---
library_name: transformers
license: apache-2.0
base_model: jackf857/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452
tags:
- alignment-handbook
- new-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: qwen3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.45-s_star-0.85
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# qwen3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.45-s_star-0.85

This model is a fine-tuned version of [jackf857/qwen3-8b-base-sft-hh-harmless-4xh200-batch-64-20260417-214452](https://huggingface.co/jackf857/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: 0.5468
- Fcm Dpo/beta: 0.5703
- Margin Dpo/margin Mean: 1.5468
- Margin Dpo/margin Std: 2.5975
- Logps/chosen: -82.0159
- Logps/rejected: -93.3573
- Logps/ref Chosen: -86.9018
- Logps/ref Rejected: -96.6964
- Logits/chosen: 1.7134
- Logits/rejected: 1.6065

## 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 | Fcm Dpo/beta | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 1.325         | 0.1512 | 100  | 0.6541          | 0.1000       | 0.9036                 | 1.9803                | -86.1995     | -96.8977       | -86.9018         | -96.6964           | 1.6835        | 1.5698          |
| 1.1881        | 0.3023 | 200  | 0.5625          | 0.6970       | 1.2537                 | 2.2271                | -78.6161     | -89.6644       | -86.9018         | -96.6964           | 1.8627        | 1.7409          |
| 1.1394        | 0.4535 | 300  | 0.5554          | 0.6672       | 1.1965                 | 2.1012                | -79.8050     | -90.7961       | -86.9018         | -96.6964           | 1.8760        | 1.7587          |
| 1.1945        | 0.6047 | 400  | 0.5504          | 0.6382       | 1.3377                 | 2.2885                | -81.0971     | -92.2295       | -86.9018         | -96.6964           | 1.9273        | 1.8112          |
| 1.0818        | 0.7559 | 500  | 0.5445          | 0.5119       | 1.5736                 | 2.6447                | -81.9627     | -93.3309       | -86.9018         | -96.6964           | 1.8607        | 1.7468          |
| 1.1017        | 0.9070 | 600  | 0.5468          | 0.5703       | 1.5468                 | 2.5975                | -82.0159     | -93.3573       | -86.9018         | -96.6964           | 1.7134        | 1.6065          |


### Framework versions

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