---
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: data/Meta-Llama-3-8B-Instruct-Merged
model-index:
- name: Meta-Llama-3-8B-Instruct-DPO-QLoRA
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/statking/huggingface/runs/ficbttt2)
# Meta-Llama-3-8B-Instruct-DPO-QLoRA

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4785
- Rewards/chosen: -2.3086
- Rewards/rejected: -3.5093
- Rewards/accuracies: 0.7740
- Rewards/margins: 1.2007
- Logps/rejected: -604.1885
- Logps/chosen: -507.2548
- Logits/rejected: -0.8544
- Logits/chosen: -0.8360

## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6865        | 0.0523 | 100  | 0.6857          | 0.0202         | 0.0036           | 0.6810             | 0.0166          | -252.9014      | -274.3707    | -0.6048         | -0.5953       |
| 0.5773        | 0.1047 | 200  | 0.5802          | -0.5398        | -0.9390          | 0.7080             | 0.3992          | -347.1614      | -330.3779    | -0.9408         | -0.9089       |
| 0.546         | 0.1570 | 300  | 0.5337          | -0.9951        | -1.7352          | 0.7370             | 0.7401          | -426.7812      | -375.9071    | -1.0937         | -1.0510       |
| 0.501         | 0.2094 | 400  | 0.5120          | -1.8215        | -2.7617          | 0.7530             | 0.9401          | -529.4277      | -458.5479    | -1.1011         | -1.0595       |
| 0.4525        | 0.2617 | 500  | 0.5090          | -1.9857        | -3.0848          | 0.7510             | 1.0991          | -561.7446      | -474.9624    | -0.9430         | -0.9134       |
| 0.508         | 0.3141 | 600  | 0.5005          | -2.2106        | -3.1511          | 0.7600             | 0.9405          | -568.3763      | -497.4550    | -0.9955         | -0.9626       |
| 0.4852        | 0.3664 | 700  | 0.5028          | -1.3971        | -2.4127          | 0.7770             | 1.0156          | -494.5317      | -416.1026    | -0.9794         | -0.9476       |
| 0.5474        | 0.4187 | 800  | 0.4966          | -1.7948        | -2.7637          | 0.7670             | 0.9689          | -529.6284      | -455.8714    | -0.9115         | -0.8851       |
| 0.5246        | 0.4711 | 900  | 0.4943          | -1.5285        | -2.5416          | 0.7660             | 1.0131          | -507.4219      | -429.2431    | -0.8138         | -0.7980       |
| 0.4635        | 0.5234 | 1000 | 0.4908          | -2.8177        | -4.0337          | 0.7630             | 1.2160          | -656.6334      | -558.1610    | -0.8713         | -0.8521       |
| 0.4856        | 0.5758 | 1100 | 0.4817          | -2.3661        | -3.4921          | 0.7720             | 1.1260          | -602.4694      | -512.9990    | -0.8044         | -0.7913       |
| 0.5013        | 0.6281 | 1200 | 0.4860          | -2.1162        | -3.2907          | 0.7720             | 1.1745          | -582.3287      | -488.0108    | -0.7890         | -0.7745       |
| 0.4497        | 0.6805 | 1300 | 0.4850          | -2.4840        | -3.7371          | 0.7730             | 1.2531          | -626.9694      | -524.7895    | -0.8096         | -0.7940       |
| 0.4734        | 0.7328 | 1400 | 0.4833          | -2.1466        | -3.3699          | 0.7740             | 1.2233          | -590.2520      | -491.0496    | -0.8148         | -0.7990       |
| 0.4482        | 0.7851 | 1500 | 0.4812          | -2.5061        | -3.7160          | 0.7760             | 1.2100          | -624.8656      | -527.0021    | -0.8423         | -0.8246       |
| 0.4982        | 0.8375 | 1600 | 0.4787          | -2.2293        | -3.3886          | 0.7770             | 1.1593          | -592.1224      | -499.3264    | -0.8377         | -0.8203       |
| 0.4594        | 0.8898 | 1700 | 0.4790          | -2.3679        | -3.5723          | 0.7730             | 1.2044          | -610.4911      | -513.1796    | -0.8566         | -0.8379       |
| 0.4551        | 0.9422 | 1800 | 0.4786          | -2.3275        | -3.5261          | 0.7730             | 1.1986          | -605.8722      | -509.1397    | -0.8587         | -0.8397       |
| 0.4605        | 0.9945 | 1900 | 0.4785          | -2.3086        | -3.5093          | 0.7740             | 1.2007          | -604.1885      | -507.2548    | -0.8544         | -0.8360       |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1