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

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: 1.5984
- Rewards/chosen: -0.0575
- Rewards/rejected: -0.0699
- Rewards/accuracies: 0.5899
- Rewards/margins: 0.0124
- Logps/rejected: -1.3977
- Logps/chosen: -1.1506
- Logits/rejected: 270.9628
- Logits/chosen: 299.8625
- Nll Loss: 1.5312
- Log Odds Ratio: -0.6761
- Log Odds Chosen: 0.3679

## 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: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.4516        | 0.9968 | 157  | 1.4765          | -0.0513        | -0.0577          | 0.5468             | 0.0064          | -1.1547        | -1.0260      | 293.8872        | 321.9495      | 1.4282   | -0.6924        | 0.1911          |
| 1.0587        | 2.0    | 315  | 1.4250          | -0.0502        | -0.0595          | 0.5468             | 0.0093          | -1.1904        | -1.0035      | 296.0850        | 323.6012      | 1.3729   | -0.6901        | 0.2723          |
| 0.5897        | 2.9905 | 471  | 1.5984          | -0.0575        | -0.0699          | 0.5899             | 0.0124          | -1.3977        | -1.1506      | 270.9628        | 299.8625      | 1.5312   | -0.6761        | 0.3679          |


### Framework versions

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