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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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