stf Example not working #1693
Description
Current version:
commit 84156f1 (HEAD -> main, origin/main, origin/HEAD)
updated on Jun 3 2024
I tired to run the following script in example/scripts/stf.py:
# regular:
python examples/scripts/sft.py \
--model_name_or_path="facebook/opt-350m" \
--report_to="wandb" \
--learning_rate=1.41e-5 \
--per_device_train_batch_size=64 \
--gradient_accumulation_steps=16 \
--output_dir="sft_openassistant-guanaco" \
--logging_steps=1 \
--num_train_epochs=3 \
--max_steps=-1 \
--push_to_hub \
--gradient_checkpointingError message:
Map: 0%| | 0/9846 [00:00<?, ? examples/s]
Traceback (most recent call last):
File "/Users/tatoaoliang/Downloads/Work/trl/examples/scripts/sft.py", line 137, in <module>
trainer = SFTTrainer(
^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/huggingface_hub/utils/_deprecation.py", line 101, in inner_f
return f(*args, **kwargs)
^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/trl/trl/trainer/sft_trainer.py", line 360, in __init__
train_dataset = self._prepare_dataset(
^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/trl/trl/trainer/sft_trainer.py", line 506, in _prepare_dataset
return self._prepare_non_packed_dataloader(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/trl/trl/trainer/sft_trainer.py", line 574, in _prepare_non_packed_dataloader
tokenized_dataset = dataset.map(
^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 602, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 567, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3156, in map
for rank, done, content in Dataset._map_single(**dataset_kwargs):
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3548, in _map_single
batch = apply_function_on_filtered_inputs(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3417, in apply_function_on_filtered_inputs
processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/trl/trl/trainer/sft_trainer.py", line 545, in tokenize
element[dataset_text_field] if not use_formatting_func else formatting_func(element),
~~~~~~~^^^^^^^^^^^^^^^^^^^^
File "/Users/tatoaoliang/Downloads/Work/virv/llama/lib/python3.11/site-packages/datasets/formatting/formatting.py", line 271, in __getitem__
value = self.data[key]
~~~~~~~~~^^^^^
KeyError: None
I check the codes, here is the original snippet of _prepare_non_packed_dataloader function in "trl/trainer/sft_trainer.py" 529 line:
def _prepare_non_packed_dataloader(
self,
tokenizer,
dataset,
dataset_text_field,
max_seq_length,
formatting_func=None,
add_special_tokens=True,
remove_unused_columns=True,
):
#### debugger told me that formatting_func is None and dataset_text_field is None
use_formatting_func = formatting_func is not None and dataset_text_field is None
self._dataset_sanity_checked = False
#### so use_formatting_func is False
# Inspired from: https://huggingface.co/learn/nlp-course/chapter7/6?fw=pt
def tokenize(element):
outputs = tokenizer(
element[dataset_text_field] if not use_formatting_func else formatting_func(element),
add_special_tokens=add_special_tokens,
truncation=True,
padding=False,
max_length=max_seq_length,
return_overflowing_tokens=False,
return_length=False,
)So it seems that formatting_func should not be None.
it is defined in sft_trainer.py , line 313
formatting_func = get_formatting_func_from_dataset(train_dataset, tokenizer)
and get_formatting_func_from_dataset is in trl/extras/dataset_formatting.py, line 60:
def get_formatting_func_from_dataset(
dataset: Union[Dataset, ConstantLengthDataset], tokenizer: AutoTokenizer
) -> Optional[Callable]:
r"""
Finds the correct formatting function based on the dataset structure. Currently supported datasets are:
- `ChatML` with [{"role": str, "content": str}]
- `instruction` with [{"prompt": str, "completion": str}]
Args:
dataset (Dataset): User dataset
tokenizer (AutoTokenizer): Tokenizer used for formatting
Returns:
Callable: Formatting function if the dataset format is supported else None
"""
if isinstance(dataset, Dataset):
if "messages" in dataset.features:
if dataset.features["messages"] == FORMAT_MAPPING["chatml"]:
logging.info("Formatting dataset with chatml format")
return conversations_formatting_function(tokenizer, "messages")
if "conversations" in dataset.features:
if dataset.features["conversations"] == FORMAT_MAPPING["chatml"]:
logging.info("Formatting dataset with chatml format")
return conversations_formatting_function(tokenizer, "conversations")
elif dataset.features == FORMAT_MAPPING["instruction"]:
logging.info("Formatting dataset with instruction format")
return instructions_formatting_function(tokenizer)
return NoneBut openassistant-guanaco dataset only has the feature "text", so it is incompatible.
https://huggingface.co/datasets/timdettmers/openassistant-guanaco?row=0