diff --git a/torchbenchmark/models/hf_T5_large/metadata.yaml b/torchbenchmark/models/hf_T5_large/metadata.yaml
index 178e62a99f..fc1bf49d41 100644
--- a/torchbenchmark/models/hf_T5_large/metadata.yaml
+++ b/torchbenchmark/models/hf_T5_large/metadata.yaml
@@ -7,4 +7,4 @@ not_implemented:
   # hf_T5 model doesn't support JIT
   - jit: true
   # disable train test because of CI infra capacity issue
-  - test: train
\ No newline at end of file
+  - test: train
diff --git a/torchbenchmark/util/model.py b/torchbenchmark/util/model.py
index 294b2b6a64..d7eebcba06 100644
--- a/torchbenchmark/util/model.py
+++ b/torchbenchmark/util/model.py
@@ -180,7 +180,7 @@ def determine_batch_size(self, batch_size=None):
             elif self.test == "eval" and (not self.batch_size == self.DEFAULT_EVAL_BSIZE):
                 raise NotImplementedError("Model doesn't support customizing batch size.")
         elif self.dargs.accuracy:
-            self.batch_size = 4
+            self.batch_size = 4 if self.batch_size > 4 else self.batch_size
 
     def load_metadata(self):
         relative_path = self.__class__.__module__.split(".")