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--- |
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license: mit |
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library_name: peft |
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tags: |
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- PEFT |
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- Qlora |
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- mistral-7b |
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- fine-tuning |
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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: mistral7b-fine-tuned-qlora |
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results: [] |
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datasets: |
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- timdettmers/openassistant-guanaco |
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pipeline_tag: text-generation |
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language: |
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- en |
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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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<img src="https://www.kdnuggets.com/wp-content/uploads/selvaraj_mistral_7bv02_finetuning_mistral_new_opensource_llm_hugging_face_3.png" alt="im" width="700" /> |
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# mistral7b-fine-tuned-qlora |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset. |
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## Usage guidance |
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Please refer to [this notebook](https://github.com/shirinyamani/mistral7b-lora-finetuning/blob/main/misral_7B_updated.ipynb) for a complete demo including notes regarding cloud deployment |
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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: 1 |
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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: 4 |
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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_steps: 2 |
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- training_steps: 10 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- PEFT 0.11.2.dev0 |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
