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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

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MMLU Abstract Algebra: 0.35

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MATHQA: 0.33

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Agieval_sat_math: 0.31

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