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---
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 |