---
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-orpo-low-quality
  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-low-quality

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: 1.5517
- Rewards/chosen: -0.0554
- Rewards/rejected: -0.0646
- Rewards/accuracies: 0.5612
- Rewards/margins: 0.0092
- Logps/rejected: -1.2920
- Logps/chosen: -1.1085
- Logits/rejected: 268.0282
- Logits/chosen: 297.1682
- Nll Loss: 1.4855
- Log Odds Ratio: -0.6970
- Log Odds Chosen: 0.2856

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.436         | 0.9955 | 167  | 1.4679          | -0.0508        | -0.0571          | 0.5468             | 0.0063          | -1.1420        | -1.0158      | 288.9292        | 318.3812      | 1.4121   | -0.6895        | 0.1983          |
| 1.1098        | 1.9970 | 335  | 1.4451          | -0.0518        | -0.0579          | 0.5468             | 0.0061          | -1.1581        | -1.0353      | 286.4312        | 315.0296      | 1.3839   | -0.7228        | 0.2105          |
| 0.5921        | 2.9866 | 501  | 1.5517          | -0.0554        | -0.0646          | 0.5612             | 0.0092          | -1.2920        | -1.1085      | 268.0282        | 297.1682      | 1.4855   | -0.6970        | 0.2856          |


### Framework versions

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