---
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:
- silviasapora/low_quality_dpo7k
model-index:
- name: gemma-7b-borpo-low-quality-v4
  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-low-quality-v4

This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the silviasapora/low_quality_dpo7k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8577
- Rewards/chosen: -0.5993
- Rewards/rejected: -0.7602
- Rewards/accuracies: 0.6143
- Rewards/margins: 0.1610
- Logps/rejected: -1.5205
- Logps/chosen: -1.1986
- Logits/rejected: 240.3907
- Logits/chosen: 301.1215
- Nll Loss: 1.5532
- Log Odds Ratio: -0.6421
- Log Odds Chosen: 0.4396

## 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: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.8227        | 1.0   | 84   | 1.9616          | -0.6050        | -0.6743          | 0.5                | 0.0693          | -1.3486        | -1.2099      | 257.8447        | 315.1940      | 1.6719   | -0.6903        | 0.1646          |
| 1.4803        | 2.0   | 168  | 1.7681          | -0.5462        | -0.6508          | 0.5286             | 0.1046          | -1.3017        | -1.0924      | 274.3526        | 328.0207      | 1.4854   | -0.6718        | 0.2561          |
| 0.9109        | 3.0   | 252  | 1.8577          | -0.5993        | -0.7602          | 0.6143             | 0.1610          | -1.5205        | -1.1986      | 240.3907        | 301.1215      | 1.5532   | -0.6421        | 0.4396          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1