---
base_model: meta-llama/Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- llama-factory
- lora
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-SAA-600
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3.1-8B-Instruct-SAA-600

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 bct_non_cot_dpo_600 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0943
- Rewards/chosen: -0.0072
- Rewards/rejected: -0.0623
- Rewards/accuracies: 0.8833
- Rewards/margins: 0.0551
- Logps/rejected: -0.6233
- Logps/chosen: -0.0722
- Logits/rejected: -0.4048
- Logits/chosen: -0.3432
- Sft Loss: 0.0119
- Odds Ratio Loss: 0.8243

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_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: 10.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
| 1.3352        | 1.4815 | 50   | 1.0317          | -0.0989        | -0.1576          | 0.8333             | 0.0587          | -1.5758        | -0.9889      | -0.4812         | -0.4002       | 0.1167   | 9.1492          |
| 0.2371        | 2.9630 | 100  | 0.1655          | -0.0135        | -0.0699          | 0.8833             | 0.0564          | -0.6987        | -0.1348      | -0.4551         | -0.3813       | 0.0177   | 1.4782          |
| 0.1421        | 4.4444 | 150  | 0.1010          | -0.0077        | -0.0577          | 0.8833             | 0.0500          | -0.5773        | -0.0770      | -0.4107         | -0.3473       | 0.0124   | 0.8869          |
| 0.1291        | 5.9259 | 200  | 0.0984          | -0.0075        | -0.0594          | 0.8833             | 0.0518          | -0.5936        | -0.0752      | -0.4066         | -0.3442       | 0.0123   | 0.8613          |
| 0.1246        | 7.4074 | 250  | 0.0943          | -0.0072        | -0.0623          | 0.8833             | 0.0551          | -0.6233        | -0.0722      | -0.4048         | -0.3432       | 0.0119   | 0.8243          |
| 0.1045        | 8.8889 | 300  | 0.0948          | -0.0072        | -0.0628          | 0.8833             | 0.0555          | -0.6277        | -0.0724      | -0.4046         | -0.3432       | 0.0119   | 0.8292          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.45.2
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.20.0