---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: lambda-llama-3-8b-dpo-test
  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. -->

# lambda-llama-3-8b-dpo-test

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5772
- Rewards/chosen: -1.0430
- Rewards/rejected: -1.6270
- Rewards/accuracies: 0.7063
- Rewards/margins: 0.5841
- Logps/rejected: -558.6804
- Logps/chosen: -509.0577
- Logits/rejected: -2.5324
- Logits/chosen: -2.3779

## 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: 2e-07
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6351        | 0.2093 | 100  | 0.6359          | -0.6754        | -0.9179          | 0.6746             | 0.2426          | -487.7697      | -472.2982    | -2.4565         | -2.2922       |
| 0.6101        | 0.4186 | 200  | 0.5990          | -0.7996        | -1.1966          | 0.7143             | 0.3970          | -515.6393      | -484.7244    | -2.4477         | -2.2933       |
| 0.5738        | 0.6279 | 300  | 0.5819          | -1.0722        | -1.6607          | 0.7143             | 0.5885          | -562.0454      | -511.9821    | -2.5003         | -2.3506       |
| 0.5808        | 0.8373 | 400  | 0.5776          | -1.0426        | -1.6196          | 0.7063             | 0.5769          | -557.9310      | -509.0269    | -2.6060         | -2.4454       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1