---
library_name: transformers
base_model: llama-3-8b-base-sft-hh-harmless-4xh200-batch-64
tags:
- alignment-handbook
- beta-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: llama-3-8b-base-beta-dpo-hh-harmless-4xh200-batch-64-20260417-233539
  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-beta-dpo-hh-harmless-4xh200-batch-64-20260417-233539

This model is a fine-tuned version of [llama-3-8b-base-sft-hh-harmless-4xh200-batch-64](https://huggingface.co/llama-3-8b-base-sft-hh-harmless-4xh200-batch-64) on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8203
- Beta Dpo/beta: 0.1705
- Beta Dpo/loss Margin Mean: 16.6192
- Beta Dpo/beta Margin Mean: 3.5151
- Beta Dpo/beta Margin Std: 4.7567
- Beta Dpo/beta Margin Grad Mean: -0.3392
- Beta Dpo/beta Margin Grad Std: 0.2229
- Beta Dpo/gap Mean: 16.4768
- Beta Dpo/gap Std: 28.4131
- Beta Dpo/beta Used Raw: 0.1085
- Beta Dpo/beta Used: 0.1705
- Beta Dpo/mask Keep Frac: 1.0
- Logits/chosen: 0.5021
- Logits/rejected: 0.4487

## 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 | Beta Dpo/beta | Beta Dpo/loss Margin Mean | Beta Dpo/beta Margin Mean | Beta Dpo/beta Margin Std | Beta Dpo/beta Margin Grad Mean | Beta Dpo/beta Margin Grad Std | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:-------------:|:-------------------------:|:-------------------------:|:------------------------:|:------------------------------:|:-----------------------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
| 1.3014        | 0.1512 | 100  | 0.6391          | 0.1183        | 1.3224                    | 0.1789                    | 0.4749                   | -0.4595                        | 0.1057                        | 1.0180            | 3.3360           | 0.1183                 | 0.1183             | 1.0                     | 0.2572        | 0.2207          |
| 0.9318        | 0.3023 | 200  | 0.5939          | 0.0752        | 9.0802                    | 0.8670                    | 1.1566                   | -0.3975                        | 0.1333                        | 10.1709           | 15.2637          | 0.0346                 | 0.0752             | 1.0                     | 0.4250        | 0.3786          |
| 1.1289        | 0.4535 | 300  | 0.6938          | 0.1151        | 14.7143                   | 2.1435                    | 2.8181                   | -0.3684                        | 0.1767                        | 15.7264           | 23.2621          | 0.0393                 | 0.1151             | 1.0                     | 0.5036        | 0.4522          |
| 1.3777        | 0.6047 | 400  | 0.6486          | 0.0698        | 13.2713                   | 1.2326                    | 1.6702                   | -0.4066                        | 0.1228                        | 15.5137           | 23.8374          | -0.0345                | 0.0698             | 1.0                     | 0.4392        | 0.3876          |
| 1.1911        | 0.7559 | 500  | 0.6888          | 0.0936        | 16.0572                   | 1.9620                    | 2.5727                   | -0.3866                        | 0.1471                        | 17.9087           | 28.7161          | -0.0111                | 0.0936             | 1.0                     | 0.5027        | 0.4490          |
| 1.0347        | 0.9070 | 600  | 0.8203          | 0.1705        | 16.6192                   | 3.5151                    | 4.7567                   | -0.3392                        | 0.2229                        | 16.4768           | 28.4131          | 0.1085                 | 0.1705             | 1.0                     | 0.5021        | 0.4487          |


### Framework versions

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