---
base_model: princeton-nlp/Llama-3-Base-8B-SFT
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
model-index:
- name: llama3-dpo-lora
  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-dpo-lora

This model is a fine-tuned version of [princeton-nlp/Llama-3-Base-8B-SFT](https://huggingface.co/princeton-nlp/Llama-3-Base-8B-SFT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5193
- Rewards/chosen: 0.0154
- Rewards/rejected: -0.7979
- Rewards/accuracies: 0.7280
- Rewards/margins: 0.8133
- Logps/rejected: -284.6558
- Logps/chosen: -292.3936
- Logits/rejected: -0.3843
- Logits/chosen: -0.4157

## 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-06
- train_batch_size: 1
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6275        | 0.1047 | 100  | 0.6122          | 0.2594         | -0.0099          | 0.6920             | 0.2693          | -276.7753      | -289.9533    | -0.5582         | -0.5619       |
| 0.5726        | 0.2094 | 200  | 0.5529          | -0.0787        | -0.6353          | 0.7040             | 0.5565          | -283.0293      | -293.3344    | -0.5103         | -0.5266       |
| 0.5429        | 0.3141 | 300  | 0.5380          | -0.1730        | -0.8455          | 0.7260             | 0.6725          | -285.1317      | -294.2773    | -0.4689         | -0.4910       |
| 0.5054        | 0.4187 | 400  | 0.5332          | -0.0870        | -0.8469          | 0.7240             | 0.7599          | -285.1459      | -293.4173    | -0.4261         | -0.4535       |
| 0.5508        | 0.5234 | 500  | 0.5267          | -0.0207        | -0.8088          | 0.7180             | 0.7881          | -284.7646      | -292.7540    | -0.4045         | -0.4335       |
| 0.5338        | 0.6281 | 600  | 0.5263          | 0.1981         | -0.5901          | 0.7300             | 0.7882          | -282.5771      | -290.5659    | -0.4002         | -0.4304       |
| 0.5064        | 0.7328 | 700  | 0.5175          | -0.2007        | -1.0076          | 0.7300             | 0.8068          | -286.7521      | -294.5546    | -0.3761         | -0.4080       |
| 0.5349        | 0.8375 | 800  | 0.5197          | 0.0149         | -0.7896          | 0.7200             | 0.8045          | -284.5727      | -292.3984    | -0.3853         | -0.4161       |
| 0.4775        | 0.9422 | 900  | 0.5181          | 0.0150         | -0.7988          | 0.7260             | 0.8139          | -284.6649      | -292.3968    | -0.3842         | -0.4151       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.44.2
- Pytorch 2.2.1+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1