---
base_model: google/gemma-2-9b-it
tags:
  - alignment-handbook
  - generated_from_trainer
datasets:
  - princeton-nlp/gemma2-ultrafeedback-armorm
model-index:
  - name: Sunshine279/gammaPO-gemma-2-9b-it
    results: []
license: mit
---

## Model Details

### Model Description

We fine-tuned [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on [princeton-nlp/gemma2-ultrafeedback-armorm](https://huggingface.co/datasets/princeton-nlp/gemma2-ultrafeedback-armorm) with the gamma-SimPO objective.

 - Developed by: Jie Sun, Junkang Wu, Jiancan Wu, Zhibo Zhu, Xingyu Lu, Jun Zhou, Lintao Ma, Xiang Wang

 - Model type: Causal Language Model

 - License: gemma

 - Finetuned from model: google/gemma-2-9b-it

### Model Sources

 - Repository: https://github.com/sunjie279/gammaPO

 - Paper: https://arxiv.org/pdf/2506.03690

### How to Get Started with the Model

```python
import torch
from transformers import pipeline

model_id = "Sunshine279/gammaPO-gemma-2-9b-it"

generator = pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device="cuda",
)
outputs = generator([{"role": "user", "content": "What's the difference between llamas and alpacas?"}],
                      do_sample=False,
                      eos_token_id=[generator.tokenizer.convert_tokens_to_ids("<end_of_turn>"), generator.tokenizer.eos_token_id],
                      max_new_tokens=200)
print(outputs[0]['generated_text'])
```

## Training details

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 8e-07
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2.5863        | 0.8594 | 400  | 2.5622          | -18.1350       | -23.0307         | 0.7828             | 4.8958          | -2.3031        | -1.8135      | -15.8316        | -15.8114      |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1