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--- |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-70B-Instruct |
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model-index: |
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- name: lora_Meta-Llama-3-70B_derta |
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results: [] |
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license: apache-2.0 |
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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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# lora_Meta-Llama-3-70B_derta |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) on the [Evol-Instruct](https://huggingface.co/datasets/WizardLMTeam/WizardLM_evol_instruct_70k) and [BeaverTails](https://huggingface.co/datasets/PKU-Alignment/BeaverTails) dataset. |
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## Model description |
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Please refer to the paper [Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training](https://arxiv.org/abs/2407.09121) and GitHub [DeRTa](https://github.com/RobustNLP/DeRTa). |
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The model is continued train 100 steps with DeRTa on LLaMA3-70B-Instruct. |
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Input format: |
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``` |
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[INST] Your Instruction [\INST] |
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``` |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 1 |
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- seed: 1 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 2.0 |
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The lora config is: |
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``` |
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{ |
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"lora_r": 96, |
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"lora_alpha": 16, |
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"lora_dropout": 0.05, |
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"lora_target_modules": [ |
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"q_proj", |
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"v_proj", |
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"k_proj", |
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"o_proj", |
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"gate_proj", |
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"down_proj", |
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"up_proj", |
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"w1", |
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"w2", |
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"w3" |
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] |
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} |
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``` |
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### Training results |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.10.0 |
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- Tokenizers 0.19.1 |
