---
license: llama3
library_name: peft
tags:
- alignment-handbook
- trl
- orpo
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- mlabonne/orpo-dpo-mix-40k
model-index:
- name: llama-3-orpo-qlora
  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. -->

# llama-3-orpo-qlora

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: 1.0581
- Rewards/chosen: -0.0823
- Rewards/rejected: -0.2496
- Rewards/accuracies: 0.7879
- Rewards/margins: 0.1673
- Logps/rejected: -2.4958
- Logps/chosen: -0.8230
- Logits/rejected: -1.0347
- Logits/chosen: -0.9355
- Nll Loss: 1.0625
- Log Odds Ratio: -0.3947
- Log Odds Chosen: 2.1017

## 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: 77
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 5

### 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.2408        | 0.9998 | 1639 | 1.1078          | -0.0850        | -0.1592          | 0.7045             | 0.0742          | -1.5920        | -0.8498      | -0.9217         | -0.9313       | 1.1014   | -0.4987        | 1.0714          |
| 1.2158        | 1.9997 | 3278 | 1.0768          | -0.0818        | -0.1961          | 0.7273             | 0.1143          | -1.9613        | -0.8183      | -0.7536         | -0.7772       | 1.0726   | -0.4562        | 1.5271          |
| 1.0891        | 2.9995 | 4917 | 1.0654          | -0.0820        | -0.2184          | 0.7197             | 0.1365          | -2.1845        | -0.8200      | -0.9358         | -0.8876       | 1.0648   | -0.4458        | 1.7377          |
| 1.0521        | 3.9994 | 6556 | 1.0605          | -0.0824        | -0.2405          | 0.7727             | 0.1581          | -2.4049        | -0.8244      | -0.9998         | -0.8917       | 1.0630   | -0.4060        | 1.9929          |
| 1.0763        | 4.9992 | 8195 | 1.0581          | -0.0823        | -0.2496          | 0.7879             | 0.1673          | -2.4958        | -0.8230      | -1.0347         | -0.9355       | 1.0625   | -0.3947        | 2.1017          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1
- Datasets 2.19.2
- Tokenizers 0.19.1