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Meta-Llama-3-8B-Instruct_derta_100step

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the Evol-Instruct and BeaverTails dataset. The model is continued to train 100 steps with DeRTa on LLaMA3-8B-Instruct.

Model description

Please refer to the paper Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training and GitHub DeRTa.

Input format:

[INST] Your Instruction [\INST]

Intended uses & limitations

The model is trained with DeRTa, showing a high safety performance.

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • weight_decay: 2e-5
  • eval_batch_size: 1
  • seed: 1
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 128
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 2.0

Training results

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.0+cu118
  • Datasets 2.10.0
  • Tokenizers 0.19.1
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