diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp
index a2b144972..6ac397d6d 100644
Binary files a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp and b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.prompt_tuning.py.swp differ
diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
index eca008b74..5311fc36f 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/prompt_tuning.py
@@ -588,7 +588,7 @@ def get_params() -> AttributeDict:
             "best_train_epoch": -1,
             "best_valid_epoch": -1,
             "batch_idx_train": 0,
-            "log_interval": 20,
+            "log_interval": 5,
             "reset_interval": 200,
             "valid_interval": 3000,  # For the 100h subset, use 800
             # parameters for zipformer