When to use a DataCollator for SFTTrainer
Hello,In the SFTTrainer document, it is stated that if the dataset is in the right format, we dont need to specify a DataCollator with a response_template.However, after I formatted my dataset with the TinyLlama/TinyLlama-1.1B-Chat-v1.0 tokenizer.apply_chat_template, the labels are not correct in the train dataloader.Here is a sample from the dataloader of the SFTTrainer:( I removed the <(s)> )Input : <|user|>Which is bigger, the moon or the sun?'<|assistant|> The sun.Inputs_ids : tensor([    1,   529, 29989,  1792, 29989, 29958,    13,  8809,   436,   338,16600, 29892,   278, 18786,   470,   278,  6575, 29973,     2, 29871,13, 29966, 29989,   465, 22137, 29989, 29958,    13,  1576,  6575,29889,     2, 29871,    13,     2,     2,     2,     2])Labels : tensor([    1,   529, 29989,  1792, 29989, 29958,    13,  8809,   436,   338,16600, 29892,   278, 18786,   470,   278,  6575, 29973,  -100, 29871,13, 29966, 29989,   465, 22137, 29989, 29958,    13,  1576,  6575,29889,  -100, 29871,    13,  -100,  -100,  -100,  -100])Is the labels supposed to be like that ? Or is it incorrect ?