Instruction Tuning LLAMA3
This repo uses the torchtune for instruction tuning the llama3 pretrained model on mathematical tasks using LORA.
Wandb report link
https://wandb.ai/som/torchtune_llama3?nw=nwusersom
Instruction_tuned Model
https://huggingface.co./Someshfengde/llama-3-instruction-tuned-AIMO
Original metallama model
https://huggingface.co./meta-llama/Meta-Llama-3-8B
For running this project
> pip install poetry
> poetry install
Further commands over shell terminal
To download the model
tune download meta-llama/Meta-Llama-3-8B \
--output-dir llama3-8b-hf \
--hf-token <HF_TOKEN>
To start instruction tuning with lora and torchtune
tune run lora_finetune_single_device --config ./lora_finetune_single_device.yaml
To quantize the model
tune run quantize --config ./quantization_config.yaml
To generate inference from model.
tune run generate --config ./generation_config.yaml \
prompt="what is 2 + 2."
Dataset used
https://huggingface.co./datasets/Someshfengde/AIMO_dataset
Evaluations
To run evaluations
tune run eleuther_eval --config ./eval_config.yaml
TruthfulQA: 0.42
MMLU Abstract Algebra: 0.35
MATHQA: 0.33
Agieval_sat_math: 0.31
