# KeyError:664 with Seq2Seq trainer() **URL:** **Author:** ![Meltoneous](https://avatars.discourse-cdn.com/v4/letter/m/ea666f/32.png) [@Meltoneous](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FMeltoneous)%5C **Post date:** [July 11, 2023, 5:01pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fkeyerror-664-with-seq2seq-trainer%2F46463%2F1 "2023-07-11T17:01:49Z") Hello all, I have two columns of data which I have loaded as a df and then dfs for training\_set, testing\_set, and a val\_set. I keep getting the error posted below. I’ve tried resetting indexes, reindexing… Any ideas? Thank you very much! The code block is: training\_args = Seq2SeqTrainingArguments( output\_dir=“TESTING”, evaluation\_strategy=“epoch”, learning\_rate=2e-5, per\_device\_train\_batch\_size=16, per\_device\_eval\_batch\_size=4, weight\_decay=0.01, save\_total\_limit=3, num\_train\_epochs=2, fp16=True, predict\_with\_generate=True, ) trainer = Seq2SeqTrainer( model=model, args=training\_args, train\_dataset=train\_set, eval\_dataset=val\_set, tokenizer=tokenizer, data\_collator=data\_collator, compute\_metrics=compute\_metrics ) trainer.train() The error is: ╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮ │ /usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py:3802 in get\_loc │ │ │ │ 3799 │ │ │ │ ) │ │ 3800 │ │ │ casted\_key = self.\_maybe\_cast\_indexer(key) │ │ 3801 │ │ │ try: │ │ ❱ 3802 │ │ │ │ return self.\_engine.get\_loc(casted\_key) │ │ 3803 │ │ │ except KeyError as err: │ │ 3804 │ │ │ │ raise KeyError(key) from err │ │ 3805 │ │ │ except TypeError: │ │ │ │ in pandas.\_libs.index.IndexEngine.get\_loc:138 │ │ │ │ in pandas.\_libs.index.IndexEngine.get\_loc:165 │ │ │ │ in pandas.\_libs.hashtable.PyObjectHashTable.get\_item:5745 │ │ │ │ in pandas.\_libs.hashtable.PyObjectHashTable.get\_item:5753 │ ╰──────────────────────────────────────────────────────────────────────────────────────────────────╯ KeyError: 664 The above exception was the direct cause of the following exception: ╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮ │ in \:25 │ │ │ │ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1645 in train │ │ │ │ 1642 │ │ inner\_training\_loop = find\_executable\_batch\_size( │ │ 1643 │ │ │ self.\_inner\_training\_loop, self.\_train\_batch\_size, args.auto\_find\_batch\_size │ │ 1644 │ │ ) │ │ ❱ 1645 │ │ return inner\_training\_loop( │ │ 1646 │ │ │ args=args, │ │ 1647 │ │ │ resume\_from\_checkpoint=resume\_from\_checkpoint, │ │ 1648 │ │ │ trial=trial, │ │ │ │ /usr/local/lib/python3.10/dist-packages/transformers/trainer.py:1916 in \_inner\_training\_loop │ │ │ │ 1913 │ │ │ │ rng\_to\_sync = True │ │ 1914 │ │ │ │ │ 1915 │ │ │ step = -1 │ │ ❱ 1916 │ │ │ for step, inputs in enumerate(epoch\_iterator): │ │ 1917 │ │ │ │ total\_batched\_samples += 1 │ │ 1918 │ │ │ │ if rng\_to\_sync: │ │ 1919 │ │ │ │ │ self.\_load\_rng\_state(resume\_from\_checkpoint) │ │ │ │ /usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:633 in **next** │ │ │ │ 630 │ │ │ if self.\_sampler\_iter is None: │ │ 631 │ │ │ │ # TODO([Bug in dataloader iterator found by mypy · Issue #76750 · pytorch/pytorch · GitHub](https://github.com/pytorch/pytorch/issues/76750)) │ │ 632 │ │ │ │ self.\_reset() # type: ignore[call-arg] │ │ ❱ 633 │ │ │ data = self.\_next\_data() │ │ 634 │ │ │ self.\_num\_yielded += 1 │ │ 635 │ │ │ if self.\_dataset\_kind == \_DatasetKind.Iterable and \ │ │ 636 │ │ │ │ │ self.\_IterableDataset\_len\_called is not None and \ │ │ │ │ /usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py:677 in \_next\_data │ │ │ │ 674 │ │ │ 675 │ def \_next\_data(self): │ │ 676 │ │ index = self.\_next\_index() # may raise StopIteration │ │ ❱ 677 │ │ data = self.\_dataset\_fetcher.fetch(index) # may raise StopIteration │ │ 678 │ │ if self.\_pin\_memory: │ │ 679 │ │ │ data = \_utils.pin\_memory.pin\_memory(data, self.\_pin\_memory\_device) │ │ 680 │ │ return data │ │ │ │ /usr/local/lib/python3.10/dist-packages/torch/utils/data/\_utils/fetch.py:51 in fetch │ │ │ │ 48 │ │ │ if hasattr(self.dataset, “ **getitems** ”) and self.dataset. **getitems** : │ │ 49 │ │ │ │ data = self.dataset. **getitems** (possibly\_batched\_index) │ │ 50 │ │ │ else: │ │ ❱ 51 │ │ │ │ data = [self.dataset[idx] for idx in possibly\_batched\_index] │ │ 52 │ │ else: │ │ 53 │ │ │ data = self.dataset[possibly\_batched\_index] │ │ 54 │ │ return self.collate\_fn(data) │ │ │ │ /usr/local/lib/python3.10/dist-packages/torch/utils/data/\_utils/fetch.py:51 in │ │ │ │ 48 │ │ │ if hasattr(self.dataset, “ **getitems** ”) and self.dataset. **getitems** : │ │ 49 │ │ │ │ data = self.dataset. **getitems** (possibly\_batched\_index) │ │ 50 │ │ │ else: │ │ ❱ 51 │ │ │ │ data = [self.dataset[idx] for idx in possibly\_batched\_index] │ │ 52 │ │ else: │ │ 53 │ │ │ data = self.dataset[possibly\_batched\_index] │ │ 54 │ │ return self.collate\_fn(data) │ │ │ │ /usr/local/lib/python3.10/dist-packages/pandas/core/frame.py:3807 in **getitem** │ │ │ │ 3804 │ │ if is\_single\_key: │ │ 3805 │ │ │ if self.columns.nlevels \> 1: │ │ 3806 │ │ │ │ return self.\_getitem\_multilevel(key) │ │ ❱ 3807 │ │ │ indexer = self.columns.get\_loc(key) │ │ 3808 │ │ │ if is\_integer(indexer): │ │ 3809 │ │ │ │ indexer = [indexer] │ │ 3810 │ │ else: │ │ │ │ /usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py:3804 in get\_loc │ │ │ │ 3801 │ │ │ try: │ │ 3802 │ │ │ │ return self.\_engine.get\_loc(casted\_key) │ │ 3803 │ │ │ except KeyError as err: │ │ ❱ 3804 │ │ │ │ raise KeyError(key) from err │ │ 3805 │ │ │ except TypeError: │ │ 3806 │ │ │ │ # If we have a listlike key, \_check\_indexing\_error will raise │ │ 3807 │ │ │ │ # InvalidIndexError. Otherwise we fall through and re-raise │ ╰──────────────────────────────────────────────────────────────────────────────────────────────────╯ KeyError: 664