---
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-0.025
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama0-3-8b-ultra-p-0.025

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: 0.5336
- Rewards/chosen: -0.9176
- Rewards/rejected: -1.7954
- Rewards/accuracies: 0.7266
- Rewards/margins: 0.8778
- Logps/rejected: -444.2013
- Logps/chosen: -348.3104
- Logits/rejected: 0.6139
- Logits/chosen: 0.4767

## 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: 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: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6219        | 0.2060 | 100  | 0.6185          | -0.3528        | -0.5814          | 0.6797             | 0.2287          | -322.8062      | -291.8294    | 0.3035          | 0.2418        |
| 0.5957        | 0.4119 | 200  | 0.5909          | -0.4280        | -0.7949          | 0.6875             | 0.3669          | -344.1528      | -299.3566    | 0.2675          | 0.1885        |
| 0.5718        | 0.6179 | 300  | 0.5747          | -0.5426        | -1.0432          | 0.6797             | 0.5006          | -368.9808      | -310.8154    | 0.4283          | 0.3112        |
| 0.5604        | 0.8239 | 400  | 0.5587          | -0.5860        | -1.1683          | 0.7031             | 0.5824          | -381.4986      | -315.1523    | 0.4728          | 0.3510        |
| 0.5212        | 1.0299 | 500  | 0.5435          | -0.7801        | -1.5211          | 0.7344             | 0.7410          | -416.7767      | -334.5627    | 0.5275          | 0.3937        |
| 0.4671        | 1.2358 | 600  | 0.5421          | -0.9911        | -1.8546          | 0.7109             | 0.8635          | -450.1224      | -355.6647    | 0.6644          | 0.5299        |
| 0.4778        | 1.4418 | 700  | 0.5348          | -0.9156        | -1.7871          | 0.7266             | 0.8715          | -443.3745      | -348.1178    | 0.6300          | 0.4953        |
| 0.4791        | 1.6478 | 800  | 0.5330          | -0.9374        | -1.8128          | 0.7266             | 0.8754          | -445.9473      | -350.2950    | 0.6640          | 0.5278        |
| 0.4831        | 1.8538 | 900  | 0.5340          | -0.9312        | -1.8200          | 0.7266             | 0.8888          | -446.6618      | -349.6732    | 0.6213          | 0.4847        |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.20.0