---
library_name: transformers
tags:
- alignment-handbook
- beta-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: qwen3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260418-012645
  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. -->

# qwen3-8b-base-beta-dpo-hh-helpful-4xh200-batch-64-20260418-012645

This model is a fine-tuned version of `/scratch/qu.yang1/dynamic-dpo-v4/outputs/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452` on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6201
- Beta Dpo/beta: 0.1744
- Beta Dpo/loss Margin Mean: 9.2097
- Beta Dpo/beta Margin Mean: 1.8984
- Beta Dpo/beta Margin Std: 2.6738
- Beta Dpo/beta Margin Grad Mean: -0.3317
- Beta Dpo/beta Margin Grad Std: 0.2463
- Beta Dpo/gap Mean: 8.2231
- Beta Dpo/gap Std: 14.9607
- Beta Dpo/beta Used Raw: 0.1592
- Beta Dpo/beta Used: 0.1744
- Beta Dpo/mask Keep Frac: 1.0
- Logits/chosen: 2.4073
- Logits/rejected: 2.4748

## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------------:|:-------------------------:|:-------------------------:|:------------------------:|:------------------------------:|:-----------------------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
| 1.3421        | 0.1468 | 100  | 0.6724          | 0.1051        | 0.4154                    | 0.0454                    | 0.1109                   | -0.4887                        | 0.0276                        | 0.3297            | 0.9661           | 0.1051                 | 0.1051             | 1.0                     | 1.9351        | 2.0227          |
| 1.1746        | 0.2937 | 200  | 0.5979          | 0.1463        | 3.4910                    | 0.5960                    | 1.1231                   | -0.3984                        | 0.1967                        | 2.7526            | 6.6589           | 0.1443                 | 0.1463             | 1.0                     | 2.4745        | 2.5521          |
| 1.0588        | 0.4405 | 300  | 0.6234          | 0.1568        | 7.0255                    | 1.3113                    | 2.0548                   | -0.3561                        | 0.2381                        | 6.2446            | 12.2876          | 0.1469                 | 0.1568             | 1.0                     | 2.5889        | 2.6667          |
| 1.0387        | 0.5874 | 400  | 0.5861          | 0.0864        | 8.3161                    | 0.9103                    | 1.2402                   | -0.3898                        | 0.1540                        | 9.0513            | 15.3829          | 0.0559                 | 0.0864             | 1.0                     | 2.2982        | 2.3580          |
| 1.3836        | 0.7342 | 500  | 0.6929          | 0.2278        | 9.2738                    | 2.4511                    | 3.5401                   | -0.3173                        | 0.2780                        | 7.2783            | 15.5833          | 0.2197                 | 0.2278             | 1.0                     | 2.3062        | 2.3664          |
| 1.1032        | 0.8811 | 600  | 0.6201          | 0.1744        | 9.2097                    | 1.8984                    | 2.6738                   | -0.3317                        | 0.2463                        | 8.2231            | 14.9607          | 0.1592                 | 0.1744             | 1.0                     | 2.4073        | 2.4748          |


### Framework versions

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