---
base_model: google/gemma-4-E4B-it
library_name: transformers
model_name: trainer_output
tags:
- generated_from_trainer
- rloo
- trl
licence: license
---

# Model Card for trainer_output

This model is a fine-tuned version of [google/gemma-4-E4B-it](https://huggingface.co/google/gemma-4-E4B-it).
It has been trained using [TRL](https://github.com/huggingface/trl).

## Quick start

```python
from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="leobianco/trainer_output", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])
```

## Training procedure

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/leobianco-universit-paris-saclay/perl_hallucination-src/runs/47q0i9sm) 



This model was trained with RLOO, a method introduced in [Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs](https://huggingface.co/papers/2402.14740).

### Framework versions

- TRL: 1.9.2
- Transformers: 5.14.1
- Pytorch: 2.11.0
- Datasets: 5.0.1
- Tokenizers: 0.22.2

## Citations

Cite RLOO as:

```bibtex
@inproceedings{ahmadian2024back,
    title        = {{Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs}},
    author       = {Arash Ahmadian and Chris Cremer and Matthias Gall{'{e}} and Marzieh Fadaee and Julia Kreutzer and Olivier Pietquin and Ahmet {"{U}}st{"{u}}n and Sara Hooker},
    year         = 2024,
    booktitle    = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), {ACL} 2024, Bangkok, Thailand, August 11-16, 2024},
    pages        = {12248--12267},
    publisher    = {Association for Computational Linguistics},
    editor       = {Lun{-}Wei Ku and Andre Martins and Vivek Srikumar},
}
```

Cite TRL as:
    
```bibtex
@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}
```