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# model-update

This model is a fine-tuned version of [chargoddard/Yi-34B-Llama](https://huggingface.co/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
{"license": "other", "library_name": "peft", "tags": ["llama-factory", "lora", "generated_from_trainer"], "base_model": "chargoddard/Yi-34B-Llama", "model-index": [{"name": "model-update", "results": []}]}
peft safetensors llama-factory lora generated_from_trainer base_model:chargoddard/Yi-34B-Llama license:other region:us