---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-hh-harmless-4xh200
tags:
- alignment-handbook
- new-dpo
- generated_from_trainer
datasets:
- Anthropic/hh-rlhf
model-index:
- name: llama-3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.5-s_star-1.0
  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-harmless-4xh200-batch-64-q_t-0.5-s_star-1.0

This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-harmless-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-harmless-4xh200) on the Anthropic/hh-rlhf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5680
- Fcm Dpo/beta: 0.6569
- Margin Dpo/margin Mean: 1.3983
- Margin Dpo/margin Std: 2.4811
- Logps/chosen: -77.8234
- Logps/rejected: -83.9112
- Logps/ref Chosen: -74.8595
- Logps/ref Rejected: -79.5490
- Logits/chosen: 0.1962
- Logits/rejected: 0.1585

## 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 |
|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 1.0309        | 0.3023 | 200  | 0.6114          | 1.5800       | 0.5045                 | 1.0288                | -75.8633     | -81.0573       | -74.8595         | -79.5490           | 0.1685        | 0.1337          |
| 1.0799        | 0.6047 | 400  | 0.5736          | 0.7420       | 1.1067                 | 2.0391                | -77.2471     | -83.0433       | -74.8595         | -79.5490           | 0.2053        | 0.1675          |
| 1.0999        | 0.9070 | 600  | 0.5680          | 0.6569       | 1.3983                 | 2.4811                | -77.8234     | -83.9112       | -74.8595         | -79.5490           | 0.1962        | 0.1585          |


### Framework versions

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