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--- |
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tags: |
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- LoRA |
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- QLoRa |
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- Merged LoRA Model |
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model-index: |
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- name: sql-guanaco-13b-merged |
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results: [] |
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datasets: |
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- richardr1126/sql-create-context_guanaco_style |
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spaces: |
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- richardr1126/sql-guanaco-13b-demo |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# sql-guanaco-13b-merged |
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- This is a merged LoRA model that can be used with AutoModelForCausalLM or LlamaModelForCausalLM. |
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- It is a combination of [richardr1126/guanaco-13b-merged](https://huggingface.co/richardr1126/guanaco-13b-merged) + [richardr1126/lora-sql-guanaco-13b-adapter](https://huggingface.co/richardr1126/lora-sql-guanaco-13b-adapter). |
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- 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. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.03 |
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- training_steps: 1875 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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## Citation |
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```bibtex |
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@article{dettmers2023qlora, |
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title={QLoRA: Efficient Finetuning of Quantized LLMs}, |
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author={Dettmers, Tim and Pagnoni, Artidoro and Holtzman, Ari and Zettlemoyer, Luke}, |
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journal={arXiv preprint arXiv:2305.14314}, |
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year={2023} |
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} |
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``` |
