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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_j-full-0912
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-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
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