---
library_name: transformers
base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
tags:
- alignment-handbook
- beta-dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: llama-3-8b-base-beta-dpo-ultrafeedback-8xh200-20260410-201956
  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-beta-dpo-ultrafeedback-8xh200-20260410-201956

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: 0.7668
- Beta Dpo/gap Mean: 15.9231
- Beta Dpo/gap Std: 25.9660
- Beta Dpo/beta Used Raw: 0.0986
- Beta Dpo/beta Used: 0.1434
- Beta Dpo/mask Keep Frac: 1.0
- Logits/chosen: -0.8035
- Logits/rejected: -0.7974

## 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: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 | Beta Dpo/gap Mean | Beta Dpo/gap Std | Beta Dpo/beta Used Raw | Beta Dpo/beta Used | Beta Dpo/mask Keep Frac | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|:----------------:|:----------------------:|:------------------:|:-----------------------:|:-------------:|:---------------:|
| 1.1971        | 0.4188 | 200  | 0.6549          | 11.0198           | 18.6390          | 0.0997                 | 0.1243             | 1.0                     | -0.7570       | -0.7553         |
| 1.2165        | 0.8377 | 400  | 0.7668          | 15.9231           | 25.9660          | 0.0986                 | 0.1434             | 1.0                     | -0.8035       | -0.7974         |


### Framework versions

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