---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
tags:
- alignment-handbook
- r-dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama-3-8b-base-r-dpo-ultrafeedback-4xh200
  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-r-dpo-ultrafeedback-4xh200

This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5080
- R Dpo/chosen Len: 291.2620
- R Dpo/rejected Len: 248.3960
- R Dpo/length Delta: 42.8660
- R Dpo/regularization Term: 0.0
- Logps/chosen: -288.0679
- Logps/rejected: -272.9751
- Logps/ref Chosen: -289.1346
- Logps/ref Rejected: -264.7782
- Logits/chosen: -0.7442
- Logits/rejected: -0.7460

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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 | R Dpo/chosen Len | R Dpo/rejected Len | R Dpo/length Delta | R Dpo/regularization Term | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:----------------:|:------------------:|:------------------:|:-------------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
| 4.178         | 0.4188 | 200  | 0.5266          | 291.2620         | 248.3960           | 42.8660            | 0.0                       | -287.2393    | -271.3152      | -289.1346        | -264.7782          | -0.7479       | -0.7490         |
| 4.0423        | 0.8377 | 400  | 0.5080          | 291.2620         | 248.3960           | 42.8660            | 0.0                       | -288.0679    | -272.9751      | -289.1346        | -264.7782          | -0.7442       | -0.7460         |


### Framework versions

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