I am training a simple encoder-decoder transformer model on a text-to-text translation task. I am using Seq2SeqTrainingArguments
class. It works fine when I am not using the label_smoothing
argument. When I add label_smoothing=0.1
, I get the following error:
ValueError Traceback (most recent call last)
Cell In[29], line 81
74 trainer = MySeq2SeqTrainer(
75 model=model,
76 args=trainer_args,
77 train_dataset=train_dataset,
78 eval_dataset=dev_dataset
79 )
-> 81 trainer.train()
File /data/envs/hugface/lib/python3.8/site-packages/transformers/trainer.py:1501, in Trainer.train(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)
1496 self.model_wrapped = self.model
1498 inner_training_loop = find_executable_batch_size(
1499 self._inner_training_loop, self._train_batch_size, args.auto_find_batch_size
1500 )
-> 1501 return inner_training_loop(
1502 args=args,
1503 resume_from_checkpoint=resume_from_checkpoint,
1504 trial=trial,
1505 ignore_keys_for_eval=ignore_keys_for_eval,
1506 )
File /data/envs/hugface/lib/python3.8/site-packages/transformers/trainer.py:1749, in Trainer._inner_training_loop(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)
...
return forward_call(*input, **kwargs)
File "/data/envs/hugface/lib/python3.8/site-packages/transformers/models/bert/modeling_bert.py", line 966, in forward
raise ValueError("You have to specify either input_ids or inputs_embeds")
ValueError: You have to specify either input_ids or inputs_embeds
I am not able to figure out what is causing this issue.