diff --git a/train_decoder.py b/train_decoder.py
index f06dadc..22ff816 100644
--- a/train_decoder.py
+++ b/train_decoder.py
@@ -323,7 +323,7 @@ def train(
         last_snapshot = sample
 
         if next_task == 'train':
-            for i, (img, emb, txt) in enumerate(trainer.train_loader):
+            for i, (img, emb, txt) in enumerate(dataloaders["train"]):
                 # We want to count the total number of samples across all processes
                 sample_length_tensor[0] = len(img)
                 all_samples = accelerator.gather(sample_length_tensor)  # TODO: accelerator.reduce is broken when this was written. If it is fixed replace this.
@@ -358,6 +358,7 @@ def train(
                         else:
                             # Then we need to pass the text instead
                             tokenized_texts = tokenize(txt, truncate=True)
+                            assert tokenized_texts.shape[0] == len(img), f"The number of texts ({tokenized_texts.shape[0]}) should be the same as the number of images ({len(img)})"
                             forward_params['text'] = tokenized_texts
                     loss = trainer.forward(img, **forward_params, unet_number=unet)
                     trainer.update(unet_number=unet)
@@ -416,7 +417,7 @@ def train(
             timer = Timer()
             accelerator.wait_for_everyone()
             i = 0
-            for i, (img, emb, txt) in enumerate(trainer.val_loader):  # Use the accelerate prepared loader
+            for i, (img, emb, txt) in enumerate(dataloaders['val']):  # Use the accelerate prepared loader
                 val_sample_length_tensor[0] = len(img)
                 all_samples = accelerator.gather(val_sample_length_tensor)
                 total_samples = all_samples.sum().item()