---
library_name: transformers
license: gemma
base_model: google/gemma-7b
tags:
- alignment-handbook
- trl
- orpo
- generated_from_trainer
- trl
- orpo
- alignment-handbook
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
model-index:
- name: gemma-7b-orpo
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gemma-7b-orpo

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7559
- Rewards/chosen: -0.0650
- Rewards/rejected: -0.0764
- Rewards/accuracies: 0.5971
- Rewards/margins: 0.0114
- Logps/rejected: -1.5282
- Logps/chosen: -1.3004
- Logits/rejected: 266.0260
- Logits/chosen: 295.6202
- Nll Loss: 1.6941
- Log Odds Ratio: -0.6992
- Log Odds Chosen: 0.3721

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.3309        | 1.0   | 1259 | 1.4432          | -0.0513        | -0.0583          | 0.5468             | 0.0071          | -1.1666        | -1.0254      | 310.9833        | 338.2715      | 1.3964   | -0.7034        | 0.2119          |
| 0.647         | 2.0   | 2518 | 1.4816          | -0.0529        | -0.0637          | 0.5899             | 0.0108          | -1.2742        | -1.0583      | 296.0398        | 324.3109      | 1.4304   | -0.6778        | 0.3416          |
| 0.348         | 3.0   | 3777 | 1.7559          | -0.0650        | -0.0764          | 0.5971             | 0.0114          | -1.5282        | -1.3004      | 266.0260        | 295.6202      | 1.6941   | -0.6992        | 0.3721          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1