sql-guanaco-13b-merged
- This is a merged LoRA model that can be used with AutoModelForCausalLM or LlamaModelForCausalLM.
- It is a combination of richardr1126/guanaco-13b-merged + richardr1126/lora-sql-guanaco-13b-adapter.
- This LoRA was fine-tuned using QLoRA techniques on the 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
@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}
}