diff --git a/run1000.sh b/run1000.sh
index e0bc4c4..46325d9 100644
--- a/run1000.sh
+++ b/run1000.sh
@@ -70,7 +70,7 @@ python -m scripts.tok_eval
 # which would decrease model performance. Possibly 2, 3 or so epochs is ~ok, but certainly not ideal and at 10+ epochs we'd
 # start to overfit hard.
 # 5) That's it, everything else (e.g. the learning rates) is adjusted automatically by the training script.
-torchrun --standalone --nproc_per_node=8 -m scripts.base_train -- --depth=32 --device_batch_size=8
+torchrun --standalone --nproc_per_node=8 -m scripts.base_train -- --depth=32 --device_batch_size=8 --run=$WANDB_RUN
 torchrun --standalone --nproc_per_node=8 -m scripts.base_loss
 torchrun --standalone --nproc_per_node=8 -m scripts.base_eval