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babyblue26 stjordanis tumeteor

rewardedsoups's Issues

About finetuning LLAMA for summerization task

Hi all,

I was following the README in the llama folder, having run these commands

python3 train_ppo.py --task summary --dataset_name news --reward_models Tristan/gpt2_reward_summarization --output_folder ${folder_r1}
python3 train_ppo.py --task summary --dataset_name news --reward_models CogComp/bart-faithful-summary --dataset_name news-detector --reward_formats '1-0' --output_folder ${folder_r2}

python3 inference_rewardedsoups.py --task summary --dataset_name news --peft_names ${folder_r1} ${folder_r2}

The results I got are as below:

d[ 0.0 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.1 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.2 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.3 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.4 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.5 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.6 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.7 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.8 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 0.9 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]
d[ 1.0 ] = [{'LABEL_0': 1.0334709184616804, 'n': 'grs'}, {'HALLUCINATED': 1.3255301121249794, 'FAITHFUL': -0.5046869936399162, 'n': 'bfsd'}, {'length': 200}]

May I kindly ask for hints about the reason for these results? They get the same scores with different objective weights. Was it caused by not tuning the number of epochs for fine-tuning?

Kind regards,
Ethan

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