--- /content/acoustic-model/train.py	2022-09-03 22:51:08.632610312 -0700
+++ train(3).py	2022-09-03 23:15:29.700072538 -0700
@@ -17,7 +17,7 @@
 from acoustic.utils import Metric, save_checkpoint, load_checkpoint, plot_spectrogram
 
 
-logging.basicConfig(level=logging.DEBUG)
+logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 ########################################################################################
@@ -28,10 +28,10 @@
 LEARNING_RATE = 4e-4
 BETAS = (0.8, 0.99)
 WEIGHT_DECAY = 1e-5
-STEPS = 80000
+STEPS = 20000
 LOG_INTERVAL = 5
-VALIDATION_INTERVAL = 1000
-CHECKPOINT_INTERVAL = 1000
+VALIDATION_INTERVAL = 2000
+CHECKPOINT_INTERVAL = 2000
 BACKEND = "nccl"
 INIT_METHOD = "tcp://localhost:54321"
 
@@ -200,6 +200,19 @@
             # Start validation loop
             # --------------------------------------------------------------------------#
 
+
+
+            if global_step % CHECKPOINT_INTERVAL == 0:
+              save_checkpoint(
+                checkpoint_dir=args.checkpoint_dir,
+                acoustic=acoustic,
+                optimizer=optimizer,
+                step=global_step,
+                loss=validation_loss.value,
+                best=9999,
+                logger=logger,
+            )
+
             if global_step % VALIDATION_INTERVAL == 0:
                 acoustic.eval()
                 validation_loss.reset()
@@ -242,22 +255,7 @@
                         f"valid -- epoch: {epoch}, loss: {validation_loss.value:.4f}"
                     )
 
-                new_best = best_loss > validation_loss.value
-                if new_best or global_step % CHECKPOINT_INTERVAL:
-                    if new_best:
-                        logger.info("-------- new best model found!")
-                        best_loss = validation_loss.value
-
-                    if rank == 0:
-                        save_checkpoint(
-                            checkpoint_dir=args.checkpoint_dir,
-                            acoustic=acoustic,
-                            optimizer=optimizer,
-                            step=global_step,
-                            loss=validation_loss.value,
-                            best=new_best,
-                            logger=logger,
-                        )
+              
 
             # -----------------------------------------------------------------------------#
             # End validation loop