---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct_dpo_sg_values_p025_OA_gold
  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. -->

# Llama-3.1-8B-Instruct_dpo_sg_values_p025_OA_gold

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the dpo_sg_values_p025_OA_gold dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1369
- Rewards/chosen: -0.3243
- Rewards/rejected: -3.7445
- Rewards/accuracies: 0.9400
- Rewards/margins: 3.4202
- Logps/chosen: -5.3343
- Logps/rejected: -44.0676
- Logits/chosen: -0.8235
- Logits/rejected: -0.8529

## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
| 0.677         | 0.1495 | 250  | 0.6611          | -0.0030        | -0.0688          | 0.8780             | 0.0658          | -2.1210      | -7.3104        | -0.6673       | -0.6792         |
| 0.4141        | 0.2990 | 500  | 0.3328          | -0.1370        | -1.2934          | 0.8960             | 1.1564          | -3.4617      | -19.5564       | -0.7405       | -0.7604         |
| 0.1869        | 0.4486 | 750  | 0.1943          | -0.3266        | -2.7983          | 0.9280             | 2.4718          | -5.3572      | -34.6058       | -0.8272       | -0.8525         |
| 0.1234        | 0.5981 | 1000 | 0.1579          | -0.3430        | -3.2984          | 0.9380             | 2.9554          | -5.5213      | -39.6065       | -0.8336       | -0.8610         |
| 0.122         | 0.7476 | 1250 | 0.1439          | -0.3187        | -3.5609          | 0.9360             | 3.2422          | -5.2784      | -42.2310       | -0.8265       | -0.8553         |
| 0.0821        | 0.8971 | 1500 | 0.1398          | -0.3263        | -3.7101          | 0.9340             | 3.3838          | -5.3544      | -43.7234       | -0.8241       | -0.8535         |


### Framework versions

- PEFT 0.15.2
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 2.21.0
- Tokenizers 0.21.1