chenhaodev/yi-34b-llama-onc-v1

model-update

This model is a fine-tuned version of chargoddard/Yi-34B-Llama 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 'chargoddard/Yi-34B-Llama' 'NVIDIA A100 80GB PCIe' 1  xxx xxx xxx "--per_device_train_batch_size 4 --gradient_accumulation_steps 4 --lora_target q_proj,v_proj --template llama2 --dataset oncc_medqa_instruct" 902i850eaw

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