---
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-4xh200-batch-64-q_t-0.5-s_star-0.85
  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-new-dpo-hh-helpful-4xh200-batch-64-q_t-0.5-s_star-0.85

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: 0.5312
- Fcm Dpo/beta: 0.0040
- Margin Dpo/margin Mean: 149.2117
- Margin Dpo/margin Std: 231.6038
- Logps/chosen: -579.7042
- Logps/rejected: -736.6628
- Logps/ref Chosen: -79.0510
- Logps/ref Rejected: -86.7979
- Logits/chosen: 0.3259
- Logits/rejected: 0.3477

## 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 |
|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 0.8901        | 0.2937 | 200  | 0.5793          | 0.0146       | 37.0480                | 73.5224               | -146.9453    | -191.7402      | -79.0510         | -86.7979           | -0.4808       | -0.4605         |
| 0.7153        | 0.5874 | 400  | 0.5444          | 0.0046       | 115.8499               | 187.1605              | -440.1346    | -563.7314      | -79.0510         | -86.7979           | 0.1299        | 0.1525          |
| 0.8902        | 0.8811 | 600  | 0.5312          | 0.0040       | 149.2117               | 231.6038              | -579.7042    | -736.6628      | -79.0510         | -86.7979           | 0.3259        | 0.3477          |


### Framework versions

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