---
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-0913
  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. -->

# llama3.1-cpo_j-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: 1.4404
- Rewards/chosen: -16.0845
- Rewards/rejected: -16.8741
- Rewards/accuracies: 0.6326
- Rewards/margins: 0.7896
- Logps/rejected: -168.7413
- Logps/chosen: -160.8449
- Logits/rejected: -0.3487
- Logits/chosen: -0.3704
- Nll Loss: 0.2790

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.7833        | 0.2311 | 100  | 1.6389          | -15.3939       | -15.7792         | 0.5783             | 0.3853          | -157.7921      | -153.9390    | -0.3065         | -0.3333       | 0.2678   |
| 1.5321        | 0.4623 | 200  | 1.5242          | -15.8988       | -16.5121         | 0.5978             | 0.6132          | -165.1206      | -158.9884    | -0.4244         | -0.4423       | 0.2764   |
| 1.4722        | 0.6934 | 300  | 1.4633          | -16.0803       | -16.8141         | 0.6217             | 0.7338          | -168.1411      | -160.8031    | -0.3641         | -0.3856       | 0.2790   |
| 1.4589        | 0.9246 | 400  | 1.4447          | -16.0215       | -16.8041         | 0.6261             | 0.7826          | -168.0413      | -160.2150    | -0.3389         | -0.3606       | 0.2798   |


### Framework versions

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