_stopping_epsilon": 0.001
+        },
+        "scheduler": {
+            "initial_lr": 1e-4,
+            "lr_scheduler": {
+                "name": "CosineAnnealingLR",
+                "base_lr": 1e-5,
+                "max_lr": 5e-4
+            }
+        },
+        "balance_samples": {"applied": false, "type": "gt"}
+    },
+    "default_model": {
+        "name": "Unet",
+        "final_activation": "relu"
+    },
+    "Modified3DUNet": {
+        "applied": true,
+        "length_3D": [256, 128, 96],
+        "stride_3D": [256, 128, 96],
+        "attention": false,
+        "n_filters": 8
+    },
+    "uncertainty": {
+        "epistemic": false,
+        "aleatoric": false,
+        "n_it": 0
+    },
+    "postprocessing": {
+        "binarize_prediction": {"thr": -1},
+        "uncertainty": {"thr": -1, "suffix": "_unc-vox.nii.gz"}
+    },
+    "evaluation_parameters": {},
+    "transformation": {
+        "CenterCrop": {"size": [256, 128, 96]},
+        "RandomReverse": {
+            "applied_to": ["im", "gt"],
+            "dataset_type": ["training"]
+        },       
+        "RandomAffine": {
+            "degrees": 10,
+            "scale": [0.3, 0.3, 0.3],
+            "translate": [0.1, 0.1, 0.1],
+            "applied_to": ["im", "gt"],
+            "dataset_type": ["training"]
+        },
+        "ElasticTransform": {
+            "alpha_range": [25.0, 35.0],
+            "sigma_range": [3.5, 5.5],
+            "p": 0.5,
+            "applied_to": ["im", "gt"],
+            "dataset_type": ["training"]
+        },
+        "RandomGamma": {
+            "log_gamma_range": [-1.5, 1.5],
+            "p": 0.5,
+            "applied_to": ["im"],
+            "dataset_type": ["training"]
+        },
+        "NormalizeInstance": {"applied_to": ["im"]}
+    }
+}