Main
Author: SumitdevelopAI
Pull request: yes

* tmp commit

* tmp commit

* make fixup

* missing removal

* fix condition

* fix end-to-end compilation

* if -> elif

* BC

* BC

* use @deprecate_kwarg("num_hidden_layers", version="4.47.0")

* wups the import

* 🥴

---------

Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>

# What does this PR do?

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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
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      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

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Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @ylacombe, @eustlb
- graph models: @clefourrier

Library:

- flax: @sanchit-gandhi
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

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- Flax: @sanchit-gandhi
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Comments:
> 😅 should I close this?

This was my first open source Contribution. I do not understand the process can you help and tell me right or wrong.

What issue are you trying to solve?

> What issue are you trying to solve?

### Improving Model Robustness Against Adversarial Attacks

### Vulnerability to Adversarial Attacks
**_Machine learning models, including RoBERTa, can be susceptible to adversarial attacks where slight, often imperceptible, modifications to input data can significantly alter model predictions. These attacks exploit weaknesses in the model's decision boundaries, leading to incorrect classifications._**

### Adversarial Training with FGSM
_**We generate adversarial examples that intentionally perturb the input data by implementing the Fast Gradient Sign Method (FGSM). Training the model with these adversarial examples helps it learn to resist such manipulations, thereby strengthening its robustness.**_

### Enhanced Generalization
 **Robustness against adversarial attacks often correlates with better generalization on unseen data. By mitigating the model's susceptibility to adversarial inputs, we improve its ability to perform consistently across diverse datasets.**

Any Update you check  

I am sorry I just don't understand what's going on here 😅 

Closing!