---
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-0913
  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-0913

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: 1.5934
- Rewards/chosen: -15.4936
- Rewards/rejected: -16.2190
- Rewards/accuracies: 0.6261
- Rewards/margins: 0.7255
- Logps/rejected: -162.1901
- Logps/chosen: -154.9355
- Logits/rejected: -0.4926
- Logits/chosen: -0.5160
- Nll Loss: 0.4228

## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.9304        | 0.2311 | 100  | 1.7873          | -14.9945       | -15.3576         | 0.5804             | 0.3632          | -153.5762      | -149.9445    | -0.3649         | -0.3854       | 0.4085   |
| 1.6908        | 0.4623 | 200  | 1.6702          | -15.6437       | -16.2439         | 0.5978             | 0.6002          | -162.4385      | -156.4369    | -0.3777         | -0.4014       | 0.4252   |
| 1.6317        | 0.6934 | 300  | 1.6162          | -15.4682       | -16.1519         | 0.6152             | 0.6837          | -161.5185      | -154.6818    | -0.4753         | -0.4948       | 0.4202   |
| 1.62          | 0.9246 | 400  | 1.5947          | -15.5964       | -16.3155         | 0.6261             | 0.7192          | -163.1553      | -155.9637    | -0.4910         | -0.5144       | 0.4262   |


### Framework versions

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