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---
license: llama3.1
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model-index:
- name: llama3.1_8b_dpo_bwgenerator_test2
  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_8b_dpo_bwgenerator_test2

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: 0.5181
- Rewards/chosen: -0.4278
- Rewards/rejected: -0.8508
- Rewards/accuracies: 0.9255
- Rewards/margins: 0.4230
- Logps/rejected: -118.6553
- Logps/chosen: -88.8263
- Logits/rejected: -0.9049
- Logits/chosen: -1.6027

## 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: 2e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6002        | 0.0719 | 1000  | 0.5390          | -0.3845        | -0.7489          | 0.9194             | 0.3644          | -117.6367      | -88.3940     | -0.9017         | -1.6013       |
| 0.5325        | 0.1438 | 2000  | 0.5237          | -0.4184        | -0.8254          | 0.9200             | 0.4070          | -118.4018      | -88.7330     | -0.9052         | -1.6035       |
| 0.5221        | 0.2157 | 3000  | 0.5199          | -0.4201        | -0.8376          | 0.9210             | 0.4175          | -118.5239      | -88.7496     | -0.9038         | -1.6021       |
| 0.518         | 0.2876 | 4000  | 0.5178          | -0.4376        | -0.8621          | 0.9220             | 0.4246          | -118.7688      | -88.9242     | -0.9056         | -1.6036       |
| 0.5177        | 0.3595 | 5000  | 0.5176          | -0.4317        | -0.8563          | 0.9213             | 0.4246          | -118.7104      | -88.8652     | -0.9063         | -1.6039       |
| 0.5186        | 0.4313 | 6000  | 0.5180          | -0.4361        | -0.8604          | 0.9200             | 0.4243          | -118.7512      | -88.9096     | -0.9063         | -1.6040       |
| 0.522         | 0.5032 | 7000  | 0.5175          | -0.4358        | -0.8614          | 0.9210             | 0.4255          | -118.7612      | -88.9070     | -0.9057         | -1.6035       |
| 0.5194        | 0.5751 | 8000  | 0.5182          | -0.4280        | -0.8506          | 0.9249             | 0.4226          | -118.6538      | -88.8285     | -0.9039         | -1.6020       |
| 0.5149        | 0.6470 | 9000  | 0.5179          | -0.4413        | -0.8651          | 0.9229             | 0.4238          | -118.7981      | -88.9612     | -0.9060         | -1.6038       |
| 0.5209        | 0.7189 | 10000 | 0.5178          | -0.4355        | -0.8600          | 0.9216             | 0.4244          | -118.7471      | -88.9040     | -0.9049         | -1.6027       |
| 0.517         | 0.7908 | 11000 | 0.5187          | -0.4343        | -0.8561          | 0.9194             | 0.4217          | -118.7081      | -88.8918     | -0.9046         | -1.6027       |
| 0.5202        | 0.8627 | 12000 | 0.5186          | -0.4321        | -0.8540          | 0.9197             | 0.4220          | -118.6880      | -88.8693     | -0.9047         | -1.6026       |
| 0.5212        | 0.9346 | 13000 | 0.5181          | -0.4278        | -0.8508          | 0.9255             | 0.4230          | -118.6553      | -88.8263     | -0.9049         | -1.6027       |


### Framework versions

- PEFT 0.10.0
- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.14.7
- Tokenizers 0.19.1