---
library_name: transformers
license: llama3.1
base_model: meta-llama/Llama-3.1-8B
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- argilla-warehouse/magpie-ultra-v1.0
model-index:
- name: Llama-3.1-8B-MagPie-Ultra-500k
  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-3.1-8B-MagPie-Ultra-500k

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B](https://huggingface.co./meta-llama/Llama-3.1-8B) on the argilla-warehouse/magpie-ultra-v1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5953

## 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-05
- 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6117        | 0.9998 | 1458 | 0.6077          |
| 0.5287        | 1.9997 | 2916 | 0.5882          |
| 0.4775        | 2.9995 | 4374 | 0.5953          |


### Framework versions

- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0