---
base_model: meta-llama/Meta-Llama-3-8B
library_name: peft
license: llama3
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: ft-Llama3-8b-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. -->

# ft-Llama3-8b-orpo

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the mlabonne/orpo-dpo-mix-40k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8983
- Rewards/chosen: -0.0999
- Rewards/rejected: -0.1748
- Rewards/accuracies: 0.4000
- Rewards/margins: 0.0749
- Logps/rejected: -1.7478
- Logps/chosen: -0.9993
- Logits/rejected: -1.5466
- Logits/chosen: -1.5315
- Nll Loss: 0.8281
- Log Odds Ratio: -0.7026
- Log Odds Chosen: 0.7314

## 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: 8e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.6579        | 0.2   | 25   | 1.2469          | -0.1560        | -0.2318          | 0.5                | 0.0758          | -2.3180        | -1.5595      | -1.2300         | -1.0199       | 1.1776   | -0.6935        | 0.7440          |
| 1.1014        | 0.4   | 50   | 1.0297          | -0.1262        | -0.1994          | 0.5                | 0.0732          | -1.9942        | -1.2621      | -1.4006         | -1.3743       | 0.9587   | -0.7096        | 0.7137          |
| 0.9391        | 0.61  | 75   | 0.9463          | -0.1106        | -0.1844          | 0.5                | 0.0738          | -1.8440        | -1.1062      | -1.5970         | -1.5504       | 0.8754   | -0.7083        | 0.7185          |
| 0.676         | 0.81  | 100  | 0.8983          | -0.0999        | -0.1748          | 0.4000             | 0.0749          | -1.7478        | -0.9993      | -1.5466         | -1.5315       | 0.8281   | -0.7026        | 0.7314          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.4.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2