README.md

---
tags:
- LoRA
- QLoRa
- LoRA Adapter
- LLaMA
model-index:
- name: lora-sql-guanaco-13b-adapter
  results: []
datasets:
- richardr1126/sql-create-context_guanaco_style
spaces:
  - richardr1126/NL2SQL-Guanaco-Chat
---

# lora-sql-guanaco-13b-adapter

This is a LoRA adapter for [richardr1126/guanaco-13b-merged](https://huggingface.co/richardr1126/guanaco-13b-merged), or any other merged guanaco-13b model, fine tuned from LLaMA.
<br>
This LoRA was fine-tuned using QLoRA techniques on the [richardr1126/sql-create-context_guanaco_style](https://huggingface.co/datasets/richardr1126/sql-create-context_guanaco_style) dataset.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 1875
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3

## Citation

```bibtex
@article{dettmers2023qlora,
  title={QLoRA: Efficient Finetuning of Quantized LLMs},
  author={Dettmers, Tim and Pagnoni, Artidoro and Holtzman, Ari and Zettlemoyer, Luke},
  journal={arXiv preprint arXiv:2305.14314},
  year={2023}
}
```