Add print

inference.py

@@ -76,7 +76,7 @@ input_as_dataset = Code.preprocess.tokenizer_new(tokenizer, data_sample, max_len
 
 model = Code.models.WordClassificationModel("bert-base-uncased")
 
-model_path = "saved_models/bert.pth"
+model_path = "Code/saved_models/bert.pth"
 model = torch.load(model_path, map_location=device)
 
 model.eval()
@@ -85,6 +85,7 @@ train_sampler = RandomSampler(data_sample)
 train_dataloader = DataLoader(data_sample, sampler=train_sampler, batch_size=1)
 
 for batch in train_dataloader:
+	print(batch)
 	inputs = {'input_ids': batch[0],
 					'attention_mask': batch[1],
 					'token_type_ids': batch[2],