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- ---
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- library_name: transformers
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- license: other
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- base_model: meta-llama/Meta-Llama-3-8B-Instruct
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- tags:
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- - llama-factory
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- - full
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- - generated_from_trainer
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- model-index:
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- - name: sft
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- results: []
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- ---
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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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-
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- # sft
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-
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- This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the cwe_tune_autodan dataset.
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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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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- - 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: 16
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- - total_eval_batch_size: 64
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- - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- - lr_scheduler_type: cosine
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- - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 3.0
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-
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- ### Training results
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-
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-
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-
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- ### Framework versions
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-
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- - Transformers 4.48.2
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- - Pytorch 2.6.0+cu124
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- - Datasets 3.2.0
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- - Tokenizers 0.21.0
 
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+ Backbone model of RedCoder