diff --git a/fit/tools/train.py b/fit/tools/train.py
index 7977adc..954b08f 100644
--- a/fit/tools/train.py
+++ b/fit/tools/train.py
@@ -72,8 +72,8 @@ def train(smpl_layer, target,
     scale = params["scale"]
     
     early_stop = Early_Stop()
-    # for epoch in tqdm(range(cfg.TRAIN.MAX_EPOCH)):
-    for epoch in range(cfg.TRAIN.MAX_EPOCH):
+    for epoch in tqdm(range(cfg.TRAIN.MAX_EPOCH)):
+    # for epoch in range(cfg.TRAIN.MAX_EPOCH):
         verts, Jtr = smpl_layer(pose_params, th_betas=shape_params)
         loss = F.smooth_l1_loss(Jtr.index_select(1, index["smpl_index"]) * 100 * scale,
                                 target.index_select(1, index["dataset_index"]) * 100)
@@ -89,8 +89,8 @@ def train(smpl_layer, target,
             break
         
         if epoch % cfg.TRAIN.WRITE == 0:
-            logger.info("Epoch {}, lossPerBatch={:.6f}, scale={:.4f} EarlyStopSatis: {}".format(
-                    epoch, float(loss),float(scale), early_stop.satis_num))
+            # logger.info("Epoch {}, lossPerBatch={:.6f}, scale={:.4f} EarlyStopSatis: {}".format(
+            #         epoch, float(loss),float(scale), early_stop.satis_num))
             writer.add_scalar('loss', float(loss), epoch)
             writer.add_scalar('learning_rate', float(
                 optimizer.state_dict()['param_groups'][0]['lr']), epoch)