diff --git a/experiments/running_sweeps.md b/experiments/running_sweeps.md
index 576b600..66e8864 100644
--- a/experiments/running_sweeps.md
+++ b/experiments/running_sweeps.md
@@ -1,8 +1,108 @@
-## Experiments
+# Running Sweeps and Experiment Structure
 
-We use `hydra` for experiment management. The experiments are structured as follow:
+## Overview
 
--   In `configs` there are default and experiment specific configurations file.
--   Each experiment has a config file named after it, as well as a folder with the same name, for example:
-    -   `./configs/spatialclip_pretrain.yaml` and `./spatialclip_pretrain` represent the same experiment.
-        The first is the configuration file, the second is the folder where slurm logs and results are stored.
+Experimental configs are organized within the `experiments/` directory, which follows a modular layout. The experiments folder is structured as follow:
+```
+experiments
+├── configs                  # main folder for experimental configuration files
+│   ├── datamodule/          # dataset configs for each panel
+│   ├── launcher/            # cluster & local launcher configs (slurm, local)
+│   ├── model/               # default model configs
+│   ├── paths/               # dataset and pretrained weights paths
+│   ├── training/            # default training configs
+│   ├── core_config_*.yaml   # (development only)
+│   ├── holy_grail_*.yaml    # benchmark sweep configs to recreate results
+│   └── local_config.yaml    # default config for local runs
+│
+├── drvi_pretrain/           # DRVI-specific pretraining files
+│   ├── train.py
+│   ├── inference.py
+│   ├── drvi_train.bash
+│   └── drvi_results.ipynb
+│
+├── hescape_pretrain/        # pretraining related files
+│   ├── train.py             # training script
+│   ├── local.bash           # launcher for local runs
+│   └── holy_grail_*.bash    # benchmark sweep launchers for each dataset
+│
+├── yaml_configs/            # (development only)
+│   └── ...                  
+│
+└── running_sweeps.md        
+```
+
+## Hydra-based Experiment Management
+
+HESCAPE uses [Hydra](https://hydra.cc) for configuration management and sweep orchestration.  
+Each experiment is defined by a YAML configuration in `experiments/configs/` and launched via a `.bash` script in `experiments/hescape_pretrain/`.
+
+Hydra combines multiple configuration files (for the model, data, training, and environment) into a single experiment specification. You can override parameters directly from the command line or define multiple values for a parameter to perform *grid sweeps*.
+
+Example `configs/holy_grail_lung_healthy.yaml`:
+
+```yaml
+hydra:
+  sweeper:
+    params:
+      model.litmodule.img_enc_name: h0-mini, uni
+      model.litmodule.gene_enc_name: drvi, nicheformer
+      model.litmodule.loss: CLIP, SIGLIP
+      datamodule.batch_size: 64, 256
+```
+Running this config will automatically expand into all combinations of the parameter values, launching one job per configuration (in this example: 2×2×2×2 = 16 runs).
+
+### Launching Sweeps
+
+Sweeps can be launched either locally or on an HPC cluster via Slurm (recommended for large-scale benchmarks).
+
+#### Local Example
+
+For quick iteration or smoke testing on a single GPU:
+```bash
+uv run experiments/hescape_pretrain/train.py \
+  --config-name=local_config.yaml \
+  launcher=local \
+  training.lightning.trainer.devices=1 \
+  datamodule.batch_size=8 \
+  training.lightning.trainer.max_steps=200
+```
+
+This command runs a single experiment (no sweeping) using the local launcher. Alternatively, `experiments/hescape_pretrain/local.bash` can be used to launch local runs.
+
+#### Slurm Sweep Example (Benchmark Reproduction)
+
+Each `holy_grail_*.bash` file launches the corresponding benchmark sweep on an HPC environment configured via the appropriate launcher YAML (e.g. configs/launcher/juelich.yaml).
+
+Example `experiments/hescape_pretrain/holy_grail_lung_healthy.bash` 
+```bash 
+#!/bin/bash
+source .venv/bin/activate
+
+export WANDB_MODE=offline
+export HYDRA_FULL_ERROR=1
+export CUDA_VISIBLE_DEVICES=0,1,2,3
+unset SLURM_CPU_BIND
+NCCL_DEBUG=INFO
+
+uv run experiments/hescape_pretrain/train.py \
+  --config-name=holy_grail_lung_healthy.yaml \
+  launcher=juelich \
+  --multirun
+```
+Key points:
+- `--multirun` triggers a Hydra sweep
+- `launcher=juelich` loads the Slurm configuration from `configs/launcher/juelich.yaml`
+- The sweep expands all parameter combinations under `hydra.sweeper.params` in the config file
+- Logs, checkpoints, and metrics are stored automatically under `experiments/hescape_pretrain/holy_grail_lung_healthy/`
+
+### Customizing a Sweep
+To create your own sweep:
+
+1. Copy an existing benchmark config
+2. Edit the `hydra.sweeper.params` section to define the grid
+
+3. Launch using a custom launcher file or via CLI with:
+```bash
+uv run experiments/hescape_pretrain/train.py --config-name=my_experiment.yaml --multirun
+````