---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- trl
- cpo
- generated_from_trainer
- trl
- cpo
- generated_from_trainer
datasets:
- princeton-nlp/llama3-ultrafeedback
model-index:
- name: llama3.1-cpo-full
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3.1-cpo-full

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the princeton-nlp/llama3-ultrafeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6689
- Rewards/chosen: -15.0012
- Rewards/rejected: -15.8900
- Rewards/accuracies: 0.6336
- Rewards/margins: 0.8888
- Logps/rejected: -158.8998
- Logps/chosen: -150.0119
- Logits/rejected: -0.3381
- Logits/chosen: -0.3504
- Nll Loss: 0.4161

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.822         | 0.9238 | 100  | 1.7791          | -14.6496       | -15.4269         | 0.6034             | 0.7773          | -154.2694      | -146.4961    | -0.4235         | -0.4380       | 0.4058   |
| 1.5612        | 1.8476 | 200  | 1.6871          | -15.1337       | -15.9726         | 0.6379             | 0.8389          | -159.7256      | -151.3367    | -0.3722         | -0.3863       | 0.4197   |
| 1.3825        | 2.7714 | 300  | 1.6704          | -15.1684       | -16.0433         | 0.6293             | 0.8749          | -160.4333      | -151.6842    | -0.3369         | -0.3497       | 0.4209   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1