---
library_name: peft
license: other
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Limo_llama
  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. -->

# Limo_llama

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the Limo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7616

## 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: 8e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Use 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: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9047        | 1.0   | 12   | 0.9276          |
| 0.8453        | 2.0   | 24   | 0.8575          |
| 0.7935        | 3.0   | 36   | 0.8197          |
| 0.7744        | 4.0   | 48   | 0.7953          |
| 0.7254        | 5.0   | 60   | 0.7805          |
| 0.7332        | 6.0   | 72   | 0.7704          |
| 0.7149        | 7.0   | 84   | 0.7655          |
| 0.7298        | 8.0   | 96   | 0.7627          |
| 0.7228        | 9.0   | 108  | 0.7619          |
| 0.7103        | 10.0  | 120  | 0.7616          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.8.0+cu129
- Datasets 3.6.0
- Tokenizers 0.21.4