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---
library_name: peft
license: cc-by-nc-4.0
language:
- ja
tags:
- llama2
---
⚠️⚠️⚠️
Only for research purpose.
Do not use it for medical purpose.
⚠️⚠️⚠️
This model is an instruction-tuned model of Llama2-70B with our own medical Q&A dataset.
## Method
QLoRA
## Parameters
- batch_size = 512
- max_steps = 30000 (around 6.89 epochs)
- source_max_len = 512
- target_max_len = 512
## Training time
1617017 seconds on NVIDIA A100 x 4 (not fully used)
## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions
- PEFT 0.4.0
### How to cite
本データを利用する場合は以下の文献の引用をご検討ください.
```
@article{sukeda2023jmedlora,
title={{JMedLoRA: Medical Domain Adaptation on Japanese Large Language Models using Instruction-tuning}},
author={Sukeda, Issey and Suzuki, Masahiro and Sakaji, Hiroki and Kodera, Satoshi},
journal={arXiv preprint arXiv:2310.10083},
year={2023}
}
``` |