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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
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
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: 1.6689
- Rewards/chosen: -15.0012
- Rewards/rejected: -15.8900
- Rewards/accuracies: 0.6336
- Rewards/margins: 0.8888
- Logps/rejected: -158.8998
- Logps/chosen: -150.0119
- Logits/rejected: -0.3381
- Logits/chosen: -0.3504
- Nll Loss: 0.4161
## 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: 5e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- total_eval_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.822 | 0.9238 | 100 | 1.7791 | -14.6496 | -15.4269 | 0.6034 | 0.7773 | -154.2694 | -146.4961 | -0.4235 | -0.4380 | 0.4058 |
| 1.5612 | 1.8476 | 200 | 1.6871 | -15.1337 | -15.9726 | 0.6379 | 0.8389 | -159.7256 | -151.3367 | -0.3722 | -0.3863 | 0.4197 |
| 1.3825 | 2.7714 | 300 | 1.6704 | -15.1684 | -16.0433 | 0.6293 | 0.8749 | -160.4333 | -151.6842 | -0.3369 | -0.3497 | 0.4209 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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