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This model is a fine-tuned version of abacusai/Smaug-34B-v0.1 on the oncc_medqa_instruct dataset.

Training procedure

git clone https://github.com/chenhaodev/LLaMA-Factory; cd LLaMA-Factory; pip install -r requirements.txt;
python create_pods.py 'Qwen/Qwen-72B' 'NVIDIA A100 80GB PCIe' 1 xxx xxx xxx 6rhltjf914

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0005
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 20
  • num_epochs: 1.0

Training results

Framework versions

  • PEFT 0.8.2
  • Transformers 4.37.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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