---
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: 1.1648
- Rewards/chosen: -0.0603
- Rewards/rejected: -0.0824
- Rewards/accuracies: 0.5
- Rewards/margins: 0.0221
- Logps/rejected: -0.8240
- Logps/chosen: -0.6033
- Logits/rejected: -0.1024
- Logits/chosen: -0.2381
- Nll Loss: 1.1016
- Log Odds Ratio: -0.6324
- Log Odds Chosen: 0.4547

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 0.95          | 0.5980 | 74   | 1.2436          | -0.0675        | -0.0830          | 0.4000             | 0.0155          | -0.8295        | -0.6746      | -0.2051         | -0.3444       | 1.1740   | -0.6961        | 0.2761          |
| 0.9613        | 1.1960 | 148  | 1.1952          | -0.0621        | -0.0799          | 0.4000             | 0.0179          | -0.7994        | -0.6209      | -0.1256         | -0.2699       | 1.1280   | -0.6717        | 0.3516          |
| 1.5258        | 1.7939 | 222  | 1.1740          | -0.0609        | -0.0818          | 0.5                | 0.0209          | -0.8183        | -0.6094      | -0.1255         | -0.2648       | 1.1099   | -0.6414        | 0.4267          |
| 1.1971        | 2.3919 | 296  | 1.1648          | -0.0603        | -0.0824          | 0.5                | 0.0221          | -0.8240        | -0.6033      | -0.1024         | -0.2381       | 1.1016   | -0.6324        | 0.4547          |


### Framework versions

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