---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-hh-helpful-4xh200
tags:
- alignment-handbook
- new-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: llama-3-8b-base-new-dpo-hh-helpful-s_star0.85-4xh200-batch-64-20260421-233802
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama-3-8b-base-new-dpo-hh-helpful-s_star0.85-4xh200-batch-64-20260421-233802

This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-helpful-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-helpful-4xh200) on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5131
- Fcm Dpo/beta: 0.0057
- Fcm Dpo/q T: 0.3538
- Fcm Dpo/delta: 0.0491
- Fcm Dpo/margin: 139.8486
- Margin Dpo/margin Mean: 139.8486
- Margin Dpo/margin Std: 209.5895
- Logps/chosen: -511.8030
- Logps/rejected: -659.3984
- Logps/ref Chosen: -79.0510
- Logps/ref Rejected: -86.7979
- Logits/chosen: 0.2560
- Logits/rejected: 0.2786

## 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 | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:------------:|:-----------:|:-------------:|:--------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 0.8697        | 0.2937 | 200  | 0.5858          | 0.0198       | 0.3795      | 0.0634        | 38.2719        | 38.2719                | 74.7381               | -148.6721    | -194.6909      | -79.0510         | -86.7979           | -0.4905       | -0.4710         |
| 0.8159        | 0.5874 | 400  | 0.5362          | 0.0070       | 0.3603      | 0.0726        | 111.7486       | 111.7486               | 182.2796              | -360.3431    | -479.8386      | -79.0510         | -86.7979           | 0.0750        | 0.0972          |
| 0.8894        | 0.8811 | 600  | 0.5131          | 0.0057       | 0.3538      | 0.0491        | 139.8486       | 139.8486               | 209.5895              | -511.8030    | -659.3984      | -79.0510         | -86.7979           | 0.2560        | 0.2786          |


### Framework versions

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