diff --git a/config/gpt2_large_sophia_g.yaml b/config/gpt2_large_sophia_g.yaml
deleted file mode 100644
index 53a1d0806..000000000
--- a/config/gpt2_large_sophia_g.yaml
+++ /dev/null
@@ -1,21 +0,0 @@
-data: !include data/openwebtext_source.yaml
-model:
-  type: gpt2
-  hidden_dim: 1280
-  num_heads: 20
-  num_layers: 36
-  seq_len: 1024
-  gradient_checkpointing: true
-  scale_attn_by_inverse_layer_idx: true
-trainer:
-  wandb:
-    project: "levanter"
-    tags: [ "openwebtext", "gpt2", "sophia-g"]
-
-  num_train_steps: 200000
-  mp: p=f32,c=bfloat16
-
-optimizer:
-  type: sophia-g
-  learning_rate: 2E-4
-  weight_decay: 0.15
diff --git a/config/gpt2_small_fast_sophia_g.yaml b/config/gpt2_small_fast_sophia_g.yaml
deleted file mode 100644
index 0f86ac503..000000000
--- a/config/gpt2_small_fast_sophia_g.yaml
+++ /dev/null
@@ -1,24 +0,0 @@
-data: !include data/openwebtext_source.yaml
-model:
-  type: gpt2
-  hidden_dim: 768
-  num_heads: 12
-  num_layers: 12
-  seq_len: 1024
-  gradient_checkpointing: true
-  scale_attn_by_inverse_layer_idx: true
-trainer:
-  wandb:
-    project: "levanter"
-    tags: [ "openwebtext", "gpt2", "itest", "sophia-g"]
-
-  mp: p=f32,c=bfloat16
-  model_axis_size: 1
-  per_device_parallelism: 8
-
-  train_batch_size: 256
-  num_train_steps: 20000
-optimizer:
-  type: sophia-g
-  learning_rate: 1E-3
-  weight_decay: 0.15
diff --git a/src/levanter/doremi.py b/src/levanter/doremi.py
index 602dae4db..d9bcd5170 100644
--- a/src/levanter/doremi.py
+++ b/src/levanter/doremi.py
@@ -185,7 +185,7 @@ def doremi_step(state: DoremiState, ref, batch, domains):
                 "train/mean_proxy_loss": mean_proxy_loss,
                 **{f"alpha/{domain}": weight for domain, weight in alpha_dict.items()},
                 # just skip domains with no excess loss
-                **{f"train/{domain}/excess_loss": loss for domain, loss in per_domain_dict.items() if loss > 0},
+                **{f"train/{domain}/excess_loss": loss for domain, loss in per_domain_dict.items()},
             },
             step=state._step,
         )