diff --git a/pithtrain/tasks/pretrain_language_model.py b/pithtrain/tasks/pretrain_language_model.py
index c740898..df7719e 100644
--- a/pithtrain/tasks/pretrain_language_model.py
+++ b/pithtrain/tasks/pretrain_language_model.py
@@ -422,12 +422,15 @@ def train_step(cfg: PretrainLanguageModelCfg, ctx: PretrainLanguageModelCtx) ->
     torch.distributed.all_reduce(peak_gpu_mem, op=torch.distributed.ReduceOp.MAX)
 
     # Collect the mean load balance loss (reduced across all ranks).
+    # The tracked values include the coefficient: lb_coef * E * dot(f, p).
+    # We divide it out so the logged metric is E * dot(f, p), where 1.0
+    # represents perfect balance (matches Megatron-LM convention).
     moe_load_balance_coef = cfg.training.moe_load_balance_coef
     lb_total, lb_count = MoELoadBalanceLossTracker.get_total_count_and_clear()
     if moe_load_balance_coef > 0:
         lb_stats = torch.tensor([lb_total, lb_count], device=device)
         torch.distributed.all_reduce(lb_stats, op=torch.distributed.ReduceOp.SUM)
-        lb_loss = (lb_stats[0] / lb_stats[1]).item() if lb_stats[1] > 0 else 0.0
+        lb_loss = (lb_stats[0] / lb_stats[1]).item() / moe_load_balance_coef
     else:
         lb_loss = 0.0