---
library_name: transformers
license: llama3.1
base_model: oxford-llms/llama3-1-ox-llms-8b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
model-index:
- name: llama3-1-ox-llms-8b-dpo-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-ox-llms-8b-dpo-full

This model is a fine-tuned version of [oxford-llms/llama3-1-ox-llms-8b-sft-full](https://huggingface.co/oxford-llms/llama3-1-ox-llms-8b-sft-full) on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4831
- Rewards/chosen: -0.2543
- Rewards/rejected: -1.0940
- Rewards/accuracies: 0.7708
- Rewards/margins: 0.8397
- Logps/rejected: -340.3136
- Logps/chosen: -325.1967
- Logits/rejected: -1.3101
- Logits/chosen: -1.3085

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.528         | 0.9479 | 100  | 0.5267          | -0.0255        | -0.6055          | 0.7604             | 0.5800          | -330.5430      | -320.6201    | -1.3169         | -1.3159       |
| 0.3731        | 1.8957 | 200  | 0.4821          | -0.2481        | -1.0900          | 0.7604             | 0.8419          | -340.2323      | -325.0733    | -1.3099         | -1.3082       |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3