---
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-0.4
  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-0.4

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: 0.6083
- Fcm Dpo/beta: 0.0011
- Margin Dpo/margin Mean: 279.8645
- Margin Dpo/margin Std: 623.9760
- Logps/chosen: -820.5049
- Logps/rejected: -1108.1163
- Logps/ref Chosen: -79.0510
- Logps/ref Rejected: -86.7979
- Logits/chosen: -1.0094
- Logits/rejected: -1.0070

## 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 |
|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 1.0859        | 0.2937 | 200  | 0.6270          | 0.0044       | 56.4595                | 146.7244              | -222.9299    | -287.1363      | -79.0510         | -86.7979           | -0.3344       | -0.3206         |
| 0.9641        | 0.5874 | 400  | 0.6132          | 0.0016       | 152.0758               | 334.0150              | -501.3864    | -661.2091      | -79.0510         | -86.7979           | -0.5097       | -0.4990         |
| 1.1787        | 0.8811 | 600  | 0.6083          | 0.0011       | 279.8645               | 623.9760              | -820.5049    | -1108.1163     | -79.0510         | -86.7979           | -1.0094       | -1.0070         |


### Framework versions

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