RuntimeError: unscale_() has already been called on this optimizer since the last update().
It mentions this fine-tuning notebook like:

https://colab.research.google.com/#fileId=https%3A//huggingface.co/dfurman/falcon-7b-chat-oasst1/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb

full stack:
```
Traceback (most recent call last):
  File "/home/llama/train_infer/finetune_falcon7b_oasst1_with_bnb_peft.py", line 204, in <module>
    trainer.train()
  File "/home/.conda/envs/3.9/lib/python3.9/site-packages/transformers/trainer.py", line 1638, in train
    return inner_training_loop(
  File "/home/.conda/envs/3.9/lib/python3.9/site-packages/accelerate/utils/memory.py", line 132, in decorator
    return function(batch_size, *args, **kwargs)
  File "/home/.conda/envs/3.9/lib/python3.9/site-packages/transformers/trainer.py", line 1972, in _inner_training_loop
    self.accelerator.clip_grad_norm_(
  File "/home/.conda/envs/3.9/lib/python3.9/site-packages/accelerate/accelerator.py", line 1892, in clip_grad_norm_
    self.unscale_gradients()
  File "/home/.conda/envs/3.9/lib/python3.9/site-packages/accelerate/accelerator.py", line 1855, in unscale_gradients
    self.scaler.unscale_(opt)
  File "/home/.conda/envs/3.9/lib/python3.9/site-packages/torch/cuda/amp/grad_scaler.py", line 275, in unscale_
    raise RuntimeError("unscale_() has already been called on this optimizer since the last update().")
RuntimeError: unscale_() has already been called on this optimizer since the last update().
```

refs https://github.com/huggingface/transformers/pull/23914, I had upgraded the transformers to the latest commit.

- `transformers` version: 4.30.0.dev0
- `Platform`: Linux-5.15.0-73-generic-x86_64-with-glibc2.31
- `Python version`: 3.9.16
- `Safetensors` version: 0.3.1
- `PyTorch` version (GPU): 2.0.1+cu117 (True)
- `peft` version:  0.4.0.dev0
- `accelerate`  version:  0.20.0.dev0
- `bitsandbytes`  version: 0.39.0

How to slove it?
Can you try restarting your runtime after installing the new version to see if that fixes it? CC @pacman100 <|||||>I'm following up this notebook: https://huggingface.co/dfurman/falcon-7b-chat-oasst1/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb

and getting this dump when training:

`File [/workspace/generative_models/.venv/lib/python3.10/site-packages/accelerate/accelerator.py:1873](https://vscode-remote+ssh-002dremote.vscode-resource.vscode-cdn.net/workspace/generative_models/.venv/lib/python3.10/site-packages/accelerate/accelerator.py:1873), in Accelerator.clip_grad_norm_(self, parameters, max_norm, norm_type)
   1869 elif self.distributed_type == DistributedType.DEEPSPEED:
   1870     # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed
   1871     # We cannot return the gradient norm because DeepSpeed does it.
   1872     return None
-> 1873 self.unscale_gradients()
   1874 return torch.nn.utils.clip_grad_norm_(parameters, max_norm, norm_type=norm_type)

File [/workspace/generative_models/.venv/lib/python3.10/site-packages/accelerate/accelerator.py:1836](https://vscode-remote+ssh-002dremote.vscode-resource.vscode-cdn.net/workspace/generative_models/.venv/lib/python3.10/site-packages/accelerate/accelerator.py:1836), in Accelerator.unscale_gradients(self, optimizer)
   1834 while isinstance(opt, AcceleratedOptimizer):
   1835     opt = opt.optimizer
-> 1836 self.scaler.unscale_(opt)

File [/workspace/generative_models/.venv/lib/python3.10/site-packages/torch/cuda/amp/grad_scaler.py:275](https://vscode-remote+ssh-002dremote-.vscode-resource.vscode-cdn.net/workspace/generative_models/.venv/lib/python3.10/site-packages/torch/cuda/amp/grad_scaler.py:275), in GradScaler.unscale_(self, optimizer)
    272 optimizer_state = self._per_optimizer_states[id(optimizer)]
    274 if optimizer_state["stage"] is OptState.UNSCALED:
--> 275     raise RuntimeError("unscale_() has already been called on this optimizer since the last update().")
    276 elif optimizer_state["stage"] is OptState.STEPPED:
    277     raise RuntimeError("unscale_() is being called after step().")

RuntimeError: unscale_() has already been called on this optimizer since the last update().`

These are the libraries versions I have:
transformers @ git+https://github.com/huggingface/transformers.git@f1660d7e23d4432513fe060bde4f9b7b29f05204
peft @ git+https://github.com/huggingface/peft.git@7fb5f90a38cb39a31396de7e638ead9ecea692af
accelerate @ git+https://github.com/huggingface/accelerate.git@62357f218f72cce88b8e086cc372b15c119b590b

I have restarted and followed (to the best of my knowledge) the guidance to correct this. @pacman100 

Thank you!

<|||||>I am getting this as well.
Tried restarting the notebook but that doesn't fix it

This was working previously. Today ran a fresh install using 

`!pip install -q git+https://github.com/huggingface/peft.git git+https://github.com/huggingface/transformers.git`<|||||>> Can you try restarting your runtime after installing the new version to see if that fixes it? CC @pacman100

@muellerzr thanks a lot. I have restarted the kernel and tried repeatedly according to the operation, but the problem still exists.<|||||>I am facing the same issue. Tried doing a fresh install still the issue persists.<|||||>Hi all, 
I was able to rerun my workflow via:

1. Deleting the current runtime
2. Starting a new runtime
3. Running using `pip install transformers`<|||||>> 3\. pip install transformers

Hi, @lfunderburk  can you share the version of each library？thanks a lot.<|||||>`transformers==4.29.2` and `tokenizers==0.13.3` on Python 3.10.11

Below is the rest of the dependencies

```
absl-py==1.4.0
accelerate==0.20.0.dev0
aiohttp==3.8.4
aiosignal==1.3.1
alabaster==0.7.13
albumentations==1.2.1
altair==4.2.2
anyio==3.6.2
appdirs==1.4.4
argon2-cffi==21.3.0
argon2-cffi-bindings==21.2.0
array-record==0.2.0
arviz==0.15.1
astropy==5.2.2
astunparse==1.6.3
async-timeout==4.0.2
attrs==23.1.0
audioread==3.0.0
autograd==1.5
Babel==2.12.1
backcall==0.2.0
beautifulsoup4==4.11.2
bitsandbytes==0.39.0
bleach==6.0.0
blis==0.7.9
blosc2==2.0.0
bokeh==2.4.3
branca==0.6.0
build==0.10.0
CacheControl==0.12.11
cached-property==1.5.2
cachetools==5.3.0
catalogue==2.0.8
certifi==2022.12.7
cffi==1.15.1
chardet==4.0.0
charset-normalizer==2.0.12
chex==0.1.7
click==8.1.3
cloudpickle==2.2.1
cmake==3.25.2
cmdstanpy==1.1.0
colorcet==3.0.1
colorlover==0.3.0
community==1.0.0b1
confection==0.0.4
cons==0.4.5
contextlib2==0.6.0.post1
contourpy==1.0.7
convertdate==2.4.0
cryptography==40.0.2
cufflinks==0.17.3
cupy-cuda11x==11.0.0
cvxopt==1.3.0
cvxpy==1.3.1
cycler==0.11.0
cymem==2.0.7
Cython==0.29.34
dask==2022.12.1
datascience==0.17.6
datasets==2.12.0
db-dtypes==1.1.1
dbus-python==1.2.16
debugpy==1.6.6
decorator==4.4.2
defusedxml==0.7.1
dill==0.3.6
distributed==2022.12.1
dlib==19.24.1
dm-tree==0.1.8
docutils==0.16
dopamine-rl==4.0.6
duckdb==0.7.1
earthengine-api==0.1.350
easydict==1.10
ecos==2.0.12
editdistance==0.6.2
en-core-web-sm==3.5.0
entrypoints==0.4
ephem==4.1.4
et-xmlfile==1.1.0
etils==1.2.0
etuples==0.3.8
exceptiongroup==1.1.1
fastai==2.7.12
fastcore==1.5.29
fastdownload==0.0.7
fastjsonschema==2.16.3
fastprogress==1.0.3
fastrlock==0.8.1
filelock==3.12.0
firebase-admin==5.3.0
Flask==2.2.4
flatbuffers==23.3.3
flax==0.6.9
folium==0.14.0
fonttools==4.39.3
frozendict==2.3.7
frozenlist==1.3.3
fsspec==2023.4.0
future==0.18.3
gast==0.4.0
GDAL==3.3.2
gdown==4.6.6
gensim==4.3.1
geographiclib==2.0
geopy==2.3.0
gin-config==0.5.0
glob2==0.7
google==2.0.3
google-api-core==2.11.0
google-api-python-client==2.84.0
google-auth==2.17.3
google-auth-httplib2==0.1.0
google-auth-oauthlib==1.0.0
google-cloud-bigquery==3.9.0
google-cloud-bigquery-storage==2.19.1
google-cloud-core==2.3.2
google-cloud-datastore==2.15.1
google-cloud-firestore==2.11.0
google-cloud-language==2.9.1
google-cloud-storage==2.8.0
google-cloud-translate==3.11.1
google-colab==1.0.0
google-crc32c==1.5.0
google-pasta==0.2.0
google-resumable-media==2.5.0
googleapis-common-protos==1.59.0
googledrivedownloader==0.4
graphviz==0.20.1
greenlet==2.0.2
grpcio==1.54.0
grpcio-status==1.48.2
gspread==3.4.2
gspread-dataframe==3.0.8
gym==0.25.2
gym-notices==0.0.8
h5netcdf==1.1.0
h5py==3.8.0
holidays==0.25
holoviews==1.15.4
html5lib==1.1
httpimport==1.3.0
httplib2==0.21.0
huggingface-hub==0.15.1
humanize==4.6.0
hyperopt==0.2.7
idna==3.4
imageio==2.25.1
imageio-ffmpeg==0.4.8
imagesize==1.4.1
imbalanced-learn==0.10.1
imgaug==0.4.0
importlib-resources==5.12.0
imutils==0.5.4
inflect==6.0.4
iniconfig==2.0.0
intel-openmp==2023.1.0
ipykernel==5.5.6
ipython==7.34.0
ipython-genutils==0.2.0
ipython-sql==0.4.1
ipywidgets==7.7.1
itsdangerous==2.1.2
jax==0.4.10
jaxlib==0.4.10+cuda11.cudnn86
jieba==0.42.1
Jinja2==3.1.2
joblib==1.2.0
jsonpickle==3.0.1
jsonschema==4.3.3
jupyter-client==6.1.12
jupyter-console==6.1.0
jupyter_core==5.3.0
jupyter-server==1.24.0
jupyterlab-pygments==0.2.2
jupyterlab-widgets==3.0.7
kaggle==1.5.13
keras==2.12.0
kiwisolver==1.4.4
korean-lunar-calendar==0.3.1
langcodes==3.3.0
lazy_loader==0.2
libclang==16.0.0
librosa==0.10.0.post2
lightgbm==3.3.5
lit==16.0.5
llvmlite==0.39.1
locket==1.0.0
logical-unification==0.4.5
loralib==0.1.1
LunarCalendar==0.0.9
lxml==4.9.2
Markdown==3.4.3
markdown-it-py==2.2.0
MarkupSafe==2.1.2
matplotlib==3.7.1
matplotlib-inline==0.1.6
matplotlib-venn==0.11.9
mdurl==0.1.2
miniKanren==1.0.3
missingno==0.5.2
mistune==0.8.4
mizani==0.8.1
mkl==2019.0
ml-dtypes==0.1.0
mlxtend==0.14.0
more-itertools==9.1.0
moviepy==1.0.3
mpmath==1.3.0
msgpack==1.0.5
multidict==6.0.4
multipledispatch==0.6.0
multiprocess==0.70.14
multitasking==0.0.11
murmurhash==1.0.9
music21==8.1.0
natsort==8.3.1
nbclient==0.7.4
nbconvert==6.5.4
nbformat==5.8.0
nest-asyncio==1.5.6
networkx==3.1
nibabel==3.0.2
nltk==3.8.1
notebook==6.4.8
numba==0.56.4
numexpr==2.8.4
numpy==1.22.4
oauth2client==4.1.3
oauthlib==3.2.2
opencv-contrib-python==4.7.0.72
opencv-python==4.7.0.72
opencv-python-headless==4.7.0.72
openpyxl==3.0.10
opt-einsum==3.3.0
optax==0.1.5
orbax-checkpoint==0.2.1
osqp==0.6.2.post8
packaging==23.1
palettable==3.3.3
pandas==1.5.3
pandas-datareader==0.10.0
pandas-gbq==0.17.9
pandocfilters==1.5.0
panel==0.14.4
param==1.13.0
parso==0.8.3
partd==1.4.0
pathlib==1.0.1
pathy==0.10.1
patsy==0.5.3
peft==0.4.0.dev0
pexpect==4.8.0
pickleshare==0.7.5
Pillow==8.4.0
pip==23.1.2
pip-tools==6.13.0
platformdirs==3.3.0
plotly==5.13.1
plotnine==0.10.1
pluggy==1.0.0
polars==0.17.3
pooch==1.6.0
portpicker==1.3.9
prefetch-generator==1.0.3
preshed==3.0.8
prettytable==0.7.2
proglog==0.1.10
progressbar2==4.2.0
prometheus-client==0.16.0
promise==2.3
prompt-toolkit==3.0.38
prophet==1.1.3
proto-plus==1.22.2
protobuf==3.20.3
psutil==5.9.5
psycopg2==2.9.6
ptyprocess==0.7.0
py-cpuinfo==9.0.0
py4j==0.10.9.7
pyarrow==9.0.0
pyasn1==0.5.0
pyasn1-modules==0.3.0
pycocotools==2.0.6
pycparser==2.21
pyct==0.5.0
pydantic==1.10.7
pydata-google-auth==1.7.0
pydot==1.4.2
pydot-ng==2.0.0
pydotplus==2.0.2
PyDrive==1.3.1
pyerfa==2.0.0.3
pygame==2.3.0
Pygments==2.14.0
PyGObject==3.36.0
pymc==5.1.2
PyMeeus==0.5.12
pymystem3==0.2.0
PyOpenGL==3.1.6
pyparsing==3.0.9
pyproject_hooks==1.0.0
pyrsistent==0.19.3
PySocks==1.7.1
pytensor==2.10.1
pytest==7.2.2
python-apt==0.0.0
python-dateutil==2.8.2
python-louvain==0.16
python-slugify==8.0.1
python-utils==3.5.2
pytz==2022.7.1
pytz-deprecation-shim==0.1.0.post0
pyviz-comms==2.2.1
PyWavelets==1.4.1
PyYAML==6.0
pyzmq==23.2.1
qdldl==0.1.7
qudida==0.0.4
regex==2022.10.31
requests==2.27.1
requests-oauthlib==1.3.1
requests-unixsocket==0.2.0
requirements-parser==0.5.0
responses==0.18.0
rich==13.3.4
rpy2==3.5.5
rsa==4.9
scikit-image==0.19.3
scikit-learn==1.2.2
scipy==1.10.1
scs==3.2.3
seaborn==0.12.2
Send2Trash==1.8.0
setuptools==67.7.2
shapely==2.0.1
six==1.16.0
sklearn-pandas==2.2.0
smart-open==6.3.0
sniffio==1.3.0
snowballstemmer==2.2.0
sortedcontainers==2.4.0
soundfile==0.12.1
soupsieve==2.4.1
soxr==0.3.5
spacy==3.5.2
spacy-legacy==3.0.12
spacy-loggers==1.0.4
Sphinx==3.5.4
sphinxcontrib-applehelp==1.0.4
sphinxcontrib-devhelp==1.0.2
sphinxcontrib-htmlhelp==2.0.1
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==1.0.3
sphinxcontrib-serializinghtml==1.1.5
SQLAlchemy==2.0.10
sqlparse==0.4.4
srsly==2.4.6
statsmodels==0.13.5
sympy==1.11.1
tables==3.8.0
tabulate==0.8.10
tblib==1.7.0
tenacity==8.2.2
tensorboard==2.12.2
tensorboard-data-server==0.7.0
tensorboard-plugin-wit==1.8.1
tensorflow==2.12.0
tensorflow-datasets==4.9.2
tensorflow-estimator==2.12.0
tensorflow-gcs-config==2.12.0
tensorflow-hub==0.13.0
tensorflow-io-gcs-filesystem==0.32.0
tensorflow-metadata==1.13.1
tensorflow-probability==0.20.1
tensorstore==0.1.36
termcolor==2.3.0
terminado==0.17.1
text-unidecode==1.3
textblob==0.17.1
tf-slim==1.1.0
thinc==8.1.9
threadpoolctl==3.1.0
tifffile==2023.4.12
tinycss2==1.2.1
tokenizers==0.13.3
toml==0.10.2
tomli==2.0.1
toolz==0.12.0
torch==2.0.1+cu118
torchaudio==2.0.2+cu118
torchdata==0.6.1
torchsummary==1.5.1
torchtext==0.15.2
torchvision==0.15.2+cu118
tornado==6.3.1
tqdm==4.65.0
traitlets==5.7.1
transformers==4.29.2
triton==2.0.0
tweepy==4.13.0
typer==0.7.0
types-setuptools==67.8.0.0
typing_extensions==4.5.0
tzdata==2023.3
tzlocal==4.3
uritemplate==4.1.1
urllib3==1.26.15
vega-datasets==0.9.0
wasabi==1.1.1
wcwidth==0.2.6
webcolors==1.13
webencodings==0.5.1
websocket-client==1.5.1
Werkzeug==2.3.0
wheel==0.40.0
widgetsnbextension==3.6.4
wordcloud==1.8.2.2
wrapt==1.14.1
xarray==2022.12.0
xarray-einstats==0.5.1
xgboost==1.7.5
xlrd==2.0.1
xxhash==3.2.0
yarl==1.9.2
yellowbrick==1.5
yfinance==0.2.18
zict==3.0.0
zipp==3.15.0
```<|||||>Hello everyone, I found the cause to be `auto_find_batch_size=True`. In the meantime, please confirm disabling it and passing small `per_device_train_batch_size =4` works (I can confirm). I'm working on a PR to resolve this. 

![Screenshot 2023-06-07 at 12 37 13 PM](https://github.com/huggingface/transformers/assets/13534540/d0765b4c-77c8-4b38-bfb3-80fdfb09a9a1)

<|||||>> Hello everyone, I found the cause to be `auto_find_batch_size=True`. In the meantime, please confirm disabling it and passing small `per_device_train_batch_size =4` works (I can confirm). I'm working on a PR to resolve this.
> 
> ![Screenshot 2023-06-07 at 12 37 13 PM](https://user-images.githubusercontent.com/13534540/243952303-d0765b4c-77c8-4b38-bfb3-80fdfb09a9a1.png)

Seems it is working with those changes in parameters (20 min training so far... previously it cancelled at about 4). THANKS!<|||||>@FedericoMontana this has also been fixed with the latest Accelerate release I believe, worst case you can use `pip install git+https://github.com/huggingface/accelerate` until we release the patch, and you can use `auto_find_batch_size=True`<|||||>I am still facing this issue. 
```
  File "/home/kunal/miniconda3/envs/lora/lib/python3.10/site-packages/transformers/trainer.py", line 1843, in _inner_training_loop                                                                                                   
    self.accelerator.clip_grad_norm_(                                                                                                                                                                                                
  File "/home/kunal/miniconda3/envs/lora/lib/python3.10/site-packages/accelerate/accelerator.py", line 1913, in clip_grad_norm_                                                                                                      
    self.unscale_gradients()                                                                                                                                                                                                         
  File "/home/kunal/miniconda3/envs/lora/lib/python3.10/site-packages/accelerate/accelerator.py", line 1876, in unscale_gradients                                                                                                    
    self.scaler.unscale_(opt)                                                                                                                                                                                                        
  File "/home/kunal/miniconda3/envs/lora/lib/python3.10/site-packages/torch/cuda/amp/grad_scaler.py", line 275, in unscale_                                                                                                          
    raise RuntimeError("unscale_() has already been called on this optimizer since the last update().")                                                                                                                              
RuntimeError: unscale_() has already been called on this optimizer since the last update().
```
This issue doesnt exist in `transformers@de9255de27abfcae4a1f816b904915f0b1e23cd9`, but I cannot use that build due to `UnboundLocalError: local variable 'load_result' referenced before assignment` error.
Environment:
```
- `transformers` version: 4.31.0.dev0
- Platform: Linux-6.3.9-zen1-1-zen-x86_64-with-glibc2.37
- Python version: 3.10.11
- Huggingface_hub version: 0.15.1
- Safetensors version: 0.3.1
- PyTorch version (GPU?): 2.0.1+cu118 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No
```<|||||>@kunaldeo, provide a minimal reproducible example post installing Transformers and Accelerate from Main branch. That would be helpful for us to deep dive.<|||||>This is working now.