---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Llama0-3-8b-ultra-p-0.05-lr1e-6-e1
  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. -->

# Llama0-3-8b-ultra-p-0.05-lr1e-6-e1

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5155
- Rewards/chosen: -0.8052
- Rewards/rejected: -1.6601
- Rewards/accuracies: 0.75
- Rewards/margins: 0.8549
- Logps/rejected: -430.6040
- Logps/chosen: -337.1520
- Logits/rejected: 0.5600
- Logits/chosen: 0.4444

## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5887        | 0.2060 | 100  | 0.5813          | -0.4118        | -0.7745          | 0.6875             | 0.3628          | -342.0493      | -297.8121    | 0.1168          | 0.0514        |
| 0.5536        | 0.4119 | 200  | 0.5446          | -0.6533        | -1.3097          | 0.7031             | 0.6564          | -395.5632      | -321.9608    | 0.3951          | 0.2772        |
| 0.5319        | 0.6179 | 300  | 0.5262          | -0.6809        | -1.4161          | 0.7344             | 0.7353          | -406.2091      | -324.7231    | 0.4856          | 0.3738        |
| 0.5268        | 0.8239 | 400  | 0.5195          | -0.7599        | -1.5725          | 0.7344             | 0.8126          | -421.8436      | -332.6288    | 0.5181          | 0.3998        |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1