---
base_model: ajibawa-2023/Code-Llama-3-8B
library_name: peft
license: llama3
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Code-Llama-3-8B-cars
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/evg_maslov/leap71/runs/4ywzr92y)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/evg_maslov/leap71/runs/4ywzr92y)
# Code-Llama-3-8B-cars

This model is a fine-tuned version of [ajibawa-2023/Code-Llama-3-8B](https://huggingface.co/ajibawa-2023/Code-Llama-3-8B) on an unknown dataset.

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 1

### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0