diff --git a/elk/training/sweep.py b/elk/training/sweep.py
index e4aca5a0..bbd761c9 100755
--- a/elk/training/sweep.py
+++ b/elk/training/sweep.py
@@ -5,7 +5,6 @@
 from datasets import get_dataset_config_info
 from transformers import AutoConfig
 
-from ..evaluation import Eval
 from ..extraction import Extract
 from ..files import memorably_named_dir, sweeps_dir
 from ..plotting.visualize import visualize_sweep
@@ -134,19 +133,19 @@ def execute(self):
                         data = replace(
                             self.run_template.data, model=model, datasets=train_datasets
                         )
-                        run = replace(self.run_template, data=data, out_dir=out_dir)
+                        elicit = replace(self.run_template, data=data, out_dir=out_dir)
                         if var_weight is not None and neg_cov_weight is not None:
-                            assert isinstance(run.net, EigenFitterConfig)
-                            run.net.var_weight = var_weight
-                            run.net.neg_cov_weight = neg_cov_weight
+                            assert isinstance(elicit.net, EigenFitterConfig)
+                            elicit.net.var_weight = var_weight
+                            elicit.net.neg_cov_weight = neg_cov_weight
 
                             # Add hyperparameter values to output directory if needed
-                            assert run.out_dir is not None
-                            run.out_dir /= f"var_weight={var_weight:.2f}"
-                            run.out_dir /= f"neg_cov_weight={neg_cov_weight:.2f}"
+                            assert elicit.out_dir is not None
+                            elicit.out_dir /= f"var_weight={var_weight:.2f}"
+                            elicit.out_dir /= f"neg_cov_weight={neg_cov_weight:.2f}"
 
                         try:
-                            run.execute()
+                            elicit.execute()
                         except torch.linalg.LinAlgError as e:
                             print(colorize(f"LinAlgError: {e}", "red"))
                             continue
@@ -161,17 +160,7 @@ def execute(self):
                                 if eval_dataset in train_datasets:
                                     continue
 
-                                assert run.out_dir is not None
-                                eval = Eval(
-                                    data=replace(
-                                        run.data, model=model, datasets=(eval_dataset,)
-                                    ),
-                                    source=run.out_dir,
-                                    out_dir=run.out_dir / "transfer" / eval_dataset,
-                                    num_gpus=run.num_gpus,
-                                    min_gpu_mem=run.min_gpu_mem,
-                                    skip_supervised=run.supervised == "none",
-                                )
+                                eval = elicit.make_eval(model, eval_dataset)
                                 eval.execute(highlight_color="green")
 
         if self.visualize:
diff --git a/elk/training/train.py b/elk/training/train.py
index 8392f2d9..82316506 100644
--- a/elk/training/train.py
+++ b/elk/training/train.py
@@ -1,7 +1,7 @@
 """Main training loop."""
 
 from collections import defaultdict
-from dataclasses import dataclass
+from dataclasses import dataclass, replace
 from pathlib import Path
 from typing import Literal
 
@@ -11,6 +11,7 @@
 from simple_parsing import subgroups
 from simple_parsing.helpers.serialization import save
 
+from ..evaluation import Eval
 from ..metrics import evaluate_preds, to_one_hot
 from ..run import Run
 from ..training.supervised import train_supervised
@@ -48,6 +49,26 @@ def create_models_dir(self, out_dir: Path):
 
         return reporter_dir, lr_dir
 
+    def make_eval(self, model, eval_dataset):
+        assert self.out_dir is not None
+        return Eval(
+            data=replace(
+                self.data,
+                model=model,
+                datasets=(eval_dataset,),
+            ),
+            source=self.out_dir,
+            out_dir=self.out_dir / "transfer" / eval_dataset,
+            num_gpus=self.num_gpus,
+            min_gpu_mem=self.min_gpu_mem,
+            skip_supervised=self.supervised == "none",
+            prompt_indices=self.prompt_indices,
+            concatenated_layer_offset=self.concatenated_layer_offset,
+            # datasets isn't needed because it's immediately overwritten
+            debug=self.debug,
+            disable_cache=self.disable_cache,
+        )
+
     def apply_to_layer(
         self,
         layer: int,