---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- generator
model-index:
- name: llama3-lora-codigopenal-dir
  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. -->

# llama3-lora-codigopenal-dir

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 the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6629

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1399
- gradient_accumulation_steps: 4
- total_train_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
- training_steps: 1000

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.4127        | 3.6364  | 20   | 1.4021          |
| 1.3428        | 7.2727  | 40   | 1.2777          |
| 1.1822        | 10.9091 | 60   | 1.1052          |
| 0.9983        | 14.5455 | 80   | 0.9440          |
| 0.825         | 18.1818 | 100  | 0.7987          |
| 0.7081        | 21.8182 | 120  | 0.7390          |
| 0.6527        | 25.4545 | 140  | 0.7078          |
| 0.6046        | 29.0909 | 160  | 0.6855          |
| 0.566         | 32.7273 | 180  | 0.6699          |
| 0.5268        | 36.3636 | 200  | 0.6610          |
| 0.4891        | 40.0    | 220  | 0.6568          |
| 0.4519        | 43.6364 | 240  | 0.6629          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.1.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1