---
base_model: meta-llama/Meta-Llama-3-8B
library_name: peft
license: llama3
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: llama2-pycodestyle
  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. -->

# llama2-pycodestyle

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2778
- Accuracy: 0.95

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8528        | 1.0   | 60   | 0.3275          | 0.9583   |
| 0.5128        | 2.0   | 120  | 0.9560          | 0.9083   |
| 0.5218        | 3.0   | 180  | 0.4518          | 0.8417   |
| 0.6752        | 4.0   | 240  | 2.0151          | 0.825    |
| 0.4693        | 5.0   | 300  | 0.2778          | 0.95     |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1