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

# OrpoLlama-3-8B-Instruct

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0517
- Rewards/chosen: -0.0621
- Rewards/rejected: -0.0634
- Rewards/accuracies: 0.6000
- Rewards/margins: 0.0013
- Logps/rejected: -0.6340
- Logps/chosen: -0.6207
- Logits/rejected: -0.2825
- Logits/chosen: -0.2736
- Nll Loss: 0.9848
- Log Odds Ratio: -0.6691
- Log Odds Chosen: 0.1127

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 2.2564        | 0.5980 | 74   | 1.8521          | -0.1306        | -0.1270          | 0.6000             | -0.0036         | -1.2696        | -1.3055      | -0.4912         | -0.5850       | 1.7776   | -0.7454        | -0.0391         |
| 1.8749        | 1.1960 | 148  | 1.3145          | -0.0855        | -0.0879          | 0.6000             | 0.0024          | -0.8795        | -0.8553      | -0.2945         | -0.2832       | 1.2482   | -0.6628        | 0.1091          |
| 1.1933        | 1.7939 | 222  | 1.1033          | -0.0662        | -0.0667          | 0.6000             | 0.0005          | -0.6671        | -0.6624      | -0.2268         | -0.2101       | 1.0354   | -0.6787        | 0.0828          |
| 0.8761        | 2.3919 | 296  | 1.0517          | -0.0621        | -0.0634          | 0.6000             | 0.0013          | -0.6340        | -0.6207      | -0.2825         | -0.2736       | 0.9848   | -0.6691        | 0.1127          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1