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

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: 1.2244
- Rewards/chosen: -0.0088
- Rewards/rejected: -0.0106
- Rewards/accuracies: 0.6028
- Rewards/margins: 0.0018
- Logps/rejected: -1.0607
- Logps/chosen: -0.8758
- Logits/rejected: -0.4873
- Logits/chosen: -0.5022
- Nll Loss: 1.2174
- Log Odds Ratio: -0.6565
- Log Odds Chosen: 0.2857

## 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: 4
- total_train_batch_size: 128
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 5.2395        | 0.4188 | 200  | 1.2644          | -0.0088        | -0.0107          | 0.6008             | 0.0018          | -1.0672        | -0.8826      | -0.4935         | -0.5068       | 1.2561   | -0.6568        | 0.2836          |
| 4.9046        | 0.8377 | 400  | 1.2244          | -0.0088        | -0.0106          | 0.6028             | 0.0018          | -1.0607        | -0.8758      | -0.4873         | -0.5022       | 1.2174   | -0.6565        | 0.2857          |


### Framework versions

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