---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- trl
- cpo
- generated_from_trainer
model-index:
- name: llama3.1-cpo_j-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_j-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4373
- Rewards/chosen: -14.1493
- Rewards/rejected: -15.5710
- Rewards/accuracies: 0.6543
- Rewards/margins: 1.4217
- Logps/rejected: -155.7095
- Logps/chosen: -141.4926
- Logits/rejected: -0.1136
- Logits/chosen: -0.1476
- Nll Loss: 0.1725

## 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: 5

### 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
| 1.4367        | 0.9986 | 432  | 1.3926          | -17.0679       | -18.0962         | 0.6565             | 1.0283          | -180.9624      | -170.6792    | -0.4080         | -0.4373       | 0.3200   |
| 0.5472        | 1.9994 | 865  | 1.2973          | -16.2909       | -17.5852         | 0.6587             | 1.2944          | -175.8523      | -162.9086    | -0.5434         | -0.5688       | 0.2148   |
| 0.2244        | 2.9980 | 1297 | 1.3861          | -15.7105       | -17.2195         | 0.6565             | 1.5089          | -172.1945      | -157.1052    | -0.3428         | -0.3715       | 0.2034   |
| 0.1472        | 3.9988 | 1730 | 1.4029          | -14.6462       | -16.1385         | 0.6522             | 1.4923          | -161.3849      | -146.4623    | -0.2701         | -0.3029       | 0.1876   |
| 0.1143        | 4.9928 | 2160 | 1.4373          | -14.1493       | -15.5710         | 0.6543             | 1.4217          | -155.7095      | -141.4926    | -0.1136         | -0.1476       | 0.1725   |


### Framework versions

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