---
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_j-full-0912
  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_j-full-0912

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: 1.4395
- Rewards/chosen: -16.1609
- Rewards/rejected: -16.9344
- Rewards/accuracies: 0.6326
- Rewards/margins: 0.7735
- Logps/rejected: -169.3439
- Logps/chosen: -161.6093
- Logits/rejected: -0.3578
- Logits/chosen: -0.3883
- Nll Loss: 0.2841

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.7848        | 0.2311 | 100  | 1.6452          | -15.3752       | -15.7662         | 0.5804             | 0.3910          | -157.6625      | -153.7521    | -0.3516         | -0.3794       | 0.2719   |
| 1.5276        | 0.4623 | 200  | 1.5229          | -15.8100       | -16.4430         | 0.6043             | 0.6331          | -164.4303      | -158.0997    | -0.3983         | -0.4237       | 0.2748   |
| 1.4811        | 0.6934 | 300  | 1.4640          | -16.0706       | -16.8001         | 0.6130             | 0.7296          | -168.0013      | -160.7057    | -0.4069         | -0.4339       | 0.2804   |
| 1.4642        | 0.9246 | 400  | 1.4429          | -16.1577       | -16.9120         | 0.6304             | 0.7544          | -169.1204      | -161.5765    | -0.3509         | -0.3812       | 0.2845   |


### Framework versions

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