---
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-0911
  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-0911

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: 1.5984
- Rewards/chosen: -14.3945
- Rewards/rejected: -15.5836
- Rewards/accuracies: 0.6304
- Rewards/margins: 1.1892
- Logps/rejected: -155.8365
- Logps/chosen: -143.9448
- Logits/rejected: -0.3142
- Logits/chosen: -0.3408
- Nll Loss: 0.3937

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.5867        | 0.9986 | 432  | 1.5248          | -16.0094       | -16.9746         | 0.6587             | 0.9652          | -169.7457      | -160.0941    | -0.4783         | -0.5128       | 0.4373   |
| 0.7108        | 1.9994 | 865  | 1.5252          | -14.8375       | -15.9459         | 0.6500             | 1.1084          | -159.4588      | -148.3749    | -0.4403         | -0.4684       | 0.4056   |
| 0.4426        | 2.9957 | 1296 | 1.5984          | -14.3945       | -15.5836         | 0.6304             | 1.1892          | -155.8365      | -143.9448    | -0.3142         | -0.3408       | 0.3937   |


### Framework versions

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