---
library_name: transformers
tags:
- alignment-handbook
- beta-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: qwen3-8b-base-beta-dpo-hh-harmless-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-harmless-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-helpful-4xh200-batch-64-20260417-214452` on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6518
- Beta Dpo/beta: 0.1628
- Beta Dpo/loss Margin Mean: 8.6336
- Beta Dpo/beta Margin Mean: 1.6614
- Beta Dpo/beta Margin Std: 2.5181
- Beta Dpo/beta Margin Grad Mean: -0.3428
- Beta Dpo/beta Margin Grad Std: 0.2482
- Beta Dpo/gap Mean: 7.7476
- Beta Dpo/gap Std: 14.8995
- Beta Dpo/beta Used Raw: 0.1532
- Beta Dpo/beta Used: 0.1628
- Beta Dpo/mask Keep Frac: 1.0
- Logits/chosen: 1.2071
- Logits/rejected: 1.1403

## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------------:|:-------------------------:|:-------------------------:|:------------------------:|:------------------------------:|:-----------------------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
| 1.3654        | 0.1512 | 100  | 0.6641          | 0.1110        | 0.6060                    | 0.0717                    | 0.2130                   | -0.4824                        | 0.0521                        | 0.4233            | 1.6301           | 0.1110                 | 0.1110             | 1.0                     | 1.3014        | 1.2543          |
| 0.9954        | 0.3023 | 200  | 0.6120          | 0.0999        | 4.1607                    | 0.5099                    | 0.9505                   | -0.4145                        | 0.1620                        | 4.2136            | 9.3730           | 0.0968                 | 0.0999             | 1.0                     | 0.9179        | 0.8638          |
| 1.2007        | 0.4535 | 300  | 0.6115          | 0.1346        | 6.6135                    | 1.0588                    | 1.7069                   | -0.3695                        | 0.2169                        | 6.1583            | 12.2942          | 0.1273                 | 0.1346             | 1.0                     | 1.2327        | 1.1646          |
| 1.3823        | 0.6047 | 400  | 0.5951          | 0.1019        | 6.9792                    | 0.8735                    | 1.3552                   | -0.3881                        | 0.1738                        | 7.2064            | 12.6529          | 0.0864                 | 0.1019             | 1.0                     | 1.2965        | 1.2260          |
| 1.2301        | 0.7559 | 500  | 0.6311          | 0.1290        | 8.6766                    | 1.3653                    | 2.0186                   | -0.3625                        | 0.2097                        | 8.4351            | 15.6317          | 0.1145                 | 0.1290             | 1.0                     | 1.2194        | 1.1512          |
| 1.0426        | 0.9070 | 600  | 0.6518          | 0.1628        | 8.6336                    | 1.6614                    | 2.5181                   | -0.3428                        | 0.2482                        | 7.7476            | 14.8995          | 0.1532                 | 0.1628             | 1.0                     | 1.2071        | 1.1403          |


### Framework versions

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