---
library_name: transformers
base_model: llama-3-8b-base-sft-hh-helpful-4xh200-batch-64
tags:
- alignment-handbook
- margin-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: llama-3-8b-base-margin-dpo-hh-helpful-4xh200-batch-64-20260417-212312
  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-3-8b-base-margin-dpo-hh-helpful-4xh200-batch-64-20260417-212312

This model is a fine-tuned version of [llama-3-8b-base-sft-hh-helpful-4xh200-batch-64](https://huggingface.co/llama-3-8b-base-sft-hh-helpful-4xh200-batch-64) on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4055
- Margin Dpo/beta: 0.1000
- Margin Dpo/loss Margin Mean: 21.7395
- Margin Dpo/beta Margin Mean: 2.1740
- Margin Dpo/beta Margin Std: 2.6342
- Margin Dpo/beta Margin Grad Mean: -0.2573
- Margin Dpo/beta Margin Grad Std: 0.2541
- Margin Dpo/margin Mean: 21.7395
- Margin Dpo/margin Std: 26.3422
- Logps/chosen: -105.8801
- Logps/rejected: -135.3665
- Logps/ref Chosen: -79.0510
- Logps/ref Rejected: -86.7979
- Logits/chosen: -0.6200
- Logits/rejected: -0.5940

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Margin Dpo/beta | Margin Dpo/loss Margin Mean | Margin Dpo/beta Margin Mean | Margin Dpo/beta Margin Std | Margin Dpo/beta Margin Grad Mean | Margin Dpo/beta Margin Grad Std | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:---------------:|:---------------------------:|:---------------------------:|:--------------------------:|:--------------------------------:|:-------------------------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 0.9045        | 0.1468 | 100  | 0.5612          | 0.1000          | 8.4438                      | 0.8444                      | 1.5441                     | -0.3672                          | 0.2312                          | 8.4438                 | 15.4407               | -87.2143     | -103.4049      | -79.0510         | -86.7979           | -0.6444       | -0.6169         |
| 0.6573        | 0.2937 | 200  | 0.4777          | 0.1000          | 14.6731                     | 1.4673                      | 2.1103                     | -0.3106                          | 0.2466                          | 14.6731                | 21.1032               | -92.9744     | -115.3944      | -79.0510         | -86.7979           | -0.6438       | -0.6210         |
| 0.7096        | 0.4405 | 300  | 0.4405          | 0.1000          | 18.1127                     | 1.8113                      | 2.3747                     | -0.2825                          | 0.2514                          | 18.1127                | 23.7469               | -100.1293    | -125.9889      | -79.0510         | -86.7979           | -0.6160       | -0.5900         |
| 0.4494        | 0.5874 | 400  | 0.4219          | 0.1000          | 20.1798                     | 2.0180                      | 2.5367                     | -0.2694                          | 0.2538                          | 20.1798                | 25.3668               | -101.8411    | -129.7678      | -79.0510         | -86.7979           | -0.6053       | -0.5765         |
| 0.3799        | 0.7342 | 500  | 0.4100          | 0.1000          | 21.6333                     | 2.1633                      | 2.6378                     | -0.2586                          | 0.2554                          | 21.6333                | 26.3782               | -106.3940    | -135.7742      | -79.0510         | -86.7979           | -0.6186       | -0.5922         |
| 0.4868        | 0.8811 | 600  | 0.4055          | 0.1000          | 21.7395                     | 2.1740                      | 2.6342                     | -0.2573                          | 0.2541                          | 21.7395                | 26.3422               | -105.8801    | -135.3665      | -79.0510         | -86.7979           | -0.6200       | -0.5940         |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4